diff --git a/.gitignore b/.gitignore index 4bb0d85..36efb51 100644 --- a/.gitignore +++ b/.gitignore @@ -1,21 +1,15 @@ ._.DS_Store .DS_Store *.pyc -notebooks/models/* -notebooks/wandb/* -notebooks/dev*.ipynb -notebooks/ref*.ipynb -notebooks/exp*.ipynb -notebooks/*.txt +notebooks/* +!notebooks/dev_90_ayla_test.ipynb wandb/* .vscode/* -notebooks/my_dir/* test/test.py output.png output.svg.png array_param/* -notebooks/*.png -archieved/ScanByScan.py +archieved/* scripts/slurm_job_swaps_gpu.sh _archieved/* environment_linux64.yaml diff --git a/notebooks/dev_90_ayla_test.ipynb b/notebooks/dev_90_ayla_test.ipynb new file mode 100644 index 0000000..cac3a1c --- /dev/null +++ b/notebooks/dev_90_ayla_test.ipynb @@ -0,0 +1,17507 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from importlib import reload\n", + "from IPython.core.interactiveshell import InteractiveShell\n", + "%load_ext autoreload\n", + "InteractiveShell.ast_node_interactivity = \"all\"\n", + "import logging\n", + "logging.basicConfig(\n", + " level=logging.INFO, format=\"%(asctime)s - %(name)s - %(levelname)s - %(message)s\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-12-19 13:33:34,207 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", + "2024-12-19 13:33:34,208 - numexpr.utils - INFO - NumExpr defaulting to 8 threads.\n", + "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", + " from pandas.core import (\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import os\n", + "import sys\n", + "import matplotlib.pyplot as plt\n", + "\n", + "module_path = os.path.abspath(os.path.join(\"..\"))\n", + "if module_path not in sys.path:\n", + " sys.path.append(module_path)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Run SWAPS with example config" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", + " from pandas.core import (\n", + "2024-12-19 13:15:18> merge with cfg file /cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/utils/exp_configs/config_ayla_test_ecoli.yaml\n", + "2024-12-19 13:15:18> ==================Load data==================\n", + "2024-12-19 13:15:18> Reading mzML file\n", + "2024-12-19 13:15:25> Saving data to pickle file\n", + "2024-12-19 13:15:32> Filtered reference maxquant result by raw file: ['BBM_647_P241_02_07_ssDDA_MIA_001']\n", + "2024-12-19 13:15:32> Using multiple GPUs, device is gpu\n", + "2024-12-19 13:15:33> maxquant_exp_df size: (95925, 61)\n", + "2024-12-19 13:15:33> maxquant_exp_df size after filter by raw file ['BBM_647_P241_02_07_ssDDA_MIA_001']: (19186, 61)\n", + "2024-12-19 13:15:33> maxquant_exp_df size after removing matched precursors: (19186, 61)\n", + "2024-12-19 13:15:33> maxquant_ref_df size after removing matched precursors: (19186, 61)\n", + "2024-12-19 13:15:33> RT index range: (0.00281795921325684, 33.0010865436236)\n", + "2024-12-19 13:15:35> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/construct_dict/BarChart_exp_elution_counts.png\n", + "2024-12-19 13:15:35> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/construct_dict/BarChart_exp_elution_counts.svg\n", + "2024-12-19 13:15:35> Removing 26 decoys from file, 19160 entries left.\n", + "2024-12-19 13:15:35> Removing 222 duplicate entries from experiment file, 18938 entries left.\n", + "2024-12-19 13:15:35> Removing 26 decoys from file, 19160 entries left.\n", + "2024-12-19 13:15:35> Removing 222 duplicate entries from experiment file, 18938 entries left.\n", + "2024-12-19 13:15:35> Maxquant_ref_df columns: Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", + " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", + " 'Oxidation (M)', 'Missed cleavages', 'Proteins', 'Leading proteins',\n", + " 'Leading razor protein', 'Gene names', 'Protein names', 'Type',\n", + " 'Raw file', 'Experiment', 'MS/MS m/z', 'Charge', 'm/z', 'Mass',\n", + " 'Resolution', 'Uncalibrated - Calibrated m/z [ppm]',\n", + " 'Uncalibrated - Calibrated m/z [Da]', 'Mass error [ppm]',\n", + " 'Mass error [Da]', 'Uncalibrated mass error [ppm]',\n", + " 'Uncalibrated mass error [Da]', 'Max intensity m/z 0', 'Retention time',\n", + " 'Retention length', 'Calibrated retention time',\n", + " 'Calibrated retention time start', 'Calibrated retention time finish',\n", + " 'Retention time calibration', 'Match time difference',\n", + " 'Match m/z difference', 'Match q-value', 'Match score',\n", + " 'Number of data points', 'Number of scans', 'Number of isotopic peaks',\n", + " 'PIF', 'Fraction of total spectrum', 'Base peak fraction', 'PEP',\n", + " 'MS/MS count', 'MS/MS scan number', 'Score', 'Delta score',\n", + " 'Combinatorics', 'Intensity', 'Reverse', 'Potential contaminant', 'id',\n", + " 'Protein group IDs', 'Peptide ID', 'Mod. peptide ID', 'MS/MS IDs',\n", + " 'Best MS/MS', 'AIF MS/MS IDs', 'Oxidation (M) site IDs'],\n", + " dtype='object')\n", + "2024-12-19 13:15:35> Maxquant_exp_df columns: Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", + " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", + " 'Oxidation (M)', 'Missed cleavages', 'Proteins', 'Leading proteins',\n", + " 'Leading razor protein', 'Gene names', 'Protein names', 'Type',\n", + " 'Raw file', 'Experiment', 'MS/MS m/z', 'Charge', 'm/z', 'Mass',\n", + " 'Resolution', 'Uncalibrated - Calibrated m/z [ppm]',\n", + " 'Uncalibrated - Calibrated m/z [Da]', 'Mass error [ppm]',\n", + " 'Mass error [Da]', 'Uncalibrated mass error [ppm]',\n", + " 'Uncalibrated mass error [Da]', 'Max intensity m/z 0', 'Retention time',\n", + " 'Retention length', 'Calibrated retention time',\n", + " 'Calibrated retention time start', 'Calibrated retention time finish',\n", + " 'Retention time calibration', 'Match time difference',\n", + " 'Match m/z difference', 'Match q-value', 'Match score',\n", + " 'Number of data points', 'Number of scans', 'Number of isotopic peaks',\n", + " 'PIF', 'Fraction of total spectrum', 'Base peak fraction', 'PEP',\n", + " 'MS/MS count', 'MS/MS scan number', 'Score', 'Delta score',\n", + " 'Combinatorics', 'Intensity', 'Reverse', 'Potential contaminant', 'id',\n", + " 'Protein group IDs', 'Peptide ID', 'Mod. peptide ID', 'MS/MS IDs',\n", + " 'Best MS/MS', 'AIF MS/MS IDs', 'Oxidation (M) site IDs',\n", + " 'Time_minute_center_exp', 'MS1_frame_idx_center_exp',\n", + " 'Time_minute_left_exp', 'MS1_frame_idx_left_exp',\n", + " 'Time_minute_right_exp', 'MS1_frame_idx_right_exp'],\n", + " dtype='object')\n", + "2024-12-19 13:15:35> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/construct_dict/BarChart_candidate_overlap.png\n", + "2024-12-19 13:15:36> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/construct_dict/BarChart_candidate_overlap.svg\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/prepare_dict/prepare_dict.py:670: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", + "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", + "\n", + "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", + "\n", + "\n", + " maxquant_result_dict[\"Calibrated retention time start\"].fillna(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/prepare_dict/prepare_dict.py:675: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", + "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", + "\n", + "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", + "\n", + "\n", + " maxquant_result_dict[\"Calibrated retention time finish\"].fillna(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/prepare_dict/prepare_dict.py:704: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " maxquant_result_dict[\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/prepare_dict/prepare_dict.py:704: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " maxquant_result_dict[\n", + "2024-12-19 13:15:40> Finish. Filtered prediction dataframe dimension: (18938, 83), columns: Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", + " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", + " 'Oxidation (M)', 'Missed cleavages', 'Proteins', 'Leading proteins',\n", + " 'Leading razor protein', 'Gene names', 'Protein names', 'Type',\n", + " 'Raw file', 'Experiment', 'MS/MS m/z', 'Charge', 'm/z', 'Mass',\n", + " 'Resolution', 'Uncalibrated - Calibrated m/z [ppm]',\n", + " 'Uncalibrated - Calibrated m/z [Da]', 'Mass error [ppm]',\n", + " 'Mass error [Da]', 'Uncalibrated mass error [ppm]',\n", + " 'Uncalibrated mass error [Da]', 'Max intensity m/z 0', 'Retention time',\n", + " 'Retention length', 'Calibrated retention time',\n", + " 'Calibrated retention time start', 'Calibrated retention time finish',\n", + " 'Retention time calibration', 'Match time difference',\n", + " 'Match m/z difference', 'Match q-value', 'Match score',\n", + " 'Number of data points', 'Number of scans', 'Number of isotopic peaks',\n", + " 'PIF', 'Fraction of total spectrum', 'Base peak fraction', 'PEP',\n", + " 'MS/MS count', 'MS/MS scan number', 'Score', 'Delta score',\n", + " 'Combinatorics', 'Intensity', 'Reverse', 'Potential contaminant', 'id',\n", + " 'Protein group IDs', 'Peptide ID', 'Mod. peptide ID', 'MS/MS IDs',\n", + " 'Best MS/MS', 'AIF MS/MS IDs', 'Oxidation (M) site IDs', 'source',\n", + " 'Time_minute_center_exp', 'MS1_frame_idx_center_exp',\n", + " 'Time_minute_left_exp', 'MS1_frame_idx_left_exp',\n", + " 'Time_minute_right_exp', 'MS1_frame_idx_right_exp', 'RT_search_left',\n", + " 'RT_search_right', 'RT_search_center', 'Time_minute_center_ref',\n", + " 'MS1_frame_idx_center_ref', 'Time_minute_left_ref',\n", + " 'MS1_frame_idx_left_ref', 'Time_minute_right_ref',\n", + " 'MS1_frame_idx_right_ref', 'IsoMZ', 'IsoAbundance', 'mz_rank', 'mz_bin',\n", + " 'mz_length', 'pept_batch_idx'],\n", + " dtype='object')\n", + "2024-12-19 13:15:40> Peptide batch index: [0]\n", + "2024-12-19 13:15:40> Finished dictionary preparation and saved config to /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/config_20241219_131518_762964.yaml\n", + "2024-12-19 13:15:40> Precalculated activation not found, start Scan By Scan.\n", + "2024-12-19 13:15:40> ==================Scan By Scan==================\n", + "2024-12-19 13:15:40> -----------------Scan by Scan Optimization-----------------\n", + "2024-12-19 13:15:40> Number of batches: 5\n", + "2024-12-19 13:15:40> Generate id partitions by block.\n", + "2024-12-19 13:15:40> indices in first batch: [ 0 5 10 15 20 25 30 35 40 45 50 55 60 65\n", + " 70 75 80 85 90 95 100 105 110 115 120 125 130 135\n", + " 140 145 150 155 160 165 170 175 180 185 190 195 200 205\n", + " 210 215 220 225 230 235 240 245 250 255 260 265 270 275\n", + " 280 285 290 295 300 305 310 315 320 325 330 335 340 345\n", + " 350 355 360 365 370 375 380 385 390 395 400 405 410 415\n", + " 420 425 430 435 440 445 450 455 460 465 470 475 480 485\n", + " 490 495 500 505 510 515 520 525 530 535 540 545 550 555\n", + " 560 565 570 575 580 585 590 595 600 605 610 615 620 625\n", + " 630 635 640 645 650 655 660 665 670 675 680 685 690 695\n", + " 700 705 710 715 720 725 730 735 740 745 750 755 760 765\n", + " 770 775 780 785 790 795 800 805 810 815 820 825 830 835\n", + " 840 845 850 855 860 865 870 875 880 885 890 895 900 905\n", + " 910 915 920 925 930 935 940 945 950 955 960 965 970 975\n", + " 980 985 990 995 1000 1005 1010 1015 1020 1025 1030 1035 1040 1045\n", + " 1050 1055 1060 1065 1070 1075 1080 1085 1090 1095 1100 1105 1110 1115\n", + " 1120 1125 1130 1135 1140 1145 1150 1155 1160 1165 1170 1175 1180 1185\n", + " 1190 1195 1200 1205 1210 1215 1220 1225 1230 1235 1240 1245 1250 1255\n", + " 1260 1265 1270 1275 1280 1285 1290 1295 1300 1305 1310 1315 1320 1325\n", + " 1330 1335 1340 1345 1350 1355 1360 1365 1370 1375 1380 1385 1390 1395\n", + " 1400 1405 1410 1415 1420 1425 1430 1435 1440 1445 1450 1455 1460 1465\n", + " 1470 1475 1480 1485 1490 1495 1500 1505 1510 1515 1520 1525 1530 1535\n", + " 1540 1545 1550 1555 1560 1565 1570 1575 1580 1585 1590 1595 1600 1605\n", + " 1610 1615 1620 1625 1630 1635 1640 1645 1650 1655 1660 1665 1670 1675\n", + " 1680 1685 1690 1695 1700 1705 1710 1715 1720 1725 1730 1735 1740 1745\n", + " 1750 1755 1760 1765 1770 1775 1780 1785 1790 1795 1800 1805 1810 1815\n", + " 1820 1825 1830 1835 1840 1845 1850 1855 1860 1865 1870 1875 1880 1885\n", + " 1890 1895 1900 1905 1910 1915 1920 1925 1930 1935 1940 1945 1950 1955\n", + " 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025\n", + " 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095\n", + " 2100 2105 2110 2115 2120 2125 2130 2135 2140 2145 2150 2155 2160 2165\n", + " 2170 2175 2180 2185 2190 2195 2200 2205 2210 2215 2220 2225 2230 2235\n", + " 2240 2245 2250 2255 2260 2265 2270 2275 2280 2285 2290 2295 2300 2305\n", + " 2310 2315 2320 2325 2330 2335 2340 2345 2350 2355 2360 2365 2370 2375\n", + " 2380 2385 2390 2395 2400 2405 2410 2415]\n", + "2024-12-19 13:15:45,017 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", + "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", + " from pandas.core import (\n", + "2024-12-19 13:15:48,538 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", + "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", + " from pandas.core import (\n", + "2024-12-19 13:15:51,405 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", + "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", + " from pandas.core import (\n", + "2024-12-19 13:15:51,467 - optimization.inference - INFO - Scan time: 0.0028\n", + "2024-12-19 13:15:51,468 - optimization.inference - INFO - Number of candidates by RT in frame 0: 25\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,473 - optimization.inference - INFO - Scan time: 0.0144\n", + "2024-12-19 13:15:51,474 - optimization.inference - INFO - Number of candidates by RT in frame 5: 25\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,479 - optimization.inference - INFO - Scan time: 0.0259\n", + "2024-12-19 13:15:51,480 - optimization.inference - INFO - Number of candidates by RT in frame 10: 32\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,485 - optimization.inference - INFO - Scan time: 0.0374\n", + "2024-12-19 13:15:51,486 - optimization.inference - INFO - Number of candidates by RT in frame 15: 34\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,491 - optimization.inference - INFO - Scan time: 0.049\n", + "2024-12-19 13:15:51,492 - optimization.inference - INFO - Number of candidates by RT in frame 20: 37\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,497 - optimization.inference - INFO - Scan time: 0.0605\n", + "2024-12-19 13:15:51,498 - optimization.inference - INFO - Number of candidates by RT in frame 25: 37\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,503 - optimization.inference - INFO - Scan time: 0.072\n", + "2024-12-19 13:15:51,504 - optimization.inference - INFO - Number of candidates by RT in frame 30: 40\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,509 - optimization.inference - INFO - Scan time: 0.0836\n", + "2024-12-19 13:15:51,510 - optimization.inference - INFO - Number of candidates by RT in frame 35: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,539 - optimization.inference - INFO - Scan time: 0.1229\n", + "2024-12-19 13:15:51,540 - optimization.inference - INFO - Number of candidates by RT in frame 40: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,547 - optimization.inference - INFO - Scan time: 0.1988\n", + "2024-12-19 13:15:51,547 - optimization.inference - INFO - Number of candidates by RT in frame 45: 70\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,555 - optimization.inference - INFO - Scan time: 0.274\n", + "2024-12-19 13:15:51,556 - optimization.inference - INFO - Number of candidates by RT in frame 50: 75\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,562 - optimization.inference - INFO - Scan time: 0.3441\n", + "2024-12-19 13:15:51,563 - optimization.inference - INFO - Number of candidates by RT in frame 55: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,570 - optimization.inference - INFO - Scan time: 0.4164\n", + "2024-12-19 13:15:51,570 - optimization.inference - INFO - Number of candidates by RT in frame 60: 67\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,578 - optimization.inference - INFO - Scan time: 0.4827\n", + "2024-12-19 13:15:51,579 - optimization.inference - INFO - Number of candidates by RT in frame 65: 64\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,588 - optimization.inference - INFO - Scan time: 0.5247\n", + "2024-12-19 13:15:51,589 - optimization.inference - INFO - Number of candidates by RT in frame 70: 65\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,596 - optimization.inference - INFO - Scan time: 0.5544\n", + "2024-12-19 13:15:51,597 - optimization.inference - INFO - Number of candidates by RT in frame 75: 67\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,605 - optimization.inference - INFO - Scan time: 0.5807\n", + "2024-12-19 13:15:51,606 - optimization.inference - INFO - Number of candidates by RT in frame 80: 67\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,614 - optimization.inference - INFO - Scan time: 0.6044\n", + "2024-12-19 13:15:51,615 - optimization.inference - INFO - Number of candidates by RT in frame 85: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,623 - optimization.inference - INFO - Scan time: 0.6279\n", + "2024-12-19 13:15:51,624 - optimization.inference - INFO - Number of candidates by RT in frame 90: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,632 - optimization.inference - INFO - Scan time: 0.6434\n", + "2024-12-19 13:15:51,633 - optimization.inference - INFO - Number of candidates by RT in frame 95: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,641 - optimization.inference - INFO - Scan time: 0.6625\n", + "2024-12-19 13:15:51,642 - optimization.inference - INFO - Number of candidates by RT in frame 100: 70\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,651 - optimization.inference - INFO - Scan time: 0.6789\n", + "2024-12-19 13:15:51,652 - optimization.inference - INFO - Number of candidates by RT in frame 105: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,660 - optimization.inference - INFO - Scan time: 0.6959\n", + "2024-12-19 13:15:51,661 - optimization.inference - INFO - Number of candidates by RT in frame 110: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,669 - optimization.inference - INFO - Scan time: 0.7093\n", + "2024-12-19 13:15:51,670 - optimization.inference - INFO - Number of candidates by RT in frame 115: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,678 - optimization.inference - INFO - Scan time: 0.7278\n", + "2024-12-19 13:15:51,679 - optimization.inference - INFO - Number of candidates by RT in frame 120: 64\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,688 - optimization.inference - INFO - Scan time: 0.7568\n", + "2024-12-19 13:15:51,689 - optimization.inference - INFO - Number of candidates by RT in frame 125: 63\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,697 - optimization.inference - INFO - Scan time: 0.772\n", + "2024-12-19 13:15:51,698 - optimization.inference - INFO - Number of candidates by RT in frame 130: 61\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,706 - optimization.inference - INFO - Scan time: 0.7911\n", + "2024-12-19 13:15:51,707 - optimization.inference - INFO - Number of candidates by RT in frame 135: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,715 - optimization.inference - INFO - Scan time: 0.8122\n", + "2024-12-19 13:15:51,716 - optimization.inference - INFO - Number of candidates by RT in frame 140: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,724 - optimization.inference - INFO - Scan time: 0.834\n", + "2024-12-19 13:15:51,725 - optimization.inference - INFO - Number of candidates by RT in frame 145: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,733 - optimization.inference - INFO - Scan time: 0.8507\n", + "2024-12-19 13:15:51,733 - optimization.inference - INFO - Number of candidates by RT in frame 150: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,740 - optimization.inference - INFO - Scan time: 0.8646\n", + "2024-12-19 13:15:51,741 - optimization.inference - INFO - Number of candidates by RT in frame 155: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,748 - optimization.inference - INFO - Scan time: 0.882\n", + "2024-12-19 13:15:51,749 - optimization.inference - INFO - Number of candidates by RT in frame 160: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,756 - optimization.inference - INFO - Scan time: 0.9009\n", + "2024-12-19 13:15:51,757 - optimization.inference - INFO - Number of candidates by RT in frame 165: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,763 - optimization.inference - INFO - Scan time: 0.9199\n", + "2024-12-19 13:15:51,764 - optimization.inference - INFO - Number of candidates by RT in frame 170: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,771 - optimization.inference - INFO - Scan time: 0.9393\n", + "2024-12-19 13:15:51,772 - optimization.inference - INFO - Number of candidates by RT in frame 175: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,779 - optimization.inference - INFO - Scan time: 0.957\n", + "2024-12-19 13:15:51,780 - optimization.inference - INFO - Number of candidates by RT in frame 180: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,786 - optimization.inference - INFO - Scan time: 0.9754\n", + "2024-12-19 13:15:51,787 - optimization.inference - INFO - Number of candidates by RT in frame 185: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,794 - optimization.inference - INFO - Scan time: 1.0007\n", + "2024-12-19 13:15:51,795 - optimization.inference - INFO - Number of candidates by RT in frame 190: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,801 - optimization.inference - INFO - Scan time: 1.0158\n", + "2024-12-19 13:15:51,802 - optimization.inference - INFO - Number of candidates by RT in frame 195: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,809 - optimization.inference - INFO - Scan time: 1.039\n", + "2024-12-19 13:15:51,810 - optimization.inference - INFO - Number of candidates by RT in frame 200: 50\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,817 - optimization.inference - INFO - Scan time: 1.0567\n", + "2024-12-19 13:15:51,818 - optimization.inference - INFO - Number of candidates by RT in frame 205: 47\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,824 - optimization.inference - INFO - Scan time: 1.0771\n", + "2024-12-19 13:15:51,825 - optimization.inference - INFO - Number of candidates by RT in frame 210: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,832 - optimization.inference - INFO - Scan time: 1.0926\n", + "2024-12-19 13:15:51,833 - optimization.inference - INFO - Number of candidates by RT in frame 215: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,840 - optimization.inference - INFO - Scan time: 1.1139\n", + "2024-12-19 13:15:51,840 - optimization.inference - INFO - Number of candidates by RT in frame 220: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,847 - optimization.inference - INFO - Scan time: 1.1379\n", + "2024-12-19 13:15:51,848 - optimization.inference - INFO - Number of candidates by RT in frame 225: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,855 - optimization.inference - INFO - Scan time: 1.164\n", + "2024-12-19 13:15:51,856 - optimization.inference - INFO - Number of candidates by RT in frame 230: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,862 - optimization.inference - INFO - Scan time: 1.1803\n", + "2024-12-19 13:15:51,863 - optimization.inference - INFO - Number of candidates by RT in frame 235: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,870 - optimization.inference - INFO - Scan time: 1.1952\n", + "2024-12-19 13:15:51,871 - optimization.inference - INFO - Number of candidates by RT in frame 240: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,877 - optimization.inference - INFO - Scan time: 1.2106\n", + "2024-12-19 13:15:51,878 - optimization.inference - INFO - Number of candidates by RT in frame 245: 47\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,885 - optimization.inference - INFO - Scan time: 1.2254\n", + "2024-12-19 13:15:51,886 - optimization.inference - INFO - Number of candidates by RT in frame 250: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,893 - optimization.inference - INFO - Scan time: 1.2389\n", + "2024-12-19 13:15:51,894 - optimization.inference - INFO - Number of candidates by RT in frame 255: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,900 - optimization.inference - INFO - Scan time: 1.2572\n", + "2024-12-19 13:15:51,901 - optimization.inference - INFO - Number of candidates by RT in frame 260: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,908 - optimization.inference - INFO - Scan time: 1.276\n", + "2024-12-19 13:15:51,909 - optimization.inference - INFO - Number of candidates by RT in frame 265: 49\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,916 - optimization.inference - INFO - Scan time: 1.2978\n", + "2024-12-19 13:15:51,917 - optimization.inference - INFO - Number of candidates by RT in frame 270: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,924 - optimization.inference - INFO - Scan time: 1.3153\n", + "2024-12-19 13:15:51,925 - optimization.inference - INFO - Number of candidates by RT in frame 275: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,931 - optimization.inference - INFO - Scan time: 1.3343\n", + "2024-12-19 13:15:51,932 - optimization.inference - INFO - Number of candidates by RT in frame 280: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,939 - optimization.inference - INFO - Scan time: 1.3525\n", + "2024-12-19 13:15:51,940 - optimization.inference - INFO - Number of candidates by RT in frame 285: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,947 - optimization.inference - INFO - Scan time: 1.3695\n", + "2024-12-19 13:15:51,948 - optimization.inference - INFO - Number of candidates by RT in frame 290: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,955 - optimization.inference - INFO - Scan time: 1.3857\n", + "2024-12-19 13:15:51,956 - optimization.inference - INFO - Number of candidates by RT in frame 295: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,964 - optimization.inference - INFO - Scan time: 1.4028\n", + "2024-12-19 13:15:51,964 - optimization.inference - INFO - Number of candidates by RT in frame 300: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,971 - optimization.inference - INFO - Scan time: 1.4211\n", + "2024-12-19 13:15:51,972 - optimization.inference - INFO - Number of candidates by RT in frame 305: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,979 - optimization.inference - INFO - Scan time: 1.4381\n", + "2024-12-19 13:15:51,980 - optimization.inference - INFO - Number of candidates by RT in frame 310: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,987 - optimization.inference - INFO - Scan time: 1.4551\n", + "2024-12-19 13:15:51,988 - optimization.inference - INFO - Number of candidates by RT in frame 315: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:51,995 - optimization.inference - INFO - Scan time: 1.4707\n", + "2024-12-19 13:15:51,996 - optimization.inference - INFO - Number of candidates by RT in frame 320: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,003 - optimization.inference - INFO - Scan time: 1.4855\n", + "2024-12-19 13:15:52,003 - optimization.inference - INFO - Number of candidates by RT in frame 325: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,011 - optimization.inference - INFO - Scan time: 1.5011\n", + "2024-12-19 13:15:52,011 - optimization.inference - INFO - Number of candidates by RT in frame 330: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,019 - optimization.inference - INFO - Scan time: 1.5185\n", + "2024-12-19 13:15:52,019 - optimization.inference - INFO - Number of candidates by RT in frame 335: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,027 - optimization.inference - INFO - Scan time: 1.5418\n", + "2024-12-19 13:15:52,027 - optimization.inference - INFO - Number of candidates by RT in frame 340: 50\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,035 - optimization.inference - INFO - Scan time: 1.556\n", + "2024-12-19 13:15:52,035 - optimization.inference - INFO - Number of candidates by RT in frame 345: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,043 - optimization.inference - INFO - Scan time: 1.5793\n", + "2024-12-19 13:15:52,043 - optimization.inference - INFO - Number of candidates by RT in frame 350: 54\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,051 - optimization.inference - INFO - Scan time: 1.6081\n", + "2024-12-19 13:15:52,052 - optimization.inference - INFO - Number of candidates by RT in frame 355: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,058 - optimization.inference - INFO - Scan time: 1.65\n", + "2024-12-19 13:15:52,059 - optimization.inference - INFO - Number of candidates by RT in frame 360: 71\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,064 - optimization.inference - INFO - Scan time: 1.6768\n", + "2024-12-19 13:15:52,065 - optimization.inference - INFO - Number of candidates by RT in frame 365: 80\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,072 - optimization.inference - INFO - Scan time: 1.7092\n", + "2024-12-19 13:15:52,073 - optimization.inference - INFO - Number of candidates by RT in frame 370: 91\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,081 - optimization.inference - INFO - Scan time: 1.7511\n", + "2024-12-19 13:15:52,082 - optimization.inference - INFO - Number of candidates by RT in frame 375: 114\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,092 - optimization.inference - INFO - Scan time: 1.8248\n", + "2024-12-19 13:15:52,092 - optimization.inference - INFO - Number of candidates by RT in frame 380: 126\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,102 - optimization.inference - INFO - Scan time: 1.9107\n", + "2024-12-19 13:15:52,103 - optimization.inference - INFO - Number of candidates by RT in frame 385: 129\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,112 - optimization.inference - INFO - Scan time: 1.9869\n", + "2024-12-19 13:15:52,113 - optimization.inference - INFO - Number of candidates by RT in frame 390: 108\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,120 - optimization.inference - INFO - Scan time: 2.0517\n", + "2024-12-19 13:15:52,121 - optimization.inference - INFO - Number of candidates by RT in frame 395: 107\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,129 - optimization.inference - INFO - Scan time: 2.1279\n", + "2024-12-19 13:15:52,130 - optimization.inference - INFO - Number of candidates by RT in frame 400: 107\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,137 - optimization.inference - INFO - Scan time: 2.2075\n", + "2024-12-19 13:15:52,138 - optimization.inference - INFO - Number of candidates by RT in frame 405: 127\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,152 - optimization.inference - INFO - Scan time: 2.2869\n", + "2024-12-19 13:15:52,153 - optimization.inference - INFO - Number of candidates by RT in frame 410: 162\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,164 - optimization.inference - INFO - Scan time: 2.372\n", + "2024-12-19 13:15:52,165 - optimization.inference - INFO - Number of candidates by RT in frame 415: 182\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,175 - optimization.inference - INFO - Scan time: 2.4571\n", + "2024-12-19 13:15:52,176 - optimization.inference - INFO - Number of candidates by RT in frame 420: 191\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,187 - optimization.inference - INFO - Scan time: 2.5439\n", + "2024-12-19 13:15:52,187 - optimization.inference - INFO - Number of candidates by RT in frame 425: 190\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,198 - optimization.inference - INFO - Scan time: 2.6283\n", + "2024-12-19 13:15:52,199 - optimization.inference - INFO - Number of candidates by RT in frame 430: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,211 - optimization.inference - INFO - Scan time: 2.7143\n", + "2024-12-19 13:15:52,212 - optimization.inference - INFO - Number of candidates by RT in frame 435: 217\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,225 - optimization.inference - INFO - Scan time: 2.8001\n", + "2024-12-19 13:15:52,226 - optimization.inference - INFO - Number of candidates by RT in frame 440: 231\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,240 - optimization.inference - INFO - Scan time: 2.8856\n", + "2024-12-19 13:15:52,240 - optimization.inference - INFO - Number of candidates by RT in frame 445: 226\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,253 - optimization.inference - INFO - Scan time: 2.9716\n", + "2024-12-19 13:15:52,253 - optimization.inference - INFO - Number of candidates by RT in frame 450: 232\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,266 - optimization.inference - INFO - Scan time: 3.0577\n", + "2024-12-19 13:15:52,267 - optimization.inference - INFO - Number of candidates by RT in frame 455: 227\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,279 - optimization.inference - INFO - Scan time: 3.1438\n", + "2024-12-19 13:15:52,279 - optimization.inference - INFO - Number of candidates by RT in frame 460: 225\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,290 - optimization.inference - INFO - Scan time: 3.2298\n", + "2024-12-19 13:15:52,291 - optimization.inference - INFO - Number of candidates by RT in frame 465: 226\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,301 - optimization.inference - INFO - Scan time: 3.3157\n", + "2024-12-19 13:15:52,302 - optimization.inference - INFO - Number of candidates by RT in frame 470: 226\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,312 - optimization.inference - INFO - Scan time: 3.4021\n", + "2024-12-19 13:15:52,312 - optimization.inference - INFO - Number of candidates by RT in frame 475: 214\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,327 - optimization.inference - INFO - Scan time: 3.4883\n", + "2024-12-19 13:15:52,328 - optimization.inference - INFO - Number of candidates by RT in frame 480: 217\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,337 - optimization.inference - INFO - Scan time: 3.5741\n", + "2024-12-19 13:15:52,338 - optimization.inference - INFO - Number of candidates by RT in frame 485: 213\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,348 - optimization.inference - INFO - Scan time: 3.6598\n", + "2024-12-19 13:15:52,348 - optimization.inference - INFO - Number of candidates by RT in frame 490: 214\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,360 - optimization.inference - INFO - Scan time: 3.7457\n", + "2024-12-19 13:15:52,361 - optimization.inference - INFO - Number of candidates by RT in frame 495: 210\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,372 - optimization.inference - INFO - Scan time: 3.8311\n", + "2024-12-19 13:15:52,373 - optimization.inference - INFO - Number of candidates by RT in frame 500: 198\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,384 - optimization.inference - INFO - Scan time: 3.9164\n", + "2024-12-19 13:15:52,385 - optimization.inference - INFO - Number of candidates by RT in frame 505: 200\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,395 - optimization.inference - INFO - Scan time: 4.0018\n", + "2024-12-19 13:15:52,396 - optimization.inference - INFO - Number of candidates by RT in frame 510: 184\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,407 - optimization.inference - INFO - Scan time: 4.0878\n", + "2024-12-19 13:15:52,408 - optimization.inference - INFO - Number of candidates by RT in frame 515: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,418 - optimization.inference - INFO - Scan time: 4.1736\n", + "2024-12-19 13:15:52,419 - optimization.inference - INFO - Number of candidates by RT in frame 520: 200\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,430 - optimization.inference - INFO - Scan time: 4.2594\n", + "2024-12-19 13:15:52,430 - optimization.inference - INFO - Number of candidates by RT in frame 525: 207\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,445 - optimization.inference - INFO - Scan time: 4.3449\n", + "2024-12-19 13:15:52,446 - optimization.inference - INFO - Number of candidates by RT in frame 530: 211\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,460 - optimization.inference - INFO - Scan time: 4.4305\n", + "2024-12-19 13:15:52,461 - optimization.inference - INFO - Number of candidates by RT in frame 535: 203\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,473 - optimization.inference - INFO - Scan time: 4.5147\n", + "2024-12-19 13:15:52,474 - optimization.inference - INFO - Number of candidates by RT in frame 540: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,485 - optimization.inference - INFO - Scan time: 4.6001\n", + "2024-12-19 13:15:52,485 - optimization.inference - INFO - Number of candidates by RT in frame 545: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,496 - optimization.inference - INFO - Scan time: 4.6865\n", + "2024-12-19 13:15:52,497 - optimization.inference - INFO - Number of candidates by RT in frame 550: 212\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,507 - optimization.inference - INFO - Scan time: 4.7721\n", + "2024-12-19 13:15:52,507 - optimization.inference - INFO - Number of candidates by RT in frame 555: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,519 - optimization.inference - INFO - Scan time: 4.8581\n", + "2024-12-19 13:15:52,520 - optimization.inference - INFO - Number of candidates by RT in frame 560: 235\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,529 - optimization.inference - INFO - Scan time: 4.9441\n", + "2024-12-19 13:15:52,530 - optimization.inference - INFO - Number of candidates by RT in frame 565: 220\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,540 - optimization.inference - INFO - Scan time: 5.0304\n", + "2024-12-19 13:15:52,541 - optimization.inference - INFO - Number of candidates by RT in frame 570: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,556 - optimization.inference - INFO - Scan time: 5.1167\n", + "2024-12-19 13:15:52,557 - optimization.inference - INFO - Number of candidates by RT in frame 575: 238\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,568 - optimization.inference - INFO - Scan time: 5.2029\n", + "2024-12-19 13:15:52,569 - optimization.inference - INFO - Number of candidates by RT in frame 580: 225\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,581 - optimization.inference - INFO - Scan time: 5.2892\n", + "2024-12-19 13:15:52,582 - optimization.inference - INFO - Number of candidates by RT in frame 585: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,595 - optimization.inference - INFO - Scan time: 5.3751\n", + "2024-12-19 13:15:52,596 - optimization.inference - INFO - Number of candidates by RT in frame 590: 234\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,608 - optimization.inference - INFO - Scan time: 5.4617\n", + "2024-12-19 13:15:52,609 - optimization.inference - INFO - Number of candidates by RT in frame 595: 237\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,624 - optimization.inference - INFO - Scan time: 5.5482\n", + "2024-12-19 13:15:52,625 - optimization.inference - INFO - Number of candidates by RT in frame 600: 231\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,636 - optimization.inference - INFO - Scan time: 5.6344\n", + "2024-12-19 13:15:52,637 - optimization.inference - INFO - Number of candidates by RT in frame 605: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,648 - optimization.inference - INFO - Scan time: 5.7201\n", + "2024-12-19 13:15:52,649 - optimization.inference - INFO - Number of candidates by RT in frame 610: 244\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,660 - optimization.inference - INFO - Scan time: 5.8058\n", + "2024-12-19 13:15:52,661 - optimization.inference - INFO - Number of candidates by RT in frame 615: 239\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,676 - optimization.inference - INFO - Scan time: 5.892\n", + "2024-12-19 13:15:52,677 - optimization.inference - INFO - Number of candidates by RT in frame 620: 252\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,690 - optimization.inference - INFO - Scan time: 5.9788\n", + "2024-12-19 13:15:52,691 - optimization.inference - INFO - Number of candidates by RT in frame 625: 228\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,703 - optimization.inference - INFO - Scan time: 6.064\n", + "2024-12-19 13:15:52,704 - optimization.inference - INFO - Number of candidates by RT in frame 630: 248\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,715 - optimization.inference - INFO - Scan time: 6.1498\n", + "2024-12-19 13:15:52,716 - optimization.inference - INFO - Number of candidates by RT in frame 635: 239\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,728 - optimization.inference - INFO - Scan time: 6.2361\n", + "2024-12-19 13:15:52,729 - optimization.inference - INFO - Number of candidates by RT in frame 640: 251\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,742 - optimization.inference - INFO - Scan time: 6.3228\n", + "2024-12-19 13:15:52,743 - optimization.inference - INFO - Number of candidates by RT in frame 645: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,753 - optimization.inference - INFO - Scan time: 6.4097\n", + "2024-12-19 13:15:52,754 - optimization.inference - INFO - Number of candidates by RT in frame 650: 235\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,767 - optimization.inference - INFO - Scan time: 6.4964\n", + "2024-12-19 13:15:52,768 - optimization.inference - INFO - Number of candidates by RT in frame 655: 236\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,779 - optimization.inference - INFO - Scan time: 6.5831\n", + "2024-12-19 13:15:52,780 - optimization.inference - INFO - Number of candidates by RT in frame 660: 237\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,796 - optimization.inference - INFO - Scan time: 6.6684\n", + "2024-12-19 13:15:52,797 - optimization.inference - INFO - Number of candidates by RT in frame 665: 241\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,808 - optimization.inference - INFO - Scan time: 6.753\n", + "2024-12-19 13:15:52,809 - optimization.inference - INFO - Number of candidates by RT in frame 670: 243\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,820 - optimization.inference - INFO - Scan time: 6.8394\n", + "2024-12-19 13:15:52,821 - optimization.inference - INFO - Number of candidates by RT in frame 675: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,833 - optimization.inference - INFO - Scan time: 6.925\n", + "2024-12-19 13:15:52,833 - optimization.inference - INFO - Number of candidates by RT in frame 680: 251\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,846 - optimization.inference - INFO - Scan time: 7.012\n", + "2024-12-19 13:15:52,847 - optimization.inference - INFO - Number of candidates by RT in frame 685: 230\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,859 - optimization.inference - INFO - Scan time: 7.0979\n", + "2024-12-19 13:15:52,860 - optimization.inference - INFO - Number of candidates by RT in frame 690: 239\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,870 - optimization.inference - INFO - Scan time: 7.1825\n", + "2024-12-19 13:15:52,871 - optimization.inference - INFO - Number of candidates by RT in frame 695: 245\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,885 - optimization.inference - INFO - Scan time: 7.2677\n", + "2024-12-19 13:15:52,886 - optimization.inference - INFO - Number of candidates by RT in frame 700: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,900 - optimization.inference - INFO - Scan time: 7.3535\n", + "2024-12-19 13:15:52,901 - optimization.inference - INFO - Number of candidates by RT in frame 705: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,911 - optimization.inference - INFO - Scan time: 7.4392\n", + "2024-12-19 13:15:52,912 - optimization.inference - INFO - Number of candidates by RT in frame 710: 256\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,924 - optimization.inference - INFO - Scan time: 7.5255\n", + "2024-12-19 13:15:52,925 - optimization.inference - INFO - Number of candidates by RT in frame 715: 259\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,938 - optimization.inference - INFO - Scan time: 7.6114\n", + "2024-12-19 13:15:52,939 - optimization.inference - INFO - Number of candidates by RT in frame 720: 249\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,950 - optimization.inference - INFO - Scan time: 7.6969\n", + "2024-12-19 13:15:52,951 - optimization.inference - INFO - Number of candidates by RT in frame 725: 258\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,964 - optimization.inference - INFO - Scan time: 7.7832\n", + "2024-12-19 13:15:52,965 - optimization.inference - INFO - Number of candidates by RT in frame 730: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:52,985 - optimization.inference - INFO - Scan time: 7.8689\n", + "2024-12-19 13:15:52,986 - optimization.inference - INFO - Number of candidates by RT in frame 735: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,000 - optimization.inference - INFO - Scan time: 7.9548\n", + "2024-12-19 13:15:53,001 - optimization.inference - INFO - Number of candidates by RT in frame 740: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,014 - optimization.inference - INFO - Scan time: 8.0398\n", + "2024-12-19 13:15:53,015 - optimization.inference - INFO - Number of candidates by RT in frame 745: 263\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,029 - optimization.inference - INFO - Scan time: 8.1257\n", + "2024-12-19 13:15:53,030 - optimization.inference - INFO - Number of candidates by RT in frame 750: 254\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,044 - optimization.inference - INFO - Scan time: 8.211\n", + "2024-12-19 13:15:53,045 - optimization.inference - INFO - Number of candidates by RT in frame 755: 258\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,057 - optimization.inference - INFO - Scan time: 8.2971\n", + "2024-12-19 13:15:53,058 - optimization.inference - INFO - Number of candidates by RT in frame 760: 247\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,072 - optimization.inference - INFO - Scan time: 8.3829\n", + "2024-12-19 13:15:53,073 - optimization.inference - INFO - Number of candidates by RT in frame 765: 253\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,088 - optimization.inference - INFO - Scan time: 8.4681\n", + "2024-12-19 13:15:53,089 - optimization.inference - INFO - Number of candidates by RT in frame 770: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,102 - optimization.inference - INFO - Scan time: 8.5533\n", + "2024-12-19 13:15:53,103 - optimization.inference - INFO - Number of candidates by RT in frame 775: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,118 - optimization.inference - INFO - Scan time: 8.6391\n", + "2024-12-19 13:15:53,119 - optimization.inference - INFO - Number of candidates by RT in frame 780: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,135 - optimization.inference - INFO - Scan time: 8.725\n", + "2024-12-19 13:15:53,136 - optimization.inference - INFO - Number of candidates by RT in frame 785: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,150 - optimization.inference - INFO - Scan time: 8.8107\n", + "2024-12-19 13:15:53,151 - optimization.inference - INFO - Number of candidates by RT in frame 790: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,169 - optimization.inference - INFO - Scan time: 8.8967\n", + "2024-12-19 13:15:53,170 - optimization.inference - INFO - Number of candidates by RT in frame 795: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,185 - optimization.inference - INFO - Scan time: 8.9817\n", + "2024-12-19 13:15:53,186 - optimization.inference - INFO - Number of candidates by RT in frame 800: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,200 - optimization.inference - INFO - Scan time: 9.0668\n", + "2024-12-19 13:15:53,201 - optimization.inference - INFO - Number of candidates by RT in frame 805: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,215 - optimization.inference - INFO - Scan time: 9.1523\n", + "2024-12-19 13:15:53,217 - optimization.inference - INFO - Number of candidates by RT in frame 810: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,230 - optimization.inference - INFO - Scan time: 9.238\n", + "2024-12-19 13:15:53,231 - optimization.inference - INFO - Number of candidates by RT in frame 815: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,248 - optimization.inference - INFO - Scan time: 9.3236\n", + "2024-12-19 13:15:53,249 - optimization.inference - INFO - Number of candidates by RT in frame 820: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,266 - optimization.inference - INFO - Scan time: 9.4091\n", + "2024-12-19 13:15:53,267 - optimization.inference - INFO - Number of candidates by RT in frame 825: 294\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,283 - optimization.inference - INFO - Scan time: 9.4961\n", + "2024-12-19 13:15:53,284 - optimization.inference - INFO - Number of candidates by RT in frame 830: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,298 - optimization.inference - INFO - Scan time: 9.5817\n", + "2024-12-19 13:15:53,299 - optimization.inference - INFO - Number of candidates by RT in frame 835: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,312 - optimization.inference - INFO - Scan time: 9.6669\n", + "2024-12-19 13:15:53,313 - optimization.inference - INFO - Number of candidates by RT in frame 840: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,328 - optimization.inference - INFO - Scan time: 9.7534\n", + "2024-12-19 13:15:53,329 - optimization.inference - INFO - Number of candidates by RT in frame 845: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,344 - optimization.inference - INFO - Scan time: 9.8391\n", + "2024-12-19 13:15:53,345 - optimization.inference - INFO - Number of candidates by RT in frame 850: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,361 - optimization.inference - INFO - Scan time: 9.9249\n", + "2024-12-19 13:15:53,362 - optimization.inference - INFO - Number of candidates by RT in frame 855: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,377 - optimization.inference - INFO - Scan time: 10.0099\n", + "2024-12-19 13:15:53,378 - optimization.inference - INFO - Number of candidates by RT in frame 860: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,391 - optimization.inference - INFO - Scan time: 10.0954\n", + "2024-12-19 13:15:53,392 - optimization.inference - INFO - Number of candidates by RT in frame 865: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,405 - optimization.inference - INFO - Scan time: 10.1809\n", + "2024-12-19 13:15:53,406 - optimization.inference - INFO - Number of candidates by RT in frame 870: 257\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,420 - optimization.inference - INFO - Scan time: 10.2663\n", + "2024-12-19 13:15:53,421 - optimization.inference - INFO - Number of candidates by RT in frame 875: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,435 - optimization.inference - INFO - Scan time: 10.3516\n", + "2024-12-19 13:15:53,436 - optimization.inference - INFO - Number of candidates by RT in frame 880: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,449 - optimization.inference - INFO - Scan time: 10.4368\n", + "2024-12-19 13:15:53,450 - optimization.inference - INFO - Number of candidates by RT in frame 885: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,464 - optimization.inference - INFO - Scan time: 10.523\n", + "2024-12-19 13:15:53,465 - optimization.inference - INFO - Number of candidates by RT in frame 890: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,476 - optimization.inference - INFO - Scan time: 10.6087\n", + "2024-12-19 13:15:53,477 - optimization.inference - INFO - Number of candidates by RT in frame 895: 263\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,491 - optimization.inference - INFO - Scan time: 10.6955\n", + "2024-12-19 13:15:53,492 - optimization.inference - INFO - Number of candidates by RT in frame 900: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,507 - optimization.inference - INFO - Scan time: 10.7817\n", + "2024-12-19 13:15:53,508 - optimization.inference - INFO - Number of candidates by RT in frame 905: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,523 - optimization.inference - INFO - Scan time: 10.8671\n", + "2024-12-19 13:15:53,524 - optimization.inference - INFO - Number of candidates by RT in frame 910: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,537 - optimization.inference - INFO - Scan time: 10.9531\n", + "2024-12-19 13:15:53,538 - optimization.inference - INFO - Number of candidates by RT in frame 915: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,550 - optimization.inference - INFO - Scan time: 11.039\n", + "2024-12-19 13:15:53,551 - optimization.inference - INFO - Number of candidates by RT in frame 920: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,567 - optimization.inference - INFO - Scan time: 11.1248\n", + "2024-12-19 13:15:53,568 - optimization.inference - INFO - Number of candidates by RT in frame 925: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,583 - optimization.inference - INFO - Scan time: 11.2103\n", + "2024-12-19 13:15:53,584 - optimization.inference - INFO - Number of candidates by RT in frame 930: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,597 - optimization.inference - INFO - Scan time: 11.297\n", + "2024-12-19 13:15:53,599 - optimization.inference - INFO - Number of candidates by RT in frame 935: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,613 - optimization.inference - INFO - Scan time: 11.3834\n", + "2024-12-19 13:15:53,614 - optimization.inference - INFO - Number of candidates by RT in frame 940: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,626 - optimization.inference - INFO - Scan time: 11.47\n", + "2024-12-19 13:15:53,628 - optimization.inference - INFO - Number of candidates by RT in frame 945: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,646 - optimization.inference - INFO - Scan time: 11.5557\n", + "2024-12-19 13:15:53,647 - optimization.inference - INFO - Number of candidates by RT in frame 950: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,662 - optimization.inference - INFO - Scan time: 11.6409\n", + "2024-12-19 13:15:53,663 - optimization.inference - INFO - Number of candidates by RT in frame 955: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,676 - optimization.inference - INFO - Scan time: 11.7268\n", + "2024-12-19 13:15:53,677 - optimization.inference - INFO - Number of candidates by RT in frame 960: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,691 - optimization.inference - INFO - Scan time: 11.8124\n", + "2024-12-19 13:15:53,692 - optimization.inference - INFO - Number of candidates by RT in frame 965: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,707 - optimization.inference - INFO - Scan time: 11.898\n", + "2024-12-19 13:15:53,708 - optimization.inference - INFO - Number of candidates by RT in frame 970: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,723 - optimization.inference - INFO - Scan time: 11.9839\n", + "2024-12-19 13:15:53,724 - optimization.inference - INFO - Number of candidates by RT in frame 975: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,736 - optimization.inference - INFO - Scan time: 12.0708\n", + "2024-12-19 13:15:53,737 - optimization.inference - INFO - Number of candidates by RT in frame 980: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,752 - optimization.inference - INFO - Scan time: 12.1571\n", + "2024-12-19 13:15:53,753 - optimization.inference - INFO - Number of candidates by RT in frame 985: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,765 - optimization.inference - INFO - Scan time: 12.2427\n", + "2024-12-19 13:15:53,767 - optimization.inference - INFO - Number of candidates by RT in frame 990: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,781 - optimization.inference - INFO - Scan time: 12.3275\n", + "2024-12-19 13:15:53,782 - optimization.inference - INFO - Number of candidates by RT in frame 995: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,797 - optimization.inference - INFO - Scan time: 12.4131\n", + "2024-12-19 13:15:53,798 - optimization.inference - INFO - Number of candidates by RT in frame 1000: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,813 - optimization.inference - INFO - Scan time: 12.4989\n", + "2024-12-19 13:15:53,814 - optimization.inference - INFO - Number of candidates by RT in frame 1005: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,830 - optimization.inference - INFO - Scan time: 12.5845\n", + "2024-12-19 13:15:53,832 - optimization.inference - INFO - Number of candidates by RT in frame 1010: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,851 - optimization.inference - INFO - Scan time: 12.6701\n", + "2024-12-19 13:15:53,852 - optimization.inference - INFO - Number of candidates by RT in frame 1015: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,868 - optimization.inference - INFO - Scan time: 12.7555\n", + "2024-12-19 13:15:53,869 - optimization.inference - INFO - Number of candidates by RT in frame 1020: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,886 - optimization.inference - INFO - Scan time: 12.8419\n", + "2024-12-19 13:15:53,887 - optimization.inference - INFO - Number of candidates by RT in frame 1025: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,908 - optimization.inference - INFO - Scan time: 12.9278\n", + "2024-12-19 13:15:53,909 - optimization.inference - INFO - Number of candidates by RT in frame 1030: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,931 - optimization.inference - INFO - Scan time: 13.0135\n", + "2024-12-19 13:15:53,932 - optimization.inference - INFO - Number of candidates by RT in frame 1035: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,952 - optimization.inference - INFO - Scan time: 13.0991\n", + "2024-12-19 13:15:53,953 - optimization.inference - INFO - Number of candidates by RT in frame 1040: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,980 - optimization.inference - INFO - Scan time: 13.185\n", + "2024-12-19 13:15:53,981 - optimization.inference - INFO - Number of candidates by RT in frame 1045: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:53,996 - optimization.inference - INFO - Scan time: 13.2722\n", + "2024-12-19 13:15:53,997 - optimization.inference - INFO - Number of candidates by RT in frame 1050: 284\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,009 - optimization.inference - INFO - Scan time: 13.3583\n", + "2024-12-19 13:15:54,010 - optimization.inference - INFO - Number of candidates by RT in frame 1055: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,024 - optimization.inference - INFO - Scan time: 13.4457\n", + "2024-12-19 13:15:54,025 - optimization.inference - INFO - Number of candidates by RT in frame 1060: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,040 - optimization.inference - INFO - Scan time: 13.5309\n", + "2024-12-19 13:15:54,041 - optimization.inference - INFO - Number of candidates by RT in frame 1065: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,058 - optimization.inference - INFO - Scan time: 13.6169\n", + "2024-12-19 13:15:54,059 - optimization.inference - INFO - Number of candidates by RT in frame 1070: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,075 - optimization.inference - INFO - Scan time: 13.703\n", + "2024-12-19 13:15:54,076 - optimization.inference - INFO - Number of candidates by RT in frame 1075: 333\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,093 - optimization.inference - INFO - Scan time: 13.7895\n", + "2024-12-19 13:15:54,094 - optimization.inference - INFO - Number of candidates by RT in frame 1080: 324\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,114 - optimization.inference - INFO - Scan time: 13.8751\n", + "2024-12-19 13:15:54,115 - optimization.inference - INFO - Number of candidates by RT in frame 1085: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,133 - optimization.inference - INFO - Scan time: 13.9604\n", + "2024-12-19 13:15:54,134 - optimization.inference - INFO - Number of candidates by RT in frame 1090: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,150 - optimization.inference - INFO - Scan time: 14.0458\n", + "2024-12-19 13:15:54,151 - optimization.inference - INFO - Number of candidates by RT in frame 1095: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,165 - optimization.inference - INFO - Scan time: 14.1323\n", + "2024-12-19 13:15:54,167 - optimization.inference - INFO - Number of candidates by RT in frame 1100: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,180 - optimization.inference - INFO - Scan time: 14.2177\n", + "2024-12-19 13:15:54,181 - optimization.inference - INFO - Number of candidates by RT in frame 1105: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,196 - optimization.inference - INFO - Scan time: 14.3042\n", + "2024-12-19 13:15:54,198 - optimization.inference - INFO - Number of candidates by RT in frame 1110: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,212 - optimization.inference - INFO - Scan time: 14.3901\n", + "2024-12-19 13:15:54,213 - optimization.inference - INFO - Number of candidates by RT in frame 1115: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,227 - optimization.inference - INFO - Scan time: 14.4754\n", + "2024-12-19 13:15:54,228 - optimization.inference - INFO - Number of candidates by RT in frame 1120: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,246 - optimization.inference - INFO - Scan time: 14.5611\n", + "2024-12-19 13:15:54,247 - optimization.inference - INFO - Number of candidates by RT in frame 1125: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,266 - optimization.inference - INFO - Scan time: 14.6464\n", + "2024-12-19 13:15:54,268 - optimization.inference - INFO - Number of candidates by RT in frame 1130: 332\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,284 - optimization.inference - INFO - Scan time: 14.7326\n", + "2024-12-19 13:15:54,285 - optimization.inference - INFO - Number of candidates by RT in frame 1135: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,303 - optimization.inference - INFO - Scan time: 14.8188\n", + "2024-12-19 13:15:54,304 - optimization.inference - INFO - Number of candidates by RT in frame 1140: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,322 - optimization.inference - INFO - Scan time: 14.9033\n", + "2024-12-19 13:15:54,323 - optimization.inference - INFO - Number of candidates by RT in frame 1145: 328\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,343 - optimization.inference - INFO - Scan time: 14.9899\n", + "2024-12-19 13:15:54,344 - optimization.inference - INFO - Number of candidates by RT in frame 1150: 317\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,361 - optimization.inference - INFO - Scan time: 15.0752\n", + "2024-12-19 13:15:54,362 - optimization.inference - INFO - Number of candidates by RT in frame 1155: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,381 - optimization.inference - INFO - Scan time: 15.1617\n", + "2024-12-19 13:15:54,382 - optimization.inference - INFO - Number of candidates by RT in frame 1160: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,396 - optimization.inference - INFO - Scan time: 15.2475\n", + "2024-12-19 13:15:54,397 - optimization.inference - INFO - Number of candidates by RT in frame 1165: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,412 - optimization.inference - INFO - Scan time: 15.3332\n", + "2024-12-19 13:15:54,413 - optimization.inference - INFO - Number of candidates by RT in frame 1170: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,430 - optimization.inference - INFO - Scan time: 15.4191\n", + "2024-12-19 13:15:54,431 - optimization.inference - INFO - Number of candidates by RT in frame 1175: 338\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,447 - optimization.inference - INFO - Scan time: 15.5051\n", + "2024-12-19 13:15:54,448 - optimization.inference - INFO - Number of candidates by RT in frame 1180: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,468 - optimization.inference - INFO - Scan time: 15.5912\n", + "2024-12-19 13:15:54,469 - optimization.inference - INFO - Number of candidates by RT in frame 1185: 340\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,489 - optimization.inference - INFO - Scan time: 15.6767\n", + "2024-12-19 13:15:54,490 - optimization.inference - INFO - Number of candidates by RT in frame 1190: 335\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,510 - optimization.inference - INFO - Scan time: 15.7627\n", + "2024-12-19 13:15:54,511 - optimization.inference - INFO - Number of candidates by RT in frame 1195: 335\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,529 - optimization.inference - INFO - Scan time: 15.8485\n", + "2024-12-19 13:15:54,530 - optimization.inference - INFO - Number of candidates by RT in frame 1200: 324\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,548 - optimization.inference - INFO - Scan time: 15.9336\n", + "2024-12-19 13:15:54,549 - optimization.inference - INFO - Number of candidates by RT in frame 1205: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,566 - optimization.inference - INFO - Scan time: 16.0192\n", + "2024-12-19 13:15:54,567 - optimization.inference - INFO - Number of candidates by RT in frame 1210: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,584 - optimization.inference - INFO - Scan time: 16.1037\n", + "2024-12-19 13:15:54,585 - optimization.inference - INFO - Number of candidates by RT in frame 1215: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,601 - optimization.inference - INFO - Scan time: 16.1908\n", + "2024-12-19 13:15:54,602 - optimization.inference - INFO - Number of candidates by RT in frame 1220: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,618 - optimization.inference - INFO - Scan time: 16.2763\n", + "2024-12-19 13:15:54,619 - optimization.inference - INFO - Number of candidates by RT in frame 1225: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,637 - optimization.inference - INFO - Scan time: 16.3619\n", + "2024-12-19 13:15:54,638 - optimization.inference - INFO - Number of candidates by RT in frame 1230: 318\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,658 - optimization.inference - INFO - Scan time: 16.4478\n", + "2024-12-19 13:15:54,659 - optimization.inference - INFO - Number of candidates by RT in frame 1235: 336\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,677 - optimization.inference - INFO - Scan time: 16.5335\n", + "2024-12-19 13:15:54,679 - optimization.inference - INFO - Number of candidates by RT in frame 1240: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,696 - optimization.inference - INFO - Scan time: 16.619\n", + "2024-12-19 13:15:54,697 - optimization.inference - INFO - Number of candidates by RT in frame 1245: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,714 - optimization.inference - INFO - Scan time: 16.7057\n", + "2024-12-19 13:15:54,715 - optimization.inference - INFO - Number of candidates by RT in frame 1250: 319\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,731 - optimization.inference - INFO - Scan time: 16.7911\n", + "2024-12-19 13:15:54,732 - optimization.inference - INFO - Number of candidates by RT in frame 1255: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,749 - optimization.inference - INFO - Scan time: 16.8763\n", + "2024-12-19 13:15:54,750 - optimization.inference - INFO - Number of candidates by RT in frame 1260: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,769 - optimization.inference - INFO - Scan time: 16.962\n", + "2024-12-19 13:15:54,770 - optimization.inference - INFO - Number of candidates by RT in frame 1265: 341\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,790 - optimization.inference - INFO - Scan time: 17.048\n", + "2024-12-19 13:15:54,791 - optimization.inference - INFO - Number of candidates by RT in frame 1270: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,808 - optimization.inference - INFO - Scan time: 17.1339\n", + "2024-12-19 13:15:54,809 - optimization.inference - INFO - Number of candidates by RT in frame 1275: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,822 - optimization.inference - INFO - Scan time: 17.2203\n", + "2024-12-19 13:15:54,823 - optimization.inference - INFO - Number of candidates by RT in frame 1280: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,839 - optimization.inference - INFO - Scan time: 17.3066\n", + "2024-12-19 13:15:54,840 - optimization.inference - INFO - Number of candidates by RT in frame 1285: 336\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,858 - optimization.inference - INFO - Scan time: 17.3922\n", + "2024-12-19 13:15:54,860 - optimization.inference - INFO - Number of candidates by RT in frame 1290: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,878 - optimization.inference - INFO - Scan time: 17.4789\n", + "2024-12-19 13:15:54,879 - optimization.inference - INFO - Number of candidates by RT in frame 1295: 330\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,898 - optimization.inference - INFO - Scan time: 17.5651\n", + "2024-12-19 13:15:54,899 - optimization.inference - INFO - Number of candidates by RT in frame 1300: 350\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,916 - optimization.inference - INFO - Scan time: 17.6512\n", + "2024-12-19 13:15:54,917 - optimization.inference - INFO - Number of candidates by RT in frame 1305: 319\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,936 - optimization.inference - INFO - Scan time: 17.7368\n", + "2024-12-19 13:15:54,937 - optimization.inference - INFO - Number of candidates by RT in frame 1310: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,954 - optimization.inference - INFO - Scan time: 17.8223\n", + "2024-12-19 13:15:54,955 - optimization.inference - INFO - Number of candidates by RT in frame 1315: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,974 - optimization.inference - INFO - Scan time: 17.9086\n", + "2024-12-19 13:15:54,975 - optimization.inference - INFO - Number of candidates by RT in frame 1320: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:54,994 - optimization.inference - INFO - Scan time: 17.9935\n", + "2024-12-19 13:15:54,995 - optimization.inference - INFO - Number of candidates by RT in frame 1325: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,013 - optimization.inference - INFO - Scan time: 18.0796\n", + "2024-12-19 13:15:55,014 - optimization.inference - INFO - Number of candidates by RT in frame 1330: 314\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,031 - optimization.inference - INFO - Scan time: 18.1659\n", + "2024-12-19 13:15:55,032 - optimization.inference - INFO - Number of candidates by RT in frame 1335: 342\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,058 - optimization.inference - INFO - Scan time: 18.2522\n", + "2024-12-19 13:15:55,059 - optimization.inference - INFO - Number of candidates by RT in frame 1340: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,080 - optimization.inference - INFO - Scan time: 18.3369\n", + "2024-12-19 13:15:55,081 - optimization.inference - INFO - Number of candidates by RT in frame 1345: 344\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,100 - optimization.inference - INFO - Scan time: 18.4226\n", + "2024-12-19 13:15:55,101 - optimization.inference - INFO - Number of candidates by RT in frame 1350: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,112 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", + "2024-12-19 13:15:55,119 - optimization.inference - INFO - Scan time: 18.5088\n", + "2024-12-19 13:15:55,120 - optimization.inference - INFO - Number of candidates by RT in frame 1355: 324\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", + " from pandas.core import (\n", + "2024-12-19 13:15:55,125 - optimization.inference - INFO - Scan time: 0.0051\n", + "2024-12-19 13:15:55,127 - optimization.inference - INFO - Number of candidates by RT in frame 1: 25\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,132 - optimization.inference - INFO - Scan time: 0.0167\n", + "2024-12-19 13:15:55,132 - optimization.inference - INFO - Number of candidates by RT in frame 6: 32\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,138 - optimization.inference - INFO - Scan time: 0.0282\n", + "2024-12-19 13:15:55,139 - optimization.inference - INFO - Scan time: 18.594\n", + "2024-12-19 13:15:55,139 - optimization.inference - INFO - Number of candidates by RT in frame 11: 32\n", + "2024-12-19 13:15:55,140 - optimization.inference - INFO - Number of candidates by RT in frame 1360: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,145 - optimization.inference - INFO - Scan time: 0.0397\n", + "2024-12-19 13:15:55,146 - optimization.inference - INFO - Number of candidates by RT in frame 16: 34\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,151 - optimization.inference - INFO - Scan time: 0.0513\n", + "2024-12-19 13:15:55,152 - optimization.inference - INFO - Number of candidates by RT in frame 21: 37\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,158 - optimization.inference - INFO - Scan time: 0.0628\n", + "2024-12-19 13:15:55,159 - optimization.inference - INFO - Number of candidates by RT in frame 26: 37\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,160 - optimization.inference - INFO - Scan time: 18.6794\n", + "2024-12-19 13:15:55,161 - optimization.inference - INFO - Number of candidates by RT in frame 1365: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,165 - optimization.inference - INFO - Scan time: 0.0743\n", + "2024-12-19 13:15:55,165 - optimization.inference - INFO - Number of candidates by RT in frame 31: 40\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,171 - optimization.inference - INFO - Scan time: 0.0859\n", + "2024-12-19 13:15:55,172 - optimization.inference - INFO - Number of candidates by RT in frame 36: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,179 - optimization.inference - INFO - Scan time: 18.7657\n", + "2024-12-19 13:15:55,180 - optimization.inference - INFO - Number of candidates by RT in frame 1370: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,197 - optimization.inference - INFO - Scan time: 18.8518\n", + "2024-12-19 13:15:55,198 - optimization.inference - INFO - Number of candidates by RT in frame 1375: 284\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,202 - optimization.inference - INFO - Scan time: 0.1403\n", + "2024-12-19 13:15:55,203 - optimization.inference - INFO - Number of candidates by RT in frame 41: 62\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,209 - optimization.inference - INFO - Scan time: 0.2154\n", + "2024-12-19 13:15:55,210 - optimization.inference - INFO - Number of candidates by RT in frame 46: 70\n", + "2024-12-19 13:15:55,211 - optimization.inference - INFO - Scan time: 18.9379\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,212 - optimization.inference - INFO - Number of candidates by RT in frame 1380: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,217 - optimization.inference - INFO - Scan time: 0.2902\n", + "2024-12-19 13:15:55,218 - optimization.inference - INFO - Number of candidates by RT in frame 51: 77\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,224 - optimization.inference - INFO - Scan time: 0.356\n", + "2024-12-19 13:15:55,225 - optimization.inference - INFO - Number of candidates by RT in frame 56: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,227 - optimization.inference - INFO - Scan time: 19.0234\n", + "2024-12-19 13:15:55,228 - optimization.inference - INFO - Number of candidates by RT in frame 1385: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,232 - optimization.inference - INFO - Scan time: 0.4297\n", + "2024-12-19 13:15:55,233 - optimization.inference - INFO - Number of candidates by RT in frame 61: 65\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,240 - optimization.inference - INFO - Scan time: 0.4922\n", + "2024-12-19 13:15:55,241 - optimization.inference - INFO - Number of candidates by RT in frame 66: 65\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,243 - optimization.inference - INFO - Scan time: 19.1091\n", + "2024-12-19 13:15:55,244 - optimization.inference - INFO - Number of candidates by RT in frame 1390: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,248 - optimization.inference - INFO - Scan time: 0.5334\n", + "2024-12-19 13:15:55,249 - optimization.inference - INFO - Number of candidates by RT in frame 71: 65\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,257 - optimization.inference - INFO - Scan time: 0.5595\n", + "2024-12-19 13:15:55,258 - optimization.inference - INFO - Number of candidates by RT in frame 76: 67\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,263 - optimization.inference - INFO - Scan time: 19.1942\n", + "2024-12-19 13:15:55,264 - optimization.inference - INFO - Number of candidates by RT in frame 1395: 339\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,266 - optimization.inference - INFO - Scan time: 0.585\n", + "2024-12-19 13:15:55,267 - optimization.inference - INFO - Number of candidates by RT in frame 81: 67\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,274 - optimization.inference - INFO - Scan time: 0.6088\n", + "2024-12-19 13:15:55,275 - optimization.inference - INFO - Number of candidates by RT in frame 86: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,282 - optimization.inference - INFO - Scan time: 19.2806\n", + "2024-12-19 13:15:55,283 - optimization.inference - INFO - Scan time: 0.6329\n", + "2024-12-19 13:15:55,283 - optimization.inference - INFO - Number of candidates by RT in frame 1400: 303\n", + "2024-12-19 13:15:55,284 - optimization.inference - INFO - Number of candidates by RT in frame 91: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,292 - optimization.inference - INFO - Scan time: 0.6463\n", + "2024-12-19 13:15:55,293 - optimization.inference - INFO - Number of candidates by RT in frame 96: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,299 - optimization.inference - INFO - Scan time: 19.3664\n", + "2024-12-19 13:15:55,300 - optimization.inference - INFO - Number of candidates by RT in frame 1405: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,301 - optimization.inference - INFO - Scan time: 0.6683\n", + "2024-12-19 13:15:55,302 - optimization.inference - INFO - Number of candidates by RT in frame 101: 70\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,310 - optimization.inference - INFO - Scan time: 0.6812\n", + "2024-12-19 13:15:55,311 - optimization.inference - INFO - Number of candidates by RT in frame 106: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,316 - optimization.inference - INFO - Scan time: 19.4527\n", + "2024-12-19 13:15:55,317 - optimization.inference - INFO - Number of candidates by RT in frame 1410: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,320 - optimization.inference - INFO - Scan time: 0.6995\n", + "2024-12-19 13:15:55,321 - optimization.inference - INFO - Number of candidates by RT in frame 111: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,329 - optimization.inference - INFO - Scan time: 0.7116\n", + "2024-12-19 13:15:55,330 - optimization.inference - INFO - Number of candidates by RT in frame 116: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,333 - optimization.inference - INFO - Scan time: 19.5393\n", + "2024-12-19 13:15:55,335 - optimization.inference - INFO - Number of candidates by RT in frame 1415: 283\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,338 - optimization.inference - INFO - Scan time: 0.7343\n", + "2024-12-19 13:15:55,339 - optimization.inference - INFO - Number of candidates by RT in frame 121: 64\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,347 - optimization.inference - INFO - Scan time: 0.7601\n", + "2024-12-19 13:15:55,348 - optimization.inference - INFO - Number of candidates by RT in frame 126: 63\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,350 - optimization.inference - INFO - Scan time: 19.6257\n", + "2024-12-19 13:15:55,351 - optimization.inference - INFO - Number of candidates by RT in frame 1420: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,356 - optimization.inference - INFO - Scan time: 0.7779\n", + "2024-12-19 13:15:55,357 - optimization.inference - INFO - Number of candidates by RT in frame 131: 60\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,367 - optimization.inference - INFO - Scan time: 19.7105\n", + "2024-12-19 13:15:55,368 - optimization.inference - INFO - Number of candidates by RT in frame 1425: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,370 - optimization.inference - INFO - Scan time: 0.7962\n", + "2024-12-19 13:15:55,371 - optimization.inference - INFO - Number of candidates by RT in frame 136: 58\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,379 - optimization.inference - INFO - Scan time: 0.8166\n", + "2024-12-19 13:15:55,380 - optimization.inference - INFO - Number of candidates by RT in frame 141: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,384 - optimization.inference - INFO - Scan time: 19.7959\n", + "2024-12-19 13:15:55,385 - optimization.inference - INFO - Number of candidates by RT in frame 1430: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,388 - optimization.inference - INFO - Scan time: 0.8377\n", + "2024-12-19 13:15:55,389 - optimization.inference - INFO - Number of candidates by RT in frame 146: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,396 - optimization.inference - INFO - Scan time: 0.8536\n", + "2024-12-19 13:15:55,397 - optimization.inference - INFO - Number of candidates by RT in frame 151: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,402 - optimization.inference - INFO - Scan time: 19.8812\n", + "2024-12-19 13:15:55,403 - optimization.inference - INFO - Number of candidates by RT in frame 1435: 314\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,406 - optimization.inference - INFO - Scan time: 0.8689\n", + "2024-12-19 13:15:55,407 - optimization.inference - INFO - Number of candidates by RT in frame 156: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,415 - optimization.inference - INFO - Scan time: 0.8877\n", + "2024-12-19 13:15:55,416 - optimization.inference - INFO - Number of candidates by RT in frame 161: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,422 - optimization.inference - INFO - Scan time: 19.9667\n", + "2024-12-19 13:15:55,423 - optimization.inference - INFO - Number of candidates by RT in frame 1440: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,425 - optimization.inference - INFO - Scan time: 0.9038\n", + "2024-12-19 13:15:55,426 - optimization.inference - INFO - Number of candidates by RT in frame 166: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,434 - optimization.inference - INFO - Scan time: 0.9242\n", + "2024-12-19 13:15:55,435 - optimization.inference - INFO - Number of candidates by RT in frame 171: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,439 - optimization.inference - INFO - Scan time: 20.0521\n", + "2024-12-19 13:15:55,440 - optimization.inference - INFO - Number of candidates by RT in frame 1445: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,443 - optimization.inference - INFO - Scan time: 0.9458\n", + "2024-12-19 13:15:55,444 - optimization.inference - INFO - Number of candidates by RT in frame 176: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,452 - optimization.inference - INFO - Scan time: 0.96\n", + "2024-12-19 13:15:55,453 - optimization.inference - INFO - Number of candidates by RT in frame 181: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,456 - optimization.inference - INFO - Scan time: 20.1384\n", + "2024-12-19 13:15:55,457 - optimization.inference - INFO - Number of candidates by RT in frame 1450: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,461 - optimization.inference - INFO - Scan time: 0.979\n", + "2024-12-19 13:15:55,462 - optimization.inference - INFO - Number of candidates by RT in frame 186: 54\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,474 - optimization.inference - INFO - Scan time: 20.2241\n", + "2024-12-19 13:15:55,475 - optimization.inference - INFO - Number of candidates by RT in frame 1455: 301\n", + "2024-12-19 13:15:55,475 - optimization.inference - INFO - Scan time: 1.003\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,477 - optimization.inference - INFO - Number of candidates by RT in frame 191: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,485 - optimization.inference - INFO - Scan time: 1.0201\n", + "2024-12-19 13:15:55,485 - optimization.inference - INFO - Number of candidates by RT in frame 196: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,493 - optimization.inference - INFO - Scan time: 1.0434\n", + "2024-12-19 13:15:55,494 - optimization.inference - INFO - Number of candidates by RT in frame 201: 49\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,497 - optimization.inference - INFO - Scan time: 20.3095\n", + "2024-12-19 13:15:55,498 - optimization.inference - INFO - Number of candidates by RT in frame 1460: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,501 - optimization.inference - INFO - Scan time: 1.0596\n", + "2024-12-19 13:15:55,502 - optimization.inference - INFO - Number of candidates by RT in frame 206: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,509 - optimization.inference - INFO - Scan time: 1.08\n", + "2024-12-19 13:15:55,510 - optimization.inference - INFO - Number of candidates by RT in frame 211: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,517 - optimization.inference - INFO - Scan time: 1.0949\n", + "2024-12-19 13:15:55,518 - optimization.inference - INFO - Scan time: 20.3947\n", + "2024-12-19 13:15:55,518 - optimization.inference - INFO - Number of candidates by RT in frame 216: 45\n", + "2024-12-19 13:15:55,519 - optimization.inference - INFO - Number of candidates by RT in frame 1465: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,526 - optimization.inference - INFO - Scan time: 1.1183\n", + "2024-12-19 13:15:55,527 - optimization.inference - INFO - Number of candidates by RT in frame 221: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,534 - optimization.inference - INFO - Scan time: 1.1423\n", + "2024-12-19 13:15:55,535 - optimization.inference - INFO - Number of candidates by RT in frame 226: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,538 - optimization.inference - INFO - Scan time: 20.4803\n", + "2024-12-19 13:15:55,539 - optimization.inference - INFO - Number of candidates by RT in frame 1470: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,542 - optimization.inference - INFO - Scan time: 1.1669\n", + "2024-12-19 13:15:55,543 - optimization.inference - INFO - Number of candidates by RT in frame 231: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,551 - optimization.inference - INFO - Scan time: 1.1846\n", + "2024-12-19 13:15:55,551 - optimization.inference - INFO - Number of candidates by RT in frame 236: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,557 - optimization.inference - INFO - Scan time: 20.5662\n", + "2024-12-19 13:15:55,558 - optimization.inference - INFO - Number of candidates by RT in frame 1475: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,559 - optimization.inference - INFO - Scan time: 1.1975\n", + "2024-12-19 13:15:55,560 - optimization.inference - INFO - Number of candidates by RT in frame 241: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,568 - optimization.inference - INFO - Scan time: 1.2142\n", + "2024-12-19 13:15:55,569 - optimization.inference - INFO - Number of candidates by RT in frame 246: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,576 - optimization.inference - INFO - Scan time: 1.2283\n", + "2024-12-19 13:15:55,577 - optimization.inference - INFO - Number of candidates by RT in frame 251: 48\n", + "2024-12-19 13:15:55,578 - optimization.inference - INFO - Scan time: 20.6513\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,579 - optimization.inference - INFO - Number of candidates by RT in frame 1480: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,585 - optimization.inference - INFO - Scan time: 1.2425\n", + "2024-12-19 13:15:55,586 - optimization.inference - INFO - Number of candidates by RT in frame 256: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,594 - optimization.inference - INFO - Scan time: 1.262\n", + "2024-12-19 13:15:55,594 - optimization.inference - INFO - Scan time: 20.7378\n", + "2024-12-19 13:15:55,594 - optimization.inference - INFO - Number of candidates by RT in frame 261: 48\n", + "2024-12-19 13:15:55,595 - optimization.inference - INFO - Number of candidates by RT in frame 1485: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,602 - optimization.inference - INFO - Scan time: 1.2796\n", + "2024-12-19 13:15:55,603 - optimization.inference - INFO - Number of candidates by RT in frame 266: 49\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,611 - optimization.inference - INFO - Scan time: 1.3007\n", + "2024-12-19 13:15:55,611 - optimization.inference - INFO - Scan time: 20.8237\n", + "2024-12-19 13:15:55,612 - optimization.inference - INFO - Number of candidates by RT in frame 271: 51\n", + "2024-12-19 13:15:55,612 - optimization.inference - INFO - Number of candidates by RT in frame 1490: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,619 - optimization.inference - INFO - Scan time: 1.3211\n", + "2024-12-19 13:15:55,620 - optimization.inference - INFO - Number of candidates by RT in frame 276: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,627 - optimization.inference - INFO - Scan time: 20.9094\n", + "2024-12-19 13:15:55,628 - optimization.inference - INFO - Scan time: 1.3373\n", + "2024-12-19 13:15:55,628 - optimization.inference - INFO - Number of candidates by RT in frame 1495: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,629 - optimization.inference - INFO - Number of candidates by RT in frame 281: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,637 - optimization.inference - INFO - Scan time: 1.3548\n", + "2024-12-19 13:15:55,638 - optimization.inference - INFO - Number of candidates by RT in frame 286: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,646 - optimization.inference - INFO - Scan time: 1.3738\n", + "2024-12-19 13:15:55,646 - optimization.inference - INFO - Number of candidates by RT in frame 291: 52\n", + "2024-12-19 13:15:55,647 - optimization.inference - INFO - Scan time: 20.9952\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,648 - optimization.inference - INFO - Number of candidates by RT in frame 1500: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,654 - optimization.inference - INFO - Scan time: 1.3908\n", + "2024-12-19 13:15:55,655 - optimization.inference - INFO - Number of candidates by RT in frame 296: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,663 - optimization.inference - INFO - Scan time: 1.4051\n", + "2024-12-19 13:15:55,664 - optimization.inference - INFO - Number of candidates by RT in frame 301: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,665 - optimization.inference - INFO - Scan time: 21.0809\n", + "2024-12-19 13:15:55,666 - optimization.inference - INFO - Number of candidates by RT in frame 1505: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,672 - optimization.inference - INFO - Scan time: 1.4234\n", + "2024-12-19 13:15:55,673 - optimization.inference - INFO - Number of candidates by RT in frame 306: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,684 - optimization.inference - INFO - Scan time: 21.167\n", + "2024-12-19 13:15:55,686 - optimization.inference - INFO - Number of candidates by RT in frame 1510: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,687 - optimization.inference - INFO - Scan time: 1.4425\n", + "2024-12-19 13:15:55,688 - optimization.inference - INFO - Number of candidates by RT in frame 311: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,696 - optimization.inference - INFO - Scan time: 1.4575\n", + "2024-12-19 13:15:55,696 - optimization.inference - INFO - Number of candidates by RT in frame 316: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,704 - optimization.inference - INFO - Scan time: 21.252\n", + "2024-12-19 13:15:55,705 - optimization.inference - INFO - Scan time: 1.4736\n", + "2024-12-19 13:15:55,705 - optimization.inference - INFO - Number of candidates by RT in frame 1515: 295\n", + "2024-12-19 13:15:55,706 - optimization.inference - INFO - Number of candidates by RT in frame 321: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,713 - optimization.inference - INFO - Scan time: 1.4892\n", + "2024-12-19 13:15:55,714 - optimization.inference - INFO - Number of candidates by RT in frame 326: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,722 - optimization.inference - INFO - Scan time: 1.504\n", + "2024-12-19 13:15:55,723 - optimization.inference - INFO - Number of candidates by RT in frame 331: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,724 - optimization.inference - INFO - Scan time: 21.3386\n", + "2024-12-19 13:15:55,725 - optimization.inference - INFO - Number of candidates by RT in frame 1520: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,731 - optimization.inference - INFO - Scan time: 1.5228\n", + "2024-12-19 13:15:55,732 - optimization.inference - INFO - Number of candidates by RT in frame 336: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,740 - optimization.inference - INFO - Scan time: 1.5454\n", + "2024-12-19 13:15:55,741 - optimization.inference - INFO - Number of candidates by RT in frame 341: 50\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,744 - optimization.inference - INFO - Scan time: 21.424\n", + "2024-12-19 13:15:55,745 - optimization.inference - INFO - Number of candidates by RT in frame 1525: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,749 - optimization.inference - INFO - Scan time: 1.5618\n", + "2024-12-19 13:15:55,750 - optimization.inference - INFO - Number of candidates by RT in frame 346: 54\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,758 - optimization.inference - INFO - Scan time: 1.5851\n", + "2024-12-19 13:15:55,759 - optimization.inference - INFO - Number of candidates by RT in frame 351: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,763 - optimization.inference - INFO - Scan time: 21.5083\n", + "2024-12-19 13:15:55,764 - optimization.inference - INFO - Number of candidates by RT in frame 1530: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,767 - optimization.inference - INFO - Scan time: 1.6161\n", + "2024-12-19 13:15:55,768 - optimization.inference - INFO - Number of candidates by RT in frame 356: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,776 - optimization.inference - INFO - Scan time: 1.6557\n", + "2024-12-19 13:15:55,777 - optimization.inference - INFO - Number of candidates by RT in frame 361: 74\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,779 - optimization.inference - INFO - Scan time: 21.5945\n", + "2024-12-19 13:15:55,780 - optimization.inference - INFO - Number of candidates by RT in frame 1535: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,783 - optimization.inference - INFO - Scan time: 1.6823\n", + "2024-12-19 13:15:55,784 - optimization.inference - INFO - Number of candidates by RT in frame 366: 80\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,792 - optimization.inference - INFO - Scan time: 1.7157\n", + "2024-12-19 13:15:55,793 - optimization.inference - INFO - Number of candidates by RT in frame 371: 91\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,798 - optimization.inference - INFO - Scan time: 21.6803\n", + "2024-12-19 13:15:55,799 - optimization.inference - INFO - Number of candidates by RT in frame 1540: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,802 - optimization.inference - INFO - Scan time: 1.7599\n", + "2024-12-19 13:15:55,803 - optimization.inference - INFO - Number of candidates by RT in frame 376: 111\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,814 - optimization.inference - INFO - Scan time: 1.8422\n", + "2024-12-19 13:15:55,815 - optimization.inference - INFO - Number of candidates by RT in frame 381: 125\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,816 - optimization.inference - INFO - Scan time: 21.7654\n", + "2024-12-19 13:15:55,817 - optimization.inference - INFO - Number of candidates by RT in frame 1545: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,825 - optimization.inference - INFO - Scan time: 1.9279\n", + "2024-12-19 13:15:55,827 - optimization.inference - INFO - Number of candidates by RT in frame 386: 124\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,835 - optimization.inference - INFO - Scan time: 1.9991\n", + "2024-12-19 13:15:55,836 - optimization.inference - INFO - Scan time: 21.8516\n", + "2024-12-19 13:15:55,836 - optimization.inference - INFO - Number of candidates by RT in frame 391: 111\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,837 - optimization.inference - INFO - Number of candidates by RT in frame 1550: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,844 - optimization.inference - INFO - Scan time: 2.0689\n", + "2024-12-19 13:15:55,845 - optimization.inference - INFO - Number of candidates by RT in frame 396: 103\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,854 - optimization.inference - INFO - Scan time: 2.1444\n", + "2024-12-19 13:15:55,855 - optimization.inference - INFO - Number of candidates by RT in frame 401: 111\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,859 - optimization.inference - INFO - Scan time: 21.9372\n", + "2024-12-19 13:15:55,860 - optimization.inference - INFO - Number of candidates by RT in frame 1555: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,863 - optimization.inference - INFO - Scan time: 2.2246\n", + "2024-12-19 13:15:55,864 - optimization.inference - INFO - Number of candidates by RT in frame 406: 127\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,872 - optimization.inference - INFO - Scan time: 2.3041\n", + "2024-12-19 13:15:55,873 - optimization.inference - INFO - Number of candidates by RT in frame 411: 161\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,881 - optimization.inference - INFO - Scan time: 22.023\n", + "2024-12-19 13:15:55,882 - optimization.inference - INFO - Number of candidates by RT in frame 1560: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,885 - optimization.inference - INFO - Scan time: 2.3889\n", + "2024-12-19 13:15:55,886 - optimization.inference - INFO - Number of candidates by RT in frame 416: 183\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,899 - optimization.inference - INFO - Scan time: 2.4746\n", + "2024-12-19 13:15:55,900 - optimization.inference - INFO - Number of candidates by RT in frame 421: 189\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,910 - optimization.inference - INFO - Scan time: 22.1091\n", + "2024-12-19 13:15:55,911 - optimization.inference - INFO - Number of candidates by RT in frame 1565: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,913 - optimization.inference - INFO - Scan time: 2.5613\n", + "2024-12-19 13:15:55,914 - optimization.inference - INFO - Number of candidates by RT in frame 426: 189\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,928 - optimization.inference - INFO - Scan time: 2.6457\n", + "2024-12-19 13:15:55,930 - optimization.inference - INFO - Number of candidates by RT in frame 431: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,932 - optimization.inference - INFO - Scan time: 22.1945\n", + "2024-12-19 13:15:55,933 - optimization.inference - INFO - Number of candidates by RT in frame 1570: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,944 - optimization.inference - INFO - Scan time: 2.7311\n", + "2024-12-19 13:15:55,945 - optimization.inference - INFO - Number of candidates by RT in frame 436: 228\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,951 - optimization.inference - INFO - Scan time: 22.2797\n", + "2024-12-19 13:15:55,953 - optimization.inference - INFO - Number of candidates by RT in frame 1575: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,962 - optimization.inference - INFO - Scan time: 2.8172\n", + "2024-12-19 13:15:55,963 - optimization.inference - INFO - Number of candidates by RT in frame 441: 233\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,974 - optimization.inference - INFO - Scan time: 22.3654\n", + "2024-12-19 13:15:55,975 - optimization.inference - INFO - Number of candidates by RT in frame 1580: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,978 - optimization.inference - INFO - Scan time: 2.903\n", + "2024-12-19 13:15:55,979 - optimization.inference - INFO - Number of candidates by RT in frame 446: 228\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:55,992 - optimization.inference - INFO - Scan time: 2.9888\n", + "2024-12-19 13:15:55,993 - optimization.inference - INFO - Number of candidates by RT in frame 451: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,000 - optimization.inference - INFO - Scan time: 22.4511\n", + "2024-12-19 13:15:56,001 - optimization.inference - INFO - Number of candidates by RT in frame 1585: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,005 - optimization.inference - INFO - Scan time: 3.0749\n", + "2024-12-19 13:15:56,006 - optimization.inference - INFO - Number of candidates by RT in frame 456: 232\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,020 - optimization.inference - INFO - Scan time: 3.1608\n", + "2024-12-19 13:15:56,021 - optimization.inference - INFO - Number of candidates by RT in frame 461: 224\n", + "2024-12-19 13:15:56,021 - optimization.inference - INFO - Scan time: 22.5376\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,022 - optimization.inference - INFO - Number of candidates by RT in frame 1590: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,036 - optimization.inference - INFO - Scan time: 3.2472\n", + "2024-12-19 13:15:56,037 - optimization.inference - INFO - Number of candidates by RT in frame 466: 227\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,039 - optimization.inference - INFO - Scan time: 22.6223\n", + "2024-12-19 13:15:56,040 - optimization.inference - INFO - Number of candidates by RT in frame 1595: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,049 - optimization.inference - INFO - Scan time: 3.3334\n", + "2024-12-19 13:15:56,050 - optimization.inference - INFO - Number of candidates by RT in frame 471: 222\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,056 - optimization.inference - INFO - Scan time: 22.7077\n", + "2024-12-19 13:15:56,057 - optimization.inference - INFO - Number of candidates by RT in frame 1600: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,062 - optimization.inference - INFO - Scan time: 3.4194\n", + "2024-12-19 13:15:56,063 - optimization.inference - INFO - Number of candidates by RT in frame 476: 214\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,073 - optimization.inference - INFO - Scan time: 22.7934\n", + "2024-12-19 13:15:56,074 - optimization.inference - INFO - Number of candidates by RT in frame 1605: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,075 - optimization.inference - INFO - Scan time: 3.5051\n", + "2024-12-19 13:15:56,076 - optimization.inference - INFO - Number of candidates by RT in frame 481: 223\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,087 - optimization.inference - INFO - Scan time: 3.5916\n", + "2024-12-19 13:15:56,088 - optimization.inference - INFO - Number of candidates by RT in frame 486: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,090 - optimization.inference - INFO - Scan time: 22.8798\n", + "2024-12-19 13:15:56,092 - optimization.inference - INFO - Number of candidates by RT in frame 1610: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,100 - optimization.inference - INFO - Scan time: 3.6766\n", + "2024-12-19 13:15:56,101 - optimization.inference - INFO - Number of candidates by RT in frame 491: 210\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,109 - optimization.inference - INFO - Scan time: 22.9664\n", + "2024-12-19 13:15:56,110 - optimization.inference - INFO - Number of candidates by RT in frame 1615: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,114 - optimization.inference - INFO - Scan time: 3.7626\n", + "2024-12-19 13:15:56,115 - optimization.inference - INFO - Number of candidates by RT in frame 496: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,126 - optimization.inference - INFO - Scan time: 23.0521\n", + "2024-12-19 13:15:56,127 - optimization.inference - INFO - Number of candidates by RT in frame 1620: 282\n", + "2024-12-19 13:15:56,128 - optimization.inference - INFO - Scan time: 3.8483\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,129 - optimization.inference - INFO - Number of candidates by RT in frame 501: 205\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,142 - optimization.inference - INFO - Scan time: 3.9331\n", + "2024-12-19 13:15:56,143 - optimization.inference - INFO - Number of candidates by RT in frame 506: 192\n", + "2024-12-19 13:15:56,144 - optimization.inference - INFO - Scan time: 23.1376\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,145 - optimization.inference - INFO - Number of candidates by RT in frame 1625: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,155 - optimization.inference - INFO - Scan time: 4.0191\n", + "2024-12-19 13:15:56,156 - optimization.inference - INFO - Number of candidates by RT in frame 511: 185\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,161 - optimization.inference - INFO - Scan time: 23.2235\n", + "2024-12-19 13:15:56,162 - optimization.inference - INFO - Number of candidates by RT in frame 1630: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,168 - optimization.inference - INFO - Scan time: 4.1054\n", + "2024-12-19 13:15:56,169 - optimization.inference - INFO - Number of candidates by RT in frame 516: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,180 - optimization.inference - INFO - Scan time: 4.191\n", + "2024-12-19 13:15:56,180 - optimization.inference - INFO - Scan time: 23.3091\n", + "2024-12-19 13:15:56,181 - optimization.inference - INFO - Number of candidates by RT in frame 1635: 295\n", + "2024-12-19 13:15:56,181 - optimization.inference - INFO - Number of candidates by RT in frame 521: 200\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,194 - optimization.inference - INFO - Scan time: 4.2767\n", + "2024-12-19 13:15:56,196 - optimization.inference - INFO - Number of candidates by RT in frame 526: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,201 - optimization.inference - INFO - Scan time: 23.3951\n", + "2024-12-19 13:15:56,202 - optimization.inference - INFO - Number of candidates by RT in frame 1640: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,211 - optimization.inference - INFO - Scan time: 4.3623\n", + "2024-12-19 13:15:56,212 - optimization.inference - INFO - Number of candidates by RT in frame 531: 207\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,221 - optimization.inference - INFO - Scan time: 23.48\n", + "2024-12-19 13:15:56,222 - optimization.inference - INFO - Number of candidates by RT in frame 1645: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,227 - optimization.inference - INFO - Scan time: 4.4473\n", + "2024-12-19 13:15:56,229 - optimization.inference - INFO - Number of candidates by RT in frame 536: 193\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,240 - optimization.inference - INFO - Scan time: 23.565\n", + "2024-12-19 13:15:56,241 - optimization.inference - INFO - Scan time: 4.5318\n", + "2024-12-19 13:15:56,241 - optimization.inference - INFO - Number of candidates by RT in frame 1650: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,242 - optimization.inference - INFO - Number of candidates by RT in frame 541: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,254 - optimization.inference - INFO - Scan time: 4.6173\n", + "2024-12-19 13:15:56,255 - optimization.inference - INFO - Number of candidates by RT in frame 546: 203\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,257 - optimization.inference - INFO - Scan time: 23.6509\n", + "2024-12-19 13:15:56,258 - optimization.inference - INFO - Number of candidates by RT in frame 1655: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,267 - optimization.inference - INFO - Scan time: 4.7036\n", + "2024-12-19 13:15:56,269 - optimization.inference - INFO - Number of candidates by RT in frame 551: 212\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,276 - optimization.inference - INFO - Scan time: 23.7367\n", + "2024-12-19 13:15:56,277 - optimization.inference - INFO - Number of candidates by RT in frame 1660: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,280 - optimization.inference - INFO - Scan time: 4.7896\n", + "2024-12-19 13:15:56,281 - optimization.inference - INFO - Number of candidates by RT in frame 556: 213\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,293 - optimization.inference - INFO - Scan time: 23.8227\n", + "2024-12-19 13:15:56,294 - optimization.inference - INFO - Number of candidates by RT in frame 1665: 248\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,295 - optimization.inference - INFO - Scan time: 4.8754\n", + "2024-12-19 13:15:56,296 - optimization.inference - INFO - Number of candidates by RT in frame 561: 237\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,307 - optimization.inference - INFO - Scan time: 4.9611\n", + "2024-12-19 13:15:56,309 - optimization.inference - INFO - Number of candidates by RT in frame 566: 216\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,311 - optimization.inference - INFO - Scan time: 23.9085\n", + "2024-12-19 13:15:56,312 - optimization.inference - INFO - Number of candidates by RT in frame 1670: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,322 - optimization.inference - INFO - Scan time: 5.0477\n", + "2024-12-19 13:15:56,324 - optimization.inference - INFO - Number of candidates by RT in frame 571: 240\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,327 - optimization.inference - INFO - Scan time: 23.9933\n", + "2024-12-19 13:15:56,328 - optimization.inference - INFO - Number of candidates by RT in frame 1675: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,339 - optimization.inference - INFO - Scan time: 5.1342\n", + "2024-12-19 13:15:56,340 - optimization.inference - INFO - Number of candidates by RT in frame 576: 245\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,342 - optimization.inference - INFO - Scan time: 24.0797\n", + "2024-12-19 13:15:56,343 - optimization.inference - INFO - Number of candidates by RT in frame 1680: 233\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,353 - optimization.inference - INFO - Scan time: 5.2204\n", + "2024-12-19 13:15:56,354 - optimization.inference - INFO - Number of candidates by RT in frame 581: 223\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,360 - optimization.inference - INFO - Scan time: 24.1649\n", + "2024-12-19 13:15:56,361 - optimization.inference - INFO - Number of candidates by RT in frame 1685: 255\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,368 - optimization.inference - INFO - Scan time: 5.3065\n", + "2024-12-19 13:15:56,369 - optimization.inference - INFO - Number of candidates by RT in frame 586: 232\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,378 - optimization.inference - INFO - Scan time: 24.2509\n", + "2024-12-19 13:15:56,379 - optimization.inference - INFO - Number of candidates by RT in frame 1690: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,383 - optimization.inference - INFO - Scan time: 5.3925\n", + "2024-12-19 13:15:56,384 - optimization.inference - INFO - Number of candidates by RT in frame 591: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,399 - optimization.inference - INFO - Scan time: 24.3366\n", + "2024-12-19 13:15:56,399 - optimization.inference - INFO - Scan time: 5.4787\n", + "2024-12-19 13:15:56,400 - optimization.inference - INFO - Number of candidates by RT in frame 1695: 263\n", + "2024-12-19 13:15:56,400 - optimization.inference - INFO - Number of candidates by RT in frame 596: 232\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,416 - optimization.inference - INFO - Scan time: 5.5652\n", + "2024-12-19 13:15:56,418 - optimization.inference - INFO - Number of candidates by RT in frame 601: 232\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,419 - optimization.inference - INFO - Scan time: 24.422\n", + "2024-12-19 13:15:56,421 - optimization.inference - INFO - Number of candidates by RT in frame 1700: 247\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,433 - optimization.inference - INFO - Scan time: 5.6513\n", + "2024-12-19 13:15:56,434 - optimization.inference - INFO - Number of candidates by RT in frame 606: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,437 - optimization.inference - INFO - Scan time: 24.5085\n", + "2024-12-19 13:15:56,438 - optimization.inference - INFO - Number of candidates by RT in frame 1705: 259\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,448 - optimization.inference - INFO - Scan time: 5.7371\n", + "2024-12-19 13:15:56,449 - optimization.inference - INFO - Number of candidates by RT in frame 611: 240\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,454 - optimization.inference - INFO - Scan time: 24.5948\n", + "2024-12-19 13:15:56,455 - optimization.inference - INFO - Number of candidates by RT in frame 1710: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,464 - optimization.inference - INFO - Scan time: 5.8232\n", + "2024-12-19 13:15:56,465 - optimization.inference - INFO - Number of candidates by RT in frame 616: 237\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,474 - optimization.inference - INFO - Scan time: 24.6809\n", + "2024-12-19 13:15:56,475 - optimization.inference - INFO - Number of candidates by RT in frame 1715: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,481 - optimization.inference - INFO - Scan time: 5.9095\n", + "2024-12-19 13:15:56,482 - optimization.inference - INFO - Number of candidates by RT in frame 621: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,492 - optimization.inference - INFO - Scan time: 24.7666\n", + "2024-12-19 13:15:56,494 - optimization.inference - INFO - Number of candidates by RT in frame 1720: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,498 - optimization.inference - INFO - Scan time: 5.9959\n", + "2024-12-19 13:15:56,499 - optimization.inference - INFO - Number of candidates by RT in frame 626: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,511 - optimization.inference - INFO - Scan time: 24.8514\n", + "2024-12-19 13:15:56,512 - optimization.inference - INFO - Number of candidates by RT in frame 1725: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,517 - optimization.inference - INFO - Scan time: 6.081\n", + "2024-12-19 13:15:56,518 - optimization.inference - INFO - Number of candidates by RT in frame 631: 247\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,530 - optimization.inference - INFO - Scan time: 6.167\n", + "2024-12-19 13:15:56,531 - optimization.inference - INFO - Scan time: 24.9366\n", + "2024-12-19 13:15:56,531 - optimization.inference - INFO - Number of candidates by RT in frame 636: 231\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,532 - optimization.inference - INFO - Number of candidates by RT in frame 1730: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,546 - optimization.inference - INFO - Scan time: 6.2535\n", + "2024-12-19 13:15:56,547 - optimization.inference - INFO - Number of candidates by RT in frame 641: 254\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,548 - optimization.inference - INFO - Scan time: 25.0215\n", + "2024-12-19 13:15:56,549 - optimization.inference - INFO - Number of candidates by RT in frame 1735: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,561 - optimization.inference - INFO - Scan time: 6.3403\n", + "2024-12-19 13:15:56,562 - optimization.inference - INFO - Number of candidates by RT in frame 646: 255\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,563 - optimization.inference - INFO - Scan time: 25.1072\n", + "2024-12-19 13:15:56,565 - optimization.inference - INFO - Number of candidates by RT in frame 1740: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,576 - optimization.inference - INFO - Scan time: 6.4271\n", + "2024-12-19 13:15:56,577 - optimization.inference - INFO - Number of candidates by RT in frame 651: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,583 - optimization.inference - INFO - Scan time: 25.1926\n", + "2024-12-19 13:15:56,584 - optimization.inference - INFO - Number of candidates by RT in frame 1745: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,593 - optimization.inference - INFO - Scan time: 6.5135\n", + "2024-12-19 13:15:56,594 - optimization.inference - INFO - Number of candidates by RT in frame 656: 240\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,603 - optimization.inference - INFO - Scan time: 25.2793\n", + "2024-12-19 13:15:56,604 - optimization.inference - INFO - Number of candidates by RT in frame 1750: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,607 - optimization.inference - INFO - Scan time: 6.6\n", + "2024-12-19 13:15:56,608 - optimization.inference - INFO - Number of candidates by RT in frame 661: 234\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,621 - optimization.inference - INFO - Scan time: 6.6852\n", + "2024-12-19 13:15:56,622 - optimization.inference - INFO - Number of candidates by RT in frame 666: 242\n", + "2024-12-19 13:15:56,622 - optimization.inference - INFO - Scan time: 25.3655\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,623 - optimization.inference - INFO - Number of candidates by RT in frame 1755: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,634 - optimization.inference - INFO - Scan time: 6.7703\n", + "2024-12-19 13:15:56,635 - optimization.inference - INFO - Number of candidates by RT in frame 671: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,643 - optimization.inference - INFO - Scan time: 25.4515\n", + "2024-12-19 13:15:56,644 - optimization.inference - INFO - Number of candidates by RT in frame 1760: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,649 - optimization.inference - INFO - Scan time: 6.8568\n", + "2024-12-19 13:15:56,650 - optimization.inference - INFO - Number of candidates by RT in frame 676: 249\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,662 - optimization.inference - INFO - Scan time: 25.537\n", + "2024-12-19 13:15:56,663 - optimization.inference - INFO - Number of candidates by RT in frame 1765: 271\n", + "2024-12-19 13:15:56,663 - optimization.inference - INFO - Scan time: 6.9424\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,664 - optimization.inference - INFO - Number of candidates by RT in frame 681: 239\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,676 - optimization.inference - INFO - Scan time: 7.0295\n", + "2024-12-19 13:15:56,677 - optimization.inference - INFO - Number of candidates by RT in frame 686: 232\n", + "2024-12-19 13:15:56,678 - optimization.inference - INFO - Scan time: 25.6227\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,679 - optimization.inference - INFO - Number of candidates by RT in frame 1770: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,692 - optimization.inference - INFO - Scan time: 7.1151\n", + "2024-12-19 13:15:56,693 - optimization.inference - INFO - Number of candidates by RT in frame 691: 239\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,703 - optimization.inference - INFO - Scan time: 25.7084\n", + "2024-12-19 13:15:56,704 - optimization.inference - INFO - Number of candidates by RT in frame 1775: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,705 - optimization.inference - INFO - Scan time: 7.1995\n", + "2024-12-19 13:15:56,706 - optimization.inference - INFO - Number of candidates by RT in frame 696: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,722 - optimization.inference - INFO - Scan time: 7.2848\n", + "2024-12-19 13:15:56,723 - optimization.inference - INFO - Number of candidates by RT in frame 701: 264\n", + "2024-12-19 13:15:56,723 - optimization.inference - INFO - Scan time: 25.7952\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,724 - optimization.inference - INFO - Number of candidates by RT in frame 1780: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,742 - optimization.inference - INFO - Scan time: 25.8808\n", + "2024-12-19 13:15:56,742 - optimization.inference - INFO - Scan time: 7.3705\n", + "2024-12-19 13:15:56,743 - optimization.inference - INFO - Number of candidates by RT in frame 1785: 275\n", + "2024-12-19 13:15:56,744 - optimization.inference - INFO - Number of candidates by RT in frame 706: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,758 - optimization.inference - INFO - Scan time: 7.4566\n", + "2024-12-19 13:15:56,759 - optimization.inference - INFO - Scan time: 25.9666\n", + "2024-12-19 13:15:56,759 - optimization.inference - INFO - Number of candidates by RT in frame 711: 253\n", + "2024-12-19 13:15:56,760 - optimization.inference - INFO - Number of candidates by RT in frame 1790: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,775 - optimization.inference - INFO - Scan time: 7.5429\n", + "2024-12-19 13:15:56,776 - optimization.inference - INFO - Scan time: 26.0529\n", + "2024-12-19 13:15:56,777 - optimization.inference - INFO - Number of candidates by RT in frame 716: 253\n", + "2024-12-19 13:15:56,777 - optimization.inference - INFO - Number of candidates by RT in frame 1795: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,791 - optimization.inference - INFO - Scan time: 7.6284\n", + "2024-12-19 13:15:56,792 - optimization.inference - INFO - Number of candidates by RT in frame 721: 249\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,796 - optimization.inference - INFO - Scan time: 26.1392\n", + "2024-12-19 13:15:56,797 - optimization.inference - INFO - Number of candidates by RT in frame 1800: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,808 - optimization.inference - INFO - Scan time: 7.7143\n", + "2024-12-19 13:15:56,809 - optimization.inference - INFO - Number of candidates by RT in frame 726: 259\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,815 - optimization.inference - INFO - Scan time: 26.2256\n", + "2024-12-19 13:15:56,817 - optimization.inference - INFO - Number of candidates by RT in frame 1805: 294\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,825 - optimization.inference - INFO - Scan time: 7.8007\n", + "2024-12-19 13:15:56,827 - optimization.inference - INFO - Number of candidates by RT in frame 731: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,837 - optimization.inference - INFO - Scan time: 26.3116\n", + "2024-12-19 13:15:56,838 - optimization.inference - INFO - Number of candidates by RT in frame 1810: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,845 - optimization.inference - INFO - Scan time: 7.886\n", + "2024-12-19 13:15:56,846 - optimization.inference - INFO - Number of candidates by RT in frame 736: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,859 - optimization.inference - INFO - Scan time: 26.3977\n", + "2024-12-19 13:15:56,860 - optimization.inference - INFO - Number of candidates by RT in frame 1815: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,865 - optimization.inference - INFO - Scan time: 7.9717\n", + "2024-12-19 13:15:56,866 - optimization.inference - INFO - Number of candidates by RT in frame 741: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,881 - optimization.inference - INFO - Scan time: 26.4831\n", + "2024-12-19 13:15:56,882 - optimization.inference - INFO - Number of candidates by RT in frame 1820: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,884 - optimization.inference - INFO - Scan time: 8.0573\n", + "2024-12-19 13:15:56,885 - optimization.inference - INFO - Number of candidates by RT in frame 746: 259\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,902 - optimization.inference - INFO - Scan time: 26.5684\n", + "2024-12-19 13:15:56,903 - optimization.inference - INFO - Scan time: 8.1424\n", + "2024-12-19 13:15:56,903 - optimization.inference - INFO - Number of candidates by RT in frame 1825: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,905 - optimization.inference - INFO - Number of candidates by RT in frame 751: 256\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,924 - optimization.inference - INFO - Scan time: 26.6543\n", + "2024-12-19 13:15:56,925 - optimization.inference - INFO - Scan time: 8.2284\n", + "2024-12-19 13:15:56,925 - optimization.inference - INFO - Number of candidates by RT in frame 1830: 266\n", + "2024-12-19 13:15:56,926 - optimization.inference - INFO - Number of candidates by RT in frame 756: 259\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,941 - optimization.inference - INFO - Scan time: 8.3141\n", + "2024-12-19 13:15:56,942 - optimization.inference - INFO - Number of candidates by RT in frame 761: 241\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,944 - optimization.inference - INFO - Scan time: 26.741\n", + "2024-12-19 13:15:56,945 - optimization.inference - INFO - Number of candidates by RT in frame 1835: 263\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,960 - optimization.inference - INFO - Scan time: 8.3999\n", + "2024-12-19 13:15:56,962 - optimization.inference - INFO - Number of candidates by RT in frame 766: 261\n", + "2024-12-19 13:15:56,962 - optimization.inference - INFO - Scan time: 26.8264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,963 - optimization.inference - INFO - Number of candidates by RT in frame 1840: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,978 - optimization.inference - INFO - Scan time: 8.4853\n", + "2024-12-19 13:15:56,979 - optimization.inference - INFO - Number of candidates by RT in frame 771: 273\n", + "2024-12-19 13:15:56,980 - optimization.inference - INFO - Scan time: 26.912\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,981 - optimization.inference - INFO - Number of candidates by RT in frame 1845: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,997 - optimization.inference - INFO - Scan time: 8.5704\n", + "2024-12-19 13:15:56,998 - optimization.inference - INFO - Scan time: 26.998\n", + "2024-12-19 13:15:56,998 - optimization.inference - INFO - Number of candidates by RT in frame 776: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:56,999 - optimization.inference - INFO - Number of candidates by RT in frame 1850: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,017 - optimization.inference - INFO - Scan time: 27.0839\n", + "2024-12-19 13:15:57,018 - optimization.inference - INFO - Number of candidates by RT in frame 1855: 290\n", + "2024-12-19 13:15:57,018 - optimization.inference - INFO - Scan time: 8.6566\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,019 - optimization.inference - INFO - Number of candidates by RT in frame 781: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,040 - optimization.inference - INFO - Scan time: 27.1693\n", + "2024-12-19 13:15:57,041 - optimization.inference - INFO - Number of candidates by RT in frame 1860: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,042 - optimization.inference - INFO - Scan time: 8.7421\n", + "2024-12-19 13:15:57,044 - optimization.inference - INFO - Number of candidates by RT in frame 786: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,060 - optimization.inference - INFO - Scan time: 27.2547\n", + "2024-12-19 13:15:57,061 - optimization.inference - INFO - Number of candidates by RT in frame 1865: 267\n", + "2024-12-19 13:15:57,062 - optimization.inference - INFO - Scan time: 8.8276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,063 - optimization.inference - INFO - Number of candidates by RT in frame 791: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,080 - optimization.inference - INFO - Scan time: 27.3404\n", + "2024-12-19 13:15:57,081 - optimization.inference - INFO - Number of candidates by RT in frame 1870: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,083 - optimization.inference - INFO - Scan time: 8.9136\n", + "2024-12-19 13:15:57,084 - optimization.inference - INFO - Number of candidates by RT in frame 796: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,100 - optimization.inference - INFO - Scan time: 27.4271\n", + "2024-12-19 13:15:57,100 - optimization.inference - INFO - Scan time: 8.9985\n", + "2024-12-19 13:15:57,101 - optimization.inference - INFO - Number of candidates by RT in frame 1875: 258\n", + "2024-12-19 13:15:57,101 - optimization.inference - INFO - Number of candidates by RT in frame 801: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,116 - optimization.inference - INFO - Scan time: 9.084\n", + "2024-12-19 13:15:57,116 - optimization.inference - INFO - Scan time: 27.5133\n", + "2024-12-19 13:15:57,117 - optimization.inference - INFO - Number of candidates by RT in frame 806: 281\n", + "2024-12-19 13:15:57,118 - optimization.inference - INFO - Number of candidates by RT in frame 1880: 253\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,133 - optimization.inference - INFO - Scan time: 9.1696\n", + "2024-12-19 13:15:57,134 - optimization.inference - INFO - Number of candidates by RT in frame 811: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,136 - optimization.inference - INFO - Scan time: 27.5994\n", + "2024-12-19 13:15:57,137 - optimization.inference - INFO - Number of candidates by RT in frame 1885: 253\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,147 - optimization.inference - INFO - Scan time: 9.2551\n", + "2024-12-19 13:15:57,148 - optimization.inference - INFO - Number of candidates by RT in frame 816: 283\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,156 - optimization.inference - INFO - Scan time: 27.6856\n", + "2024-12-19 13:15:57,157 - optimization.inference - INFO - Number of candidates by RT in frame 1890: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,166 - optimization.inference - INFO - Scan time: 9.3404\n", + "2024-12-19 13:15:57,167 - optimization.inference - INFO - Number of candidates by RT in frame 821: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,175 - optimization.inference - INFO - Scan time: 27.7723\n", + "2024-12-19 13:15:57,176 - optimization.inference - INFO - Number of candidates by RT in frame 1895: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,185 - optimization.inference - INFO - Scan time: 9.4269\n", + "2024-12-19 13:15:57,186 - optimization.inference - INFO - Number of candidates by RT in frame 826: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,196 - optimization.inference - INFO - Scan time: 27.8579\n", + "2024-12-19 13:15:57,197 - optimization.inference - INFO - Number of candidates by RT in frame 1900: 258\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,203 - optimization.inference - INFO - Scan time: 9.5129\n", + "2024-12-19 13:15:57,204 - optimization.inference - INFO - Number of candidates by RT in frame 831: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,218 - optimization.inference - INFO - Scan time: 27.9435\n", + "2024-12-19 13:15:57,219 - optimization.inference - INFO - Number of candidates by RT in frame 1905: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,220 - optimization.inference - INFO - Scan time: 9.5986\n", + "2024-12-19 13:15:57,221 - optimization.inference - INFO - Number of candidates by RT in frame 836: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,237 - optimization.inference - INFO - Scan time: 9.6842\n", + "2024-12-19 13:15:57,237 - optimization.inference - INFO - Scan time: 28.0288\n", + "2024-12-19 13:15:57,238 - optimization.inference - INFO - Number of candidates by RT in frame 841: 291\n", + "2024-12-19 13:15:57,238 - optimization.inference - INFO - Number of candidates by RT in frame 1910: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,255 - optimization.inference - INFO - Scan time: 9.7708\n", + "2024-12-19 13:15:57,256 - optimization.inference - INFO - Number of candidates by RT in frame 846: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,257 - optimization.inference - INFO - Scan time: 28.1145\n", + "2024-12-19 13:15:57,259 - optimization.inference - INFO - Number of candidates by RT in frame 1915: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,272 - optimization.inference - INFO - Scan time: 9.8559\n", + "2024-12-19 13:15:57,273 - optimization.inference - INFO - Number of candidates by RT in frame 851: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,278 - optimization.inference - INFO - Scan time: 28.2001\n", + "2024-12-19 13:15:57,280 - optimization.inference - INFO - Number of candidates by RT in frame 1920: 247\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,291 - optimization.inference - INFO - Scan time: 9.9417\n", + "2024-12-19 13:15:57,292 - optimization.inference - INFO - Number of candidates by RT in frame 856: 284\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,300 - optimization.inference - INFO - Scan time: 28.2853\n", + "2024-12-19 13:15:57,301 - optimization.inference - INFO - Number of candidates by RT in frame 1925: 248\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,308 - optimization.inference - INFO - Scan time: 10.0274\n", + "2024-12-19 13:15:57,309 - optimization.inference - INFO - Number of candidates by RT in frame 861: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,315 - optimization.inference - INFO - Scan time: 28.3707\n", + "2024-12-19 13:15:57,316 - optimization.inference - INFO - Number of candidates by RT in frame 1930: 244\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,324 - optimization.inference - INFO - Scan time: 10.1126\n", + "2024-12-19 13:15:57,325 - optimization.inference - INFO - Number of candidates by RT in frame 866: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,334 - optimization.inference - INFO - Scan time: 28.456\n", + "2024-12-19 13:15:57,335 - optimization.inference - INFO - Number of candidates by RT in frame 1935: 228\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,340 - optimization.inference - INFO - Scan time: 10.198\n", + "2024-12-19 13:15:57,341 - optimization.inference - INFO - Number of candidates by RT in frame 871: 258\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,353 - optimization.inference - INFO - Scan time: 28.5417\n", + "2024-12-19 13:15:57,354 - optimization.inference - INFO - Number of candidates by RT in frame 1940: 237\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,358 - optimization.inference - INFO - Scan time: 10.2832\n", + "2024-12-19 13:15:57,359 - optimization.inference - INFO - Number of candidates by RT in frame 876: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,370 - optimization.inference - INFO - Scan time: 28.6267\n", + "2024-12-19 13:15:57,371 - optimization.inference - INFO - Number of candidates by RT in frame 1945: 235\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,375 - optimization.inference - INFO - Scan time: 10.3686\n", + "2024-12-19 13:15:57,376 - optimization.inference - INFO - Number of candidates by RT in frame 881: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,389 - optimization.inference - INFO - Scan time: 28.7124\n", + "2024-12-19 13:15:57,390 - optimization.inference - INFO - Number of candidates by RT in frame 1950: 213\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,392 - optimization.inference - INFO - Scan time: 10.4542\n", + "2024-12-19 13:15:57,393 - optimization.inference - INFO - Number of candidates by RT in frame 886: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,406 - optimization.inference - INFO - Scan time: 28.7976\n", + "2024-12-19 13:15:57,407 - optimization.inference - INFO - Number of candidates by RT in frame 1955: 208\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,410 - optimization.inference - INFO - Scan time: 10.5403\n", + "2024-12-19 13:15:57,411 - optimization.inference - INFO - Number of candidates by RT in frame 891: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,423 - optimization.inference - INFO - Scan time: 28.8832\n", + "2024-12-19 13:15:57,424 - optimization.inference - INFO - Number of candidates by RT in frame 1960: 201\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,425 - optimization.inference - INFO - Scan time: 10.6261\n", + "2024-12-19 13:15:57,426 - optimization.inference - INFO - Number of candidates by RT in frame 896: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,439 - optimization.inference - INFO - Scan time: 28.9692\n", + "2024-12-19 13:15:57,440 - optimization.inference - INFO - Number of candidates by RT in frame 1965: 198\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,443 - optimization.inference - INFO - Scan time: 10.7125\n", + "2024-12-19 13:15:57,444 - optimization.inference - INFO - Number of candidates by RT in frame 901: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,455 - optimization.inference - INFO - Scan time: 29.0553\n", + "2024-12-19 13:15:57,456 - optimization.inference - INFO - Number of candidates by RT in frame 1970: 201\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,460 - optimization.inference - INFO - Scan time: 10.7993\n", + "2024-12-19 13:15:57,461 - optimization.inference - INFO - Number of candidates by RT in frame 906: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,471 - optimization.inference - INFO - Scan time: 29.1409\n", + "2024-12-19 13:15:57,473 - optimization.inference - INFO - Number of candidates by RT in frame 1975: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,478 - optimization.inference - INFO - Scan time: 10.8846\n", + "2024-12-19 13:15:57,479 - optimization.inference - INFO - Number of candidates by RT in frame 911: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,487 - optimization.inference - INFO - Scan time: 29.2258\n", + "2024-12-19 13:15:57,488 - optimization.inference - INFO - Number of candidates by RT in frame 1980: 198\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,494 - optimization.inference - INFO - Scan time: 10.9699\n", + "2024-12-19 13:15:57,495 - optimization.inference - INFO - Number of candidates by RT in frame 916: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,504 - optimization.inference - INFO - Scan time: 29.3113\n", + "2024-12-19 13:15:57,505 - optimization.inference - INFO - Number of candidates by RT in frame 1985: 210\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,510 - optimization.inference - INFO - Scan time: 11.056\n", + "2024-12-19 13:15:57,512 - optimization.inference - INFO - Number of candidates by RT in frame 921: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,522 - optimization.inference - INFO - Scan time: 29.3967\n", + "2024-12-19 13:15:57,523 - optimization.inference - INFO - Number of candidates by RT in frame 1990: 205\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,529 - optimization.inference - INFO - Scan time: 11.1416\n", + "2024-12-19 13:15:57,531 - optimization.inference - INFO - Number of candidates by RT in frame 926: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,539 - optimization.inference - INFO - Scan time: 29.483\n", + "2024-12-19 13:15:57,540 - optimization.inference - INFO - Number of candidates by RT in frame 1995: 207\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,552 - optimization.inference - INFO - Scan time: 11.2275\n", + "2024-12-19 13:15:57,553 - optimization.inference - INFO - Number of candidates by RT in frame 931: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,558 - optimization.inference - INFO - Scan time: 29.569\n", + "2024-12-19 13:15:57,559 - optimization.inference - INFO - Number of candidates by RT in frame 2000: 218\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,572 - optimization.inference - INFO - Scan time: 11.3146\n", + "2024-12-19 13:15:57,573 - optimization.inference - INFO - Number of candidates by RT in frame 936: 298\n", + "2024-12-19 13:15:57,573 - optimization.inference - INFO - Scan time: 29.6547\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,574 - optimization.inference - INFO - Number of candidates by RT in frame 2005: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,592 - optimization.inference - INFO - Scan time: 11.4008\n", + "2024-12-19 13:15:57,592 - optimization.inference - INFO - Scan time: 29.7405\n", + "2024-12-19 13:15:57,593 - optimization.inference - INFO - Number of candidates by RT in frame 941: 298\n", + "2024-12-19 13:15:57,593 - optimization.inference - INFO - Number of candidates by RT in frame 2010: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,606 - optimization.inference - INFO - Scan time: 29.8258\n", + "2024-12-19 13:15:57,608 - optimization.inference - INFO - Number of candidates by RT in frame 2015: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,615 - optimization.inference - INFO - Scan time: 11.4875\n", + "2024-12-19 13:15:57,616 - optimization.inference - INFO - Number of candidates by RT in frame 946: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,623 - optimization.inference - INFO - Scan time: 29.9119\n", + "2024-12-19 13:15:57,624 - optimization.inference - INFO - Number of candidates by RT in frame 2020: 208\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,633 - optimization.inference - INFO - Scan time: 11.5726\n", + "2024-12-19 13:15:57,635 - optimization.inference - INFO - Number of candidates by RT in frame 951: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,639 - optimization.inference - INFO - Scan time: 29.9979\n", + "2024-12-19 13:15:57,640 - optimization.inference - INFO - Number of candidates by RT in frame 2025: 194\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,652 - optimization.inference - INFO - Scan time: 11.658\n", + "2024-12-19 13:15:57,653 - optimization.inference - INFO - Number of candidates by RT in frame 956: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,659 - optimization.inference - INFO - Scan time: 30.0842\n", + "2024-12-19 13:15:57,660 - optimization.inference - INFO - Number of candidates by RT in frame 2030: 193\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,668 - optimization.inference - INFO - Scan time: 11.7441\n", + "2024-12-19 13:15:57,669 - optimization.inference - INFO - Number of candidates by RT in frame 961: 294\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,675 - optimization.inference - INFO - Scan time: 30.1702\n", + "2024-12-19 13:15:57,676 - optimization.inference - INFO - Number of candidates by RT in frame 2035: 175\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,685 - optimization.inference - INFO - Scan time: 11.8296\n", + "2024-12-19 13:15:57,686 - optimization.inference - INFO - Number of candidates by RT in frame 966: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,690 - optimization.inference - INFO - Scan time: 30.2555\n", + "2024-12-19 13:15:57,691 - optimization.inference - INFO - Number of candidates by RT in frame 2040: 175\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,703 - optimization.inference - INFO - Scan time: 11.9154\n", + "2024-12-19 13:15:57,704 - optimization.inference - INFO - Number of candidates by RT in frame 971: 308\n", + "2024-12-19 13:15:57,704 - optimization.inference - INFO - Scan time: 30.3417\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,705 - optimization.inference - INFO - Number of candidates by RT in frame 2045: 184\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,721 - optimization.inference - INFO - Scan time: 30.4274\n", + "2024-12-19 13:15:57,722 - optimization.inference - INFO - Number of candidates by RT in frame 2050: 205\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,724 - optimization.inference - INFO - Scan time: 12.0014\n", + "2024-12-19 13:15:57,725 - optimization.inference - INFO - Number of candidates by RT in frame 976: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,740 - optimization.inference - INFO - Scan time: 30.5141\n", + "2024-12-19 13:15:57,741 - optimization.inference - INFO - Number of candidates by RT in frame 2055: 222\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,742 - optimization.inference - INFO - Scan time: 12.0879\n", + "2024-12-19 13:15:57,743 - optimization.inference - INFO - Number of candidates by RT in frame 981: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,755 - optimization.inference - INFO - Scan time: 30.5997\n", + "2024-12-19 13:15:57,757 - optimization.inference - INFO - Number of candidates by RT in frame 2060: 225\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,758 - optimization.inference - INFO - Scan time: 12.1746\n", + "2024-12-19 13:15:57,759 - optimization.inference - INFO - Number of candidates by RT in frame 986: 294\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,772 - optimization.inference - INFO - Scan time: 30.6847\n", + "2024-12-19 13:15:57,774 - optimization.inference - INFO - Number of candidates by RT in frame 2065: 219\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,775 - optimization.inference - INFO - Scan time: 12.2596\n", + "2024-12-19 13:15:57,776 - optimization.inference - INFO - Number of candidates by RT in frame 991: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,793 - optimization.inference - INFO - Scan time: 12.3442\n", + "2024-12-19 13:15:57,793 - optimization.inference - INFO - Scan time: 30.7702\n", + "2024-12-19 13:15:57,794 - optimization.inference - INFO - Number of candidates by RT in frame 996: 309\n", + "2024-12-19 13:15:57,794 - optimization.inference - INFO - Number of candidates by RT in frame 2070: 208\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,812 - optimization.inference - INFO - Scan time: 12.4302\n", + "2024-12-19 13:15:57,814 - optimization.inference - INFO - Number of candidates by RT in frame 1001: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,814 - optimization.inference - INFO - Scan time: 30.8562\n", + "2024-12-19 13:15:57,815 - optimization.inference - INFO - Number of candidates by RT in frame 2075: 195\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,830 - optimization.inference - INFO - Scan time: 12.5158\n", + "2024-12-19 13:15:57,831 - optimization.inference - INFO - Number of candidates by RT in frame 1006: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,832 - optimization.inference - INFO - Scan time: 30.9416\n", + "2024-12-19 13:15:57,833 - optimization.inference - INFO - Number of candidates by RT in frame 2080: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,848 - optimization.inference - INFO - Scan time: 12.602\n", + "2024-12-19 13:15:57,849 - optimization.inference - INFO - Scan time: 31.0271\n", + "2024-12-19 13:15:57,849 - optimization.inference - INFO - Number of candidates by RT in frame 1011: 307\n", + "2024-12-19 13:15:57,850 - optimization.inference - INFO - Number of candidates by RT in frame 2085: 182\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,864 - optimization.inference - INFO - Scan time: 31.1129\n", + "2024-12-19 13:15:57,865 - optimization.inference - INFO - Number of candidates by RT in frame 2090: 216\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,865 - optimization.inference - INFO - Scan time: 12.6876\n", + "2024-12-19 13:15:57,867 - optimization.inference - INFO - Number of candidates by RT in frame 1016: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,879 - optimization.inference - INFO - Scan time: 31.1987\n", + "2024-12-19 13:15:57,880 - optimization.inference - INFO - Number of candidates by RT in frame 2095: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,883 - optimization.inference - INFO - Scan time: 12.7726\n", + "2024-12-19 13:15:57,884 - optimization.inference - INFO - Number of candidates by RT in frame 1021: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,898 - optimization.inference - INFO - Scan time: 31.2842\n", + "2024-12-19 13:15:57,899 - optimization.inference - INFO - Number of candidates by RT in frame 2100: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,901 - optimization.inference - INFO - Scan time: 12.8588\n", + "2024-12-19 13:15:57,902 - optimization.inference - INFO - Number of candidates by RT in frame 1026: 328\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,916 - optimization.inference - INFO - Scan time: 31.3701\n", + "2024-12-19 13:15:57,917 - optimization.inference - INFO - Number of candidates by RT in frame 2105: 206\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,921 - optimization.inference - INFO - Scan time: 12.9452\n", + "2024-12-19 13:15:57,922 - optimization.inference - INFO - Number of candidates by RT in frame 1031: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,931 - optimization.inference - INFO - Scan time: 31.4562\n", + "2024-12-19 13:15:57,932 - optimization.inference - INFO - Number of candidates by RT in frame 2110: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,943 - optimization.inference - INFO - Scan time: 13.0303\n", + "2024-12-19 13:15:57,944 - optimization.inference - INFO - Number of candidates by RT in frame 1036: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,948 - optimization.inference - INFO - Scan time: 31.5416\n", + "2024-12-19 13:15:57,949 - optimization.inference - INFO - Number of candidates by RT in frame 2115: 187\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,958 - optimization.inference - INFO - Scan time: 0.0074\n", + "2024-12-19 13:15:57,960 - optimization.inference - INFO - Number of candidates by RT in frame 2: 25\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,963 - optimization.inference - INFO - Scan time: 13.1166\n", + "2024-12-19 13:15:57,964 - optimization.inference - INFO - Number of candidates by RT in frame 1041: 320\n", + "2024-12-19 13:15:57,964 - optimization.inference - INFO - Scan time: 31.6275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,965 - optimization.inference - INFO - Number of candidates by RT in frame 2120: 156\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,967 - optimization.inference - INFO - Scan time: 0.019\n", + "2024-12-19 13:15:57,968 - optimization.inference - INFO - Number of candidates by RT in frame 7: 32\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,974 - optimization.inference - INFO - Scan time: 0.0305\n", + "2024-12-19 13:15:57,975 - optimization.inference - INFO - Number of candidates by RT in frame 12: 32\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,977 - optimization.inference - INFO - Scan time: 31.7132\n", + "2024-12-19 13:15:57,977 - optimization.inference - INFO - Scan time: 13.2025\n", + "2024-12-19 13:15:57,978 - optimization.inference - INFO - Number of candidates by RT in frame 2125: 140\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,978 - optimization.inference - INFO - Number of candidates by RT in frame 1046: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,980 - optimization.inference - INFO - Scan time: 0.042\n", + "2024-12-19 13:15:57,981 - optimization.inference - INFO - Number of candidates by RT in frame 17: 34\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,986 - optimization.inference - INFO - Scan time: 0.0536\n", + "2024-12-19 13:15:57,987 - optimization.inference - INFO - Number of candidates by RT in frame 22: 37\n", + "2024-12-19 13:15:57,988 - optimization.inference - INFO - Scan time: 31.7988\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,988 - optimization.inference - INFO - Number of candidates by RT in frame 2130: 141\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,993 - optimization.inference - INFO - Scan time: 0.0651\n", + "2024-12-19 13:15:57,994 - optimization.inference - INFO - Number of candidates by RT in frame 27: 40\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:57,995 - optimization.inference - INFO - Scan time: 13.2895\n", + "2024-12-19 13:15:57,996 - optimization.inference - INFO - Number of candidates by RT in frame 1051: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,000 - optimization.inference - INFO - Scan time: 0.0766\n", + "2024-12-19 13:15:58,001 - optimization.inference - INFO - Number of candidates by RT in frame 32: 40\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,005 - optimization.inference - INFO - Scan time: 31.8846\n", + "2024-12-19 13:15:58,006 - optimization.inference - INFO - Number of candidates by RT in frame 2135: 105\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,007 - optimization.inference - INFO - Scan time: 0.0882\n", + "2024-12-19 13:15:58,008 - optimization.inference - INFO - Number of candidates by RT in frame 37: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,010 - optimization.inference - INFO - Scan time: 13.3758\n", + "2024-12-19 13:15:58,011 - optimization.inference - INFO - Number of candidates by RT in frame 1056: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,020 - optimization.inference - INFO - Scan time: 31.9707\n", + "2024-12-19 13:15:58,021 - optimization.inference - INFO - Number of candidates by RT in frame 2140: 66\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,026 - optimization.inference - INFO - Scan time: 13.4627\n", + "2024-12-19 13:15:58,027 - optimization.inference - INFO - Number of candidates by RT in frame 1061: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,034 - optimization.inference - INFO - Scan time: 32.0573\n", + "2024-12-19 13:15:58,035 - optimization.inference - INFO - Number of candidates by RT in frame 2145: 32\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,043 - optimization.inference - INFO - Scan time: 13.5478\n", + "2024-12-19 13:15:58,044 - optimization.inference - INFO - Number of candidates by RT in frame 1066: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,046 - optimization.inference - INFO - Scan time: 32.1371\n", + "2024-12-19 13:15:58,047 - optimization.inference - INFO - Number of candidates by RT in frame 2150: 19\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,058 - optimization.inference - INFO - Scan time: 32.1791\n", + "2024-12-19 13:15:58,059 - optimization.inference - INFO - Number of candidates by RT in frame 2155: 17\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,062 - optimization.inference - INFO - Scan time: 13.6344\n", + "2024-12-19 13:15:58,063 - optimization.inference - INFO - Number of candidates by RT in frame 1071: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,069 - optimization.inference - INFO - Scan time: 32.2025\n", + "2024-12-19 13:15:58,070 - optimization.inference - INFO - Number of candidates by RT in frame 2160: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,081 - optimization.inference - INFO - Scan time: 32.2169\n", + "2024-12-19 13:15:58,081 - optimization.inference - INFO - Scan time: 13.7202\n", + "2024-12-19 13:15:58,082 - optimization.inference - INFO - Number of candidates by RT in frame 2165: 14\n", + "2024-12-19 13:15:58,082 - optimization.inference - INFO - Number of candidates by RT in frame 1076: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,092 - optimization.inference - INFO - Scan time: 32.2366\n", + "2024-12-19 13:15:58,093 - optimization.inference - INFO - Number of candidates by RT in frame 2170: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,099 - optimization.inference - INFO - Scan time: 13.8067\n", + "2024-12-19 13:15:58,099 - optimization.inference - INFO - Scan time: 0.1576\n", + "2024-12-19 13:15:58,100 - optimization.inference - INFO - Number of candidates by RT in frame 1081: 323\n", + "2024-12-19 13:15:58,100 - optimization.inference - INFO - Number of candidates by RT in frame 42: 64\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,102 - optimization.inference - INFO - Scan time: 32.2628\n", + "2024-12-19 13:15:58,103 - optimization.inference - INFO - Number of candidates by RT in frame 2175: 12\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,107 - optimization.inference - INFO - Scan time: 0.232\n", + "2024-12-19 13:15:58,109 - optimization.inference - INFO - Number of candidates by RT in frame 47: 71\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,115 - optimization.inference - INFO - Scan time: 32.2858\n", + "2024-12-19 13:15:58,116 - optimization.inference - INFO - Number of candidates by RT in frame 2180: 12\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,122 - optimization.inference - INFO - Scan time: 0.3023\n", + "2024-12-19 13:15:58,124 - optimization.inference - INFO - Number of candidates by RT in frame 52: 76\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,127 - optimization.inference - INFO - Scan time: 32.2994\n", + "2024-12-19 13:15:58,127 - optimization.inference - INFO - Scan time: 13.8926\n", + "2024-12-19 13:15:58,128 - optimization.inference - INFO - Number of candidates by RT in frame 2185: 11\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,128 - optimization.inference - INFO - Number of candidates by RT in frame 1086: 314\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,135 - optimization.inference - INFO - Scan time: 0.3703\n", + "2024-12-19 13:15:58,136 - optimization.inference - INFO - Number of candidates by RT in frame 57: 66\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,138 - optimization.inference - INFO - Scan time: 32.3124\n", + "2024-12-19 13:15:58,139 - optimization.inference - INFO - Number of candidates by RT in frame 2190: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,149 - optimization.inference - INFO - Scan time: 0.4445\n", + "2024-12-19 13:15:58,150 - optimization.inference - INFO - Scan time: 32.3294\n", + "2024-12-19 13:15:58,150 - optimization.inference - INFO - Number of candidates by RT in frame 62: 63\n", + "2024-12-19 13:15:58,150 - optimization.inference - INFO - Number of candidates by RT in frame 2195: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,158 - optimization.inference - INFO - Scan time: 13.9773\n", + "2024-12-19 13:15:58,160 - optimization.inference - INFO - Number of candidates by RT in frame 1091: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,161 - optimization.inference - INFO - Scan time: 32.3436\n", + "2024-12-19 13:15:58,161 - optimization.inference - INFO - Number of candidates by RT in frame 2200: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,165 - optimization.inference - INFO - Scan time: 0.5017\n", + "2024-12-19 13:15:58,166 - optimization.inference - INFO - Number of candidates by RT in frame 67: 65\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,171 - optimization.inference - INFO - Scan time: 32.367\n", + "2024-12-19 13:15:58,171 - optimization.inference - INFO - Number of candidates by RT in frame 2205: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,177 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", + "2024-12-19 13:15:58,180 - optimization.inference - INFO - Scan time: 0.5399\n", + "2024-12-19 13:15:58,182 - optimization.inference - INFO - Number of candidates by RT in frame 72: 66\n", + "2024-12-19 13:15:58,182 - optimization.inference - INFO - Scan time: 32.3875\n", + "2024-12-19 13:15:58,183 - optimization.inference - INFO - Number of candidates by RT in frame 2210: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,187 - optimization.inference - INFO - Scan time: 14.0633\n", + "2024-12-19 13:15:58,188 - optimization.inference - INFO - Number of candidates by RT in frame 1096: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", + " from pandas.core import (\n", + "2024-12-19 13:15:58,192 - optimization.inference - INFO - Scan time: 32.4038\n", + "2024-12-19 13:15:58,193 - optimization.inference - INFO - Number of candidates by RT in frame 2215: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,197 - optimization.inference - INFO - Scan time: 0.5653\n", + "2024-12-19 13:15:58,198 - optimization.inference - INFO - Number of candidates by RT in frame 77: 67\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,203 - optimization.inference - INFO - Scan time: 32.4242\n", + "2024-12-19 13:15:58,203 - optimization.inference - INFO - Number of candidates by RT in frame 2220: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,213 - optimization.inference - INFO - Scan time: 0.5887\n", + "2024-12-19 13:15:58,213 - optimization.inference - INFO - Scan time: 32.4365\n", + "2024-12-19 13:15:58,214 - optimization.inference - INFO - Number of candidates by RT in frame 2225: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,214 - optimization.inference - INFO - Number of candidates by RT in frame 82: 68\n", + "2024-12-19 13:15:58,215 - optimization.inference - INFO - Scan time: 14.1493\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,216 - optimization.inference - INFO - Number of candidates by RT in frame 1101: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,222 - optimization.inference - INFO - Scan time: 32.4492\n", + "2024-12-19 13:15:58,223 - optimization.inference - INFO - Number of candidates by RT in frame 2230: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,229 - optimization.inference - INFO - Scan time: 0.6154\n", + "2024-12-19 13:15:58,230 - optimization.inference - INFO - Number of candidates by RT in frame 87: 68\n", + "2024-12-19 13:15:58,231 - optimization.inference - INFO - Scan time: 32.4627\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,231 - optimization.inference - INFO - Number of candidates by RT in frame 2235: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,239 - optimization.inference - INFO - Scan time: 32.4756\n", + "2024-12-19 13:15:58,240 - optimization.inference - INFO - Number of candidates by RT in frame 2240: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,241 - optimization.inference - INFO - Scan time: 14.2352\n", + "2024-12-19 13:15:58,243 - optimization.inference - INFO - Number of candidates by RT in frame 1106: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,245 - optimization.inference - INFO - Scan time: 0.6359\n", + "2024-12-19 13:15:58,246 - optimization.inference - INFO - Number of candidates by RT in frame 92: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,249 - optimization.inference - INFO - Scan time: 32.4883\n", + "2024-12-19 13:15:58,250 - optimization.inference - INFO - Number of candidates by RT in frame 2245: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,259 - optimization.inference - INFO - Scan time: 32.504\n", + "2024-12-19 13:15:58,260 - optimization.inference - INFO - Number of candidates by RT in frame 2250: 4\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,262 - optimization.inference - INFO - Scan time: 0.6507\n", + "2024-12-19 13:15:58,263 - optimization.inference - INFO - Number of candidates by RT in frame 97: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,269 - optimization.inference - INFO - Scan time: 32.5183\n", + "2024-12-19 13:15:58,270 - optimization.inference - INFO - Number of candidates by RT in frame 2255: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,271 - optimization.inference - INFO - Scan time: 14.3213\n", + "2024-12-19 13:15:58,273 - optimization.inference - INFO - Number of candidates by RT in frame 1111: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,277 - optimization.inference - INFO - Scan time: 32.5352\n", + "2024-12-19 13:15:58,278 - optimization.inference - INFO - Number of candidates by RT in frame 2260: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,279 - optimization.inference - INFO - Scan time: 0.672\n", + "2024-12-19 13:15:58,280 - optimization.inference - INFO - Number of candidates by RT in frame 102: 70\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,285 - optimization.inference - INFO - Scan time: 32.5521\n", + "2024-12-19 13:15:58,286 - optimization.inference - INFO - Number of candidates by RT in frame 2265: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,295 - optimization.inference - INFO - Scan time: 32.571\n", + "2024-12-19 13:15:58,295 - optimization.inference - INFO - Number of candidates by RT in frame 2270: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,296 - optimization.inference - INFO - Scan time: 0.6856\n", + "2024-12-19 13:15:58,298 - optimization.inference - INFO - Number of candidates by RT in frame 107: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,301 - optimization.inference - INFO - Scan time: 14.4071\n", + "2024-12-19 13:15:58,303 - optimization.inference - INFO - Scan time: 32.5845\n", + "2024-12-19 13:15:58,303 - optimization.inference - INFO - Number of candidates by RT in frame 1116: 310\n", + "2024-12-19 13:15:58,304 - optimization.inference - INFO - Number of candidates by RT in frame 2275: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,311 - optimization.inference - INFO - Scan time: 32.5974\n", + "2024-12-19 13:15:58,312 - optimization.inference - INFO - Number of candidates by RT in frame 2280: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,313 - optimization.inference - INFO - Scan time: 0.7024\n", + "2024-12-19 13:15:58,315 - optimization.inference - INFO - Number of candidates by RT in frame 112: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,319 - optimization.inference - INFO - Scan time: 32.6115\n", + "2024-12-19 13:15:58,319 - optimization.inference - INFO - Number of candidates by RT in frame 2285: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,327 - optimization.inference - INFO - Scan time: 32.6259\n", + "2024-12-19 13:15:58,327 - optimization.inference - INFO - Number of candidates by RT in frame 2290: 3\n", + "2024-12-19 13:15:58,327 - optimization.inference - INFO - Scan time: 14.4923\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,329 - optimization.inference - INFO - Number of candidates by RT in frame 1121: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,331 - optimization.inference - INFO - Scan time: 0.716\n", + "2024-12-19 13:15:58,332 - optimization.inference - INFO - Number of candidates by RT in frame 117: 67\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,335 - optimization.inference - INFO - Scan time: 32.6408\n", + "2024-12-19 13:15:58,336 - optimization.inference - INFO - Number of candidates by RT in frame 2295: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,343 - optimization.inference - INFO - Scan time: 32.6575\n", + "2024-12-19 13:15:58,344 - optimization.inference - INFO - Number of candidates by RT in frame 2300: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,347 - optimization.inference - INFO - Scan time: 0.7394\n", + "2024-12-19 13:15:58,349 - optimization.inference - INFO - Number of candidates by RT in frame 122: 63\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,351 - optimization.inference - INFO - Scan time: 32.6709\n", + "2024-12-19 13:15:58,351 - optimization.inference - INFO - Number of candidates by RT in frame 2305: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,359 - optimization.inference - INFO - Scan time: 32.6874\n", + "2024-12-19 13:15:58,360 - optimization.inference - INFO - Number of candidates by RT in frame 2310: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,362 - optimization.inference - INFO - Scan time: 14.5781\n", + "2024-12-19 13:15:58,364 - optimization.inference - INFO - Number of candidates by RT in frame 1126: 329\n", + "2024-12-19 13:15:58,364 - optimization.inference - INFO - Scan time: 0.7624\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,366 - optimization.inference - INFO - Number of candidates by RT in frame 127: 62\n", + "2024-12-19 13:15:58,367 - optimization.inference - INFO - Scan time: 32.7023\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,368 - optimization.inference - INFO - Number of candidates by RT in frame 2315: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,374 - optimization.inference - INFO - Scan time: 32.7164\n", + "2024-12-19 13:15:58,375 - optimization.inference - INFO - Number of candidates by RT in frame 2320: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,381 - optimization.inference - INFO - Scan time: 0.7815\n", + "2024-12-19 13:15:58,382 - optimization.inference - INFO - Scan time: 32.7333\n", + "2024-12-19 13:15:58,382 - optimization.inference - INFO - Number of candidates by RT in frame 132: 59\n", + "2024-12-19 13:15:58,383 - optimization.inference - INFO - Number of candidates by RT in frame 2325: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,390 - optimization.inference - INFO - Scan time: 32.746\n", + "2024-12-19 13:15:58,391 - optimization.inference - INFO - Number of candidates by RT in frame 2330: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,394 - optimization.inference - INFO - Scan time: 14.6639\n", + "2024-12-19 13:15:58,396 - optimization.inference - INFO - Number of candidates by RT in frame 1131: 340\n", + "2024-12-19 13:15:58,397 - optimization.inference - INFO - Scan time: 0.8006\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,398 - optimization.inference - INFO - Scan time: 32.7617\n", + "2024-12-19 13:15:58,398 - optimization.inference - INFO - Number of candidates by RT in frame 137: 57\n", + "2024-12-19 13:15:58,399 - optimization.inference - INFO - Number of candidates by RT in frame 2335: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,405 - optimization.inference - INFO - Scan time: 32.7815\n", + "2024-12-19 13:15:58,406 - optimization.inference - INFO - Number of candidates by RT in frame 2340: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,412 - optimization.inference - INFO - Scan time: 0.8202\n", + "2024-12-19 13:15:58,412 - optimization.inference - INFO - Scan time: 32.7963\n", + "2024-12-19 13:15:58,413 - optimization.inference - INFO - Number of candidates by RT in frame 2345: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,413 - optimization.inference - INFO - Number of candidates by RT in frame 142: 54\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,419 - optimization.inference - INFO - Scan time: 32.8113\n", + "2024-12-19 13:15:58,419 - optimization.inference - INFO - Number of candidates by RT in frame 2350: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,426 - optimization.inference - INFO - Scan time: 32.8267\n", + "2024-12-19 13:15:58,426 - optimization.inference - INFO - Scan time: 14.7496\n", + "2024-12-19 13:15:58,426 - optimization.inference - INFO - Number of candidates by RT in frame 2355: 2\n", + "2024-12-19 13:15:58,427 - optimization.inference - INFO - Scan time: 0.8431\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,427 - optimization.inference - INFO - Number of candidates by RT in frame 1136: 318\n", + "2024-12-19 13:15:58,428 - optimization.inference - INFO - Number of candidates by RT in frame 147: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,433 - optimization.inference - INFO - Scan time: 32.8415\n", + "2024-12-19 13:15:58,433 - optimization.inference - INFO - Number of candidates by RT in frame 2360: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,440 - optimization.inference - INFO - Scan time: 32.8565\n", + "2024-12-19 13:15:58,441 - optimization.inference - INFO - Number of candidates by RT in frame 2365: 2\n", + "2024-12-19 13:15:58,441 - optimization.inference - INFO - Scan time: 0.8565\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,442 - optimization.inference - INFO - Number of candidates by RT in frame 152: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,447 - optimization.inference - INFO - Scan time: 32.8699\n", + "2024-12-19 13:15:58,448 - optimization.inference - INFO - Number of candidates by RT in frame 2370: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,455 - optimization.inference - INFO - Scan time: 32.8814\n", + "2024-12-19 13:15:58,455 - optimization.inference - INFO - Scan time: 14.8357\n", + "2024-12-19 13:15:58,456 - optimization.inference - INFO - Number of candidates by RT in frame 2375: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,456 - optimization.inference - INFO - Scan time: 0.8725\n", + "2024-12-19 13:15:58,457 - optimization.inference - INFO - Number of candidates by RT in frame 1141: 324\n", + "2024-12-19 13:15:58,457 - optimization.inference - INFO - Number of candidates by RT in frame 157: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,462 - optimization.inference - INFO - Scan time: 32.8977\n", + "2024-12-19 13:15:58,463 - optimization.inference - INFO - Number of candidates by RT in frame 2380: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,469 - optimization.inference - INFO - Scan time: 32.911\n", + "2024-12-19 13:15:58,470 - optimization.inference - INFO - Number of candidates by RT in frame 2385: 2\n", + "2024-12-19 13:15:58,470 - optimization.inference - INFO - Scan time: 0.89\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,471 - optimization.inference - INFO - Number of candidates by RT in frame 162: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,476 - optimization.inference - INFO - Scan time: 32.9232\n", + "2024-12-19 13:15:58,477 - optimization.inference - INFO - Number of candidates by RT in frame 2390: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,483 - optimization.inference - INFO - Scan time: 32.9376\n", + "2024-12-19 13:15:58,484 - optimization.inference - INFO - Number of candidates by RT in frame 2395: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,484 - optimization.inference - INFO - Scan time: 0.9067\n", + "2024-12-19 13:15:58,486 - optimization.inference - INFO - Number of candidates by RT in frame 167: 57\n", + "2024-12-19 13:15:58,490 - optimization.inference - INFO - Scan time: 32.9497\n", + "2024-12-19 13:15:58,491 - optimization.inference - INFO - Number of candidates by RT in frame 2400: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,493 - optimization.inference - INFO - Scan time: 14.9208\n", + "2024-12-19 13:15:58,494 - optimization.inference - INFO - Number of candidates by RT in frame 1146: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,497 - optimization.inference - INFO - Scan time: 32.9613\n", + "2024-12-19 13:15:58,498 - optimization.inference - INFO - Number of candidates by RT in frame 2405: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,503 - optimization.inference - INFO - Scan time: 32.9728\n", + "2024-12-19 13:15:58,504 - optimization.inference - INFO - Scan time: 0.9283\n", + "2024-12-19 13:15:58,504 - optimization.inference - INFO - Number of candidates by RT in frame 2410: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,505 - optimization.inference - INFO - Number of candidates by RT in frame 172: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,510 - optimization.inference - INFO - Scan time: 32.9911\n", + "2024-12-19 13:15:58,511 - optimization.inference - INFO - Number of candidates by RT in frame 2415: 1\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,516 - optimization.inference - INFO - Shape of COO matrix: (2421, 18939)\n", + "2024-12-19 13:15:58,517 - optimization.inference - INFO - Scan time: 0.9487\n", + "2024-12-19 13:15:58,518 - optimization.inference - INFO - Number of candidates by RT in frame 177: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,525 - optimization.inference - INFO - Scan time: 0.9643\n", + "2024-12-19 13:15:58,526 - optimization.inference - INFO - Number of candidates by RT in frame 182: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,530 - optimization.inference - INFO - Scan time: 15.007\n", + "2024-12-19 13:15:58,532 - optimization.inference - INFO - Number of candidates by RT in frame 1151: 322\n", + "2024-12-19 13:15:58,533 - optimization.inference - INFO - Scan time: 0.9855\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,534 - optimization.inference - INFO - Number of candidates by RT in frame 187: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,541 - optimization.inference - INFO - Scan time: 1.0053\n", + "2024-12-19 13:15:58,542 - optimization.inference - INFO - Number of candidates by RT in frame 192: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,548 - optimization.inference - INFO - Scan time: 1.0252\n", + "2024-12-19 13:15:58,549 - optimization.inference - INFO - Number of candidates by RT in frame 197: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,556 - optimization.inference - INFO - Scan time: 1.0478\n", + "2024-12-19 13:15:58,557 - optimization.inference - INFO - Number of candidates by RT in frame 202: 49\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,564 - optimization.inference - INFO - Scan time: 1.0632\n", + "2024-12-19 13:15:58,564 - optimization.inference - INFO - Number of candidates by RT in frame 207: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,565 - optimization.inference - INFO - Scan time: 15.0927\n", + "2024-12-19 13:15:58,567 - optimization.inference - INFO - Number of candidates by RT in frame 1156: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,571 - optimization.inference - INFO - Scan time: 1.0843\n", + "2024-12-19 13:15:58,572 - optimization.inference - INFO - Number of candidates by RT in frame 212: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,579 - optimization.inference - INFO - Scan time: 1.0972\n", + "2024-12-19 13:15:58,580 - optimization.inference - INFO - Number of candidates by RT in frame 217: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,587 - optimization.inference - INFO - Scan time: 1.1234\n", + "2024-12-19 13:15:58,587 - optimization.inference - INFO - Number of candidates by RT in frame 222: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,594 - optimization.inference - INFO - Scan time: 1.1481\n", + "2024-12-19 13:15:58,595 - optimization.inference - INFO - Number of candidates by RT in frame 227: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,600 - optimization.inference - INFO - Size of COO matrix in batch 0: 1.618512 Mb\n", + "2024-12-19 13:15:58,602 - optimization.inference - INFO - Scan time: 1.1692\n", + "2024-12-19 13:15:58,603 - optimization.inference - INFO - Number of candidates by RT in frame 232: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,608 - optimization.inference - INFO - Scan time: 15.1791\n", + "2024-12-19 13:15:58,610 - optimization.inference - INFO - Number of candidates by RT in frame 1161: 327\n", + "2024-12-19 13:15:58,610 - optimization.inference - INFO - Scan time: 1.1883\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,611 - optimization.inference - INFO - Number of candidates by RT in frame 237: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,619 - optimization.inference - INFO - Scan time: 1.2004\n", + "2024-12-19 13:15:58,620 - optimization.inference - INFO - Number of candidates by RT in frame 242: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,627 - optimization.inference - INFO - Scan time: 1.2172\n", + "2024-12-19 13:15:58,628 - optimization.inference - INFO - Number of candidates by RT in frame 247: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,635 - optimization.inference - INFO - Scan time: 1.2306\n", + "2024-12-19 13:15:58,635 - optimization.inference - INFO - Scan time: 15.2643\n", + "2024-12-19 13:15:58,636 - optimization.inference - INFO - Number of candidates by RT in frame 252: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,637 - optimization.inference - INFO - Number of candidates by RT in frame 1166: 332\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,643 - optimization.inference - INFO - Scan time: 1.2462\n", + "2024-12-19 13:15:58,644 - optimization.inference - INFO - Number of candidates by RT in frame 257: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,652 - optimization.inference - INFO - Scan time: 1.2671\n", + "2024-12-19 13:15:58,652 - optimization.inference - INFO - Number of candidates by RT in frame 262: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,660 - optimization.inference - INFO - Scan time: 1.284\n", + "2024-12-19 13:15:58,661 - optimization.inference - INFO - Number of candidates by RT in frame 267: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,664 - optimization.inference - INFO - Scan time: 15.3507\n", + "2024-12-19 13:15:58,666 - optimization.inference - INFO - Number of candidates by RT in frame 1171: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,669 - optimization.inference - INFO - Scan time: 1.3036\n", + "2024-12-19 13:15:58,670 - optimization.inference - INFO - Number of candidates by RT in frame 272: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,678 - optimization.inference - INFO - Scan time: 1.3248\n", + "2024-12-19 13:15:58,679 - optimization.inference - INFO - Number of candidates by RT in frame 277: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,686 - optimization.inference - INFO - Scan time: 1.3428\n", + "2024-12-19 13:15:58,687 - optimization.inference - INFO - Number of candidates by RT in frame 282: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,693 - optimization.inference - INFO - Scan time: 15.4363\n", + "2024-12-19 13:15:58,695 - optimization.inference - INFO - Number of candidates by RT in frame 1176: 335\n", + "2024-12-19 13:15:58,695 - optimization.inference - INFO - Scan time: 1.3571\n", + "2024-12-19 13:15:58,696 - optimization.inference - INFO - Number of candidates by RT in frame 287: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,703 - optimization.inference - INFO - Scan time: 1.3782\n", + "2024-12-19 13:15:58,704 - optimization.inference - INFO - Number of candidates by RT in frame 292: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,713 - optimization.inference - INFO - Scan time: 1.3959\n", + "2024-12-19 13:15:58,713 - optimization.inference - INFO - Number of candidates by RT in frame 297: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,716 - optimization.inference - INFO - Scan time: 15.5224\n", + "2024-12-19 13:15:58,718 - optimization.inference - INFO - Number of candidates by RT in frame 1181: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,721 - optimization.inference - INFO - Scan time: 1.4088\n", + "2024-12-19 13:15:58,725 - optimization.inference - INFO - Number of candidates by RT in frame 302: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,733 - optimization.inference - INFO - Scan time: 1.4271\n", + "2024-12-19 13:15:58,734 - optimization.inference - INFO - Number of candidates by RT in frame 307: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,737 - optimization.inference - INFO - Scan time: 15.6086\n", + "2024-12-19 13:15:58,738 - optimization.inference - INFO - Number of candidates by RT in frame 1186: 345\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,742 - optimization.inference - INFO - Scan time: 1.4462\n", + "2024-12-19 13:15:58,743 - optimization.inference - INFO - Number of candidates by RT in frame 312: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,751 - optimization.inference - INFO - Scan time: 1.4598\n", + "2024-12-19 13:15:58,752 - optimization.inference - INFO - Number of candidates by RT in frame 317: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,759 - optimization.inference - INFO - Scan time: 15.6939\n", + "2024-12-19 13:15:58,759 - optimization.inference - INFO - Scan time: 1.4759\n", + "2024-12-19 13:15:58,760 - optimization.inference - INFO - Number of candidates by RT in frame 1191: 331\n", + "2024-12-19 13:15:58,760 - optimization.inference - INFO - Number of candidates by RT in frame 322: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,768 - optimization.inference - INFO - Scan time: 1.4936\n", + "2024-12-19 13:15:58,769 - optimization.inference - INFO - Number of candidates by RT in frame 327: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,777 - optimization.inference - INFO - Scan time: 1.5109\n", + "2024-12-19 13:15:58,778 - optimization.inference - INFO - Number of candidates by RT in frame 332: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,779 - optimization.inference - INFO - Scan time: 15.7798\n", + "2024-12-19 13:15:58,780 - optimization.inference - INFO - Number of candidates by RT in frame 1196: 333\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,786 - optimization.inference - INFO - Scan time: 1.5272\n", + "2024-12-19 13:15:58,787 - optimization.inference - INFO - Number of candidates by RT in frame 337: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,795 - optimization.inference - INFO - Scan time: 1.5491\n", + "2024-12-19 13:15:58,796 - optimization.inference - INFO - Number of candidates by RT in frame 342: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,797 - optimization.inference - INFO - Scan time: 15.8655\n", + "2024-12-19 13:15:58,799 - optimization.inference - INFO - Number of candidates by RT in frame 1201: 314\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,804 - optimization.inference - INFO - Scan time: 1.5662\n", + "2024-12-19 13:15:58,805 - optimization.inference - INFO - Number of candidates by RT in frame 347: 54\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,814 - optimization.inference - INFO - Scan time: 1.5916\n", + "2024-12-19 13:15:58,815 - optimization.inference - INFO - Number of candidates by RT in frame 352: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,816 - optimization.inference - INFO - Scan time: 15.9505\n", + "2024-12-19 13:15:58,817 - optimization.inference - INFO - Number of candidates by RT in frame 1206: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,823 - optimization.inference - INFO - Scan time: 1.6234\n", + "2024-12-19 13:15:58,824 - optimization.inference - INFO - Number of candidates by RT in frame 357: 58\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,834 - optimization.inference - INFO - Scan time: 1.663\n", + "2024-12-19 13:15:58,834 - optimization.inference - INFO - Scan time: 16.0361\n", + "2024-12-19 13:15:58,835 - optimization.inference - INFO - Number of candidates by RT in frame 362: 74\n", + "2024-12-19 13:15:58,836 - optimization.inference - INFO - Number of candidates by RT in frame 1211: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,842 - optimization.inference - INFO - Scan time: 1.6866\n", + "2024-12-19 13:15:58,843 - optimization.inference - INFO - Number of candidates by RT in frame 367: 87\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,852 - optimization.inference - INFO - Scan time: 16.1212\n", + "2024-12-19 13:15:58,854 - optimization.inference - INFO - Number of candidates by RT in frame 1216: 298\n", + "2024-12-19 13:15:58,854 - optimization.inference - INFO - Scan time: 1.723\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,855 - optimization.inference - INFO - Number of candidates by RT in frame 372: 101\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,871 - optimization.inference - INFO - Scan time: 16.2081\n", + "2024-12-19 13:15:58,872 - optimization.inference - INFO - Number of candidates by RT in frame 1221: 309\n", + "2024-12-19 13:15:58,873 - optimization.inference - INFO - Scan time: 1.7769\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,874 - optimization.inference - INFO - Number of candidates by RT in frame 377: 117\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,888 - optimization.inference - INFO - Scan time: 16.2933\n", + "2024-12-19 13:15:58,889 - optimization.inference - INFO - Number of candidates by RT in frame 1226: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,893 - optimization.inference - INFO - Scan time: 1.8591\n", + "2024-12-19 13:15:58,894 - optimization.inference - INFO - Number of candidates by RT in frame 382: 126\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,908 - optimization.inference - INFO - Scan time: 16.3791\n", + "2024-12-19 13:15:58,909 - optimization.inference - INFO - Number of candidates by RT in frame 1231: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,913 - optimization.inference - INFO - Scan time: 1.9446\n", + "2024-12-19 13:15:58,915 - optimization.inference - INFO - Number of candidates by RT in frame 387: 117\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,929 - optimization.inference - INFO - Scan time: 16.4651\n", + "2024-12-19 13:15:58,930 - optimization.inference - INFO - Number of candidates by RT in frame 1236: 329\n", + "2024-12-19 13:15:58,931 - optimization.inference - INFO - Scan time: 2.0113\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,933 - optimization.inference - INFO - Number of candidates by RT in frame 392: 112\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,944 - optimization.inference - INFO - Scan time: 2.0823\n", + "2024-12-19 13:15:58,945 - optimization.inference - INFO - Number of candidates by RT in frame 397: 104\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,953 - optimization.inference - INFO - Scan time: 2.1613\n", + "2024-12-19 13:15:58,954 - optimization.inference - INFO - Number of candidates by RT in frame 402: 120\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,959 - optimization.inference - INFO - Scan time: 16.5506\n", + "2024-12-19 13:15:58,960 - optimization.inference - INFO - Number of candidates by RT in frame 1241: 318\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,963 - optimization.inference - INFO - Scan time: 2.2393\n", + "2024-12-19 13:15:58,964 - optimization.inference - INFO - Number of candidates by RT in frame 407: 128\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,973 - optimization.inference - INFO - Scan time: 2.321\n", + "2024-12-19 13:15:58,974 - optimization.inference - INFO - Number of candidates by RT in frame 412: 168\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,979 - optimization.inference - INFO - Scan time: 16.6364\n", + "2024-12-19 13:15:58,980 - optimization.inference - INFO - Number of candidates by RT in frame 1246: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,985 - optimization.inference - INFO - Scan time: 2.4059\n", + "2024-12-19 13:15:58,986 - optimization.inference - INFO - Number of candidates by RT in frame 417: 186\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:58,997 - optimization.inference - INFO - Scan time: 16.7225\n", + "2024-12-19 13:15:58,998 - optimization.inference - INFO - Number of candidates by RT in frame 1251: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,000 - optimization.inference - INFO - Scan time: 2.4918\n", + "2024-12-19 13:15:59,001 - optimization.inference - INFO - Number of candidates by RT in frame 422: 190\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,011 - optimization.inference - INFO - Scan time: 2.5786\n", + "2024-12-19 13:15:59,012 - optimization.inference - INFO - Number of candidates by RT in frame 427: 195\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,014 - optimization.inference - INFO - Scan time: 16.8085\n", + "2024-12-19 13:15:59,015 - optimization.inference - INFO - Number of candidates by RT in frame 1256: 321\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,025 - optimization.inference - INFO - Scan time: 2.6623\n", + "2024-12-19 13:15:59,026 - optimization.inference - INFO - Number of candidates by RT in frame 432: 201\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,032 - optimization.inference - INFO - Scan time: 16.8931\n", + "2024-12-19 13:15:59,034 - optimization.inference - INFO - Number of candidates by RT in frame 1261: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,036 - optimization.inference - INFO - Scan time: 2.7484\n", + "2024-12-19 13:15:59,037 - optimization.inference - INFO - Number of candidates by RT in frame 437: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,052 - optimization.inference - INFO - Scan time: 16.979\n", + "2024-12-19 13:15:59,054 - optimization.inference - INFO - Number of candidates by RT in frame 1266: 336\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,056 - optimization.inference - INFO - Scan time: 2.834\n", + "2024-12-19 13:15:59,057 - optimization.inference - INFO - Number of candidates by RT in frame 442: 230\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,071 - optimization.inference - INFO - Scan time: 2.92\n", + "2024-12-19 13:15:59,072 - optimization.inference - INFO - Number of candidates by RT in frame 447: 233\n", + "2024-12-19 13:15:59,072 - optimization.inference - INFO - Scan time: 17.065\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,073 - optimization.inference - INFO - Number of candidates by RT in frame 1271: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,085 - optimization.inference - INFO - Scan time: 3.0063\n", + "2024-12-19 13:15:59,086 - optimization.inference - INFO - Number of candidates by RT in frame 452: 227\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,090 - optimization.inference - INFO - Scan time: 17.1514\n", + "2024-12-19 13:15:59,091 - optimization.inference - INFO - Number of candidates by RT in frame 1276: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,098 - optimization.inference - INFO - Scan time: 3.0919\n", + "2024-12-19 13:15:59,099 - optimization.inference - INFO - Number of candidates by RT in frame 457: 226\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,107 - optimization.inference - INFO - Scan time: 17.2374\n", + "2024-12-19 13:15:59,108 - optimization.inference - INFO - Number of candidates by RT in frame 1281: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,114 - optimization.inference - INFO - Scan time: 3.1782\n", + "2024-12-19 13:15:59,115 - optimization.inference - INFO - Number of candidates by RT in frame 462: 225\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,124 - optimization.inference - INFO - Scan time: 17.3239\n", + "2024-12-19 13:15:59,126 - optimization.inference - INFO - Number of candidates by RT in frame 1286: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,129 - optimization.inference - INFO - Scan time: 3.2646\n", + "2024-12-19 13:15:59,130 - optimization.inference - INFO - Number of candidates by RT in frame 467: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,142 - optimization.inference - INFO - Scan time: 3.3507\n", + "2024-12-19 13:15:59,143 - optimization.inference - INFO - Number of candidates by RT in frame 472: 217\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,144 - optimization.inference - INFO - Scan time: 17.4092\n", + "2024-12-19 13:15:59,145 - optimization.inference - INFO - Number of candidates by RT in frame 1291: 330\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,157 - optimization.inference - INFO - Scan time: 3.4363\n", + "2024-12-19 13:15:59,158 - optimization.inference - INFO - Number of candidates by RT in frame 477: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,166 - optimization.inference - INFO - Scan time: 17.4958\n", + "2024-12-19 13:15:59,168 - optimization.inference - INFO - Number of candidates by RT in frame 1296: 335\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,169 - optimization.inference - INFO - Scan time: 3.5223\n", + "2024-12-19 13:15:59,170 - optimization.inference - INFO - Number of candidates by RT in frame 482: 212\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,179 - optimization.inference - INFO - Scan time: 3.6086\n", + "2024-12-19 13:15:59,180 - optimization.inference - INFO - Number of candidates by RT in frame 487: 216\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,187 - optimization.inference - INFO - Scan time: 17.5825\n", + "2024-12-19 13:15:59,188 - optimization.inference - INFO - Number of candidates by RT in frame 1301: 348\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,193 - optimization.inference - INFO - Scan time: 3.6936\n", + "2024-12-19 13:15:59,194 - optimization.inference - INFO - Number of candidates by RT in frame 492: 208\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,205 - optimization.inference - INFO - Scan time: 17.6682\n", + "2024-12-19 13:15:59,205 - optimization.inference - INFO - Scan time: 3.7798\n", + "2024-12-19 13:15:59,206 - optimization.inference - INFO - Number of candidates by RT in frame 1306: 318\n", + "2024-12-19 13:15:59,206 - optimization.inference - INFO - Number of candidates by RT in frame 497: 210\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,217 - optimization.inference - INFO - Scan time: 3.8653\n", + "2024-12-19 13:15:59,218 - optimization.inference - INFO - Number of candidates by RT in frame 502: 205\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,226 - optimization.inference - INFO - Scan time: 17.754\n", + "2024-12-19 13:15:59,228 - optimization.inference - INFO - Number of candidates by RT in frame 1311: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,231 - optimization.inference - INFO - Scan time: 3.95\n", + "2024-12-19 13:15:59,232 - optimization.inference - INFO - Number of candidates by RT in frame 507: 189\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,243 - optimization.inference - INFO - Scan time: 4.0362\n", + "2024-12-19 13:15:59,245 - optimization.inference - INFO - Number of candidates by RT in frame 512: 185\n", + "2024-12-19 13:15:59,245 - optimization.inference - INFO - Scan time: 17.8398\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,246 - optimization.inference - INFO - Number of candidates by RT in frame 1316: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,256 - optimization.inference - INFO - Scan time: 4.1228\n", + "2024-12-19 13:15:59,257 - optimization.inference - INFO - Number of candidates by RT in frame 517: 194\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,266 - optimization.inference - INFO - Scan time: 17.9259\n", + "2024-12-19 13:15:59,267 - optimization.inference - INFO - Number of candidates by RT in frame 1321: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,269 - optimization.inference - INFO - Scan time: 4.2081\n", + "2024-12-19 13:15:59,270 - optimization.inference - INFO - Number of candidates by RT in frame 522: 193\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,286 - optimization.inference - INFO - Scan time: 18.011\n", + "2024-12-19 13:15:59,287 - optimization.inference - INFO - Number of candidates by RT in frame 1326: 330\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,289 - optimization.inference - INFO - Scan time: 4.2938\n", + "2024-12-19 13:15:59,290 - optimization.inference - INFO - Number of candidates by RT in frame 527: 212\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,303 - optimization.inference - INFO - Scan time: 4.3793\n", + "2024-12-19 13:15:59,304 - optimization.inference - INFO - Number of candidates by RT in frame 532: 203\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,306 - optimization.inference - INFO - Scan time: 18.0968\n", + "2024-12-19 13:15:59,307 - optimization.inference - INFO - Number of candidates by RT in frame 1331: 316\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,317 - optimization.inference - INFO - Scan time: 4.4641\n", + "2024-12-19 13:15:59,318 - optimization.inference - INFO - Number of candidates by RT in frame 537: 194\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,323 - optimization.inference - INFO - Scan time: 18.1831\n", + "2024-12-19 13:15:59,325 - optimization.inference - INFO - Number of candidates by RT in frame 1336: 337\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,330 - optimization.inference - INFO - Scan time: 4.5488\n", + "2024-12-19 13:15:59,331 - optimization.inference - INFO - Number of candidates by RT in frame 542: 205\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,343 - optimization.inference - INFO - Scan time: 4.6346\n", + "2024-12-19 13:15:59,344 - optimization.inference - INFO - Number of candidates by RT in frame 547: 216\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,345 - optimization.inference - INFO - Scan time: 18.269\n", + "2024-12-19 13:15:59,346 - optimization.inference - INFO - Number of candidates by RT in frame 1341: 344\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,355 - optimization.inference - INFO - Scan time: 4.7206\n", + "2024-12-19 13:15:59,356 - optimization.inference - INFO - Number of candidates by RT in frame 552: 214\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,368 - optimization.inference - INFO - Scan time: 4.8067\n", + "2024-12-19 13:15:59,368 - optimization.inference - INFO - Scan time: 18.3538\n", + "2024-12-19 13:15:59,369 - optimization.inference - INFO - Number of candidates by RT in frame 557: 216\n", + "2024-12-19 13:15:59,369 - optimization.inference - INFO - Number of candidates by RT in frame 1346: 346\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,379 - optimization.inference - INFO - Scan time: 4.8928\n", + "2024-12-19 13:15:59,380 - optimization.inference - INFO - Number of candidates by RT in frame 562: 232\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,385 - optimization.inference - INFO - Scan time: 18.4401\n", + "2024-12-19 13:15:59,386 - optimization.inference - INFO - Number of candidates by RT in frame 1351: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,391 - optimization.inference - INFO - Scan time: 4.9784\n", + "2024-12-19 13:15:59,392 - optimization.inference - INFO - Number of candidates by RT in frame 567: 217\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,404 - optimization.inference - INFO - Scan time: 18.5257\n", + "2024-12-19 13:15:59,405 - optimization.inference - INFO - Number of candidates by RT in frame 1356: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,409 - optimization.inference - INFO - Scan time: 5.0652\n", + "2024-12-19 13:15:59,410 - optimization.inference - INFO - Number of candidates by RT in frame 572: 234\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,423 - optimization.inference - INFO - Scan time: 5.1514\n", + "2024-12-19 13:15:59,424 - optimization.inference - INFO - Scan time: 18.6108\n", + "2024-12-19 13:15:59,424 - optimization.inference - INFO - Number of candidates by RT in frame 577: 236\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,425 - optimization.inference - INFO - Number of candidates by RT in frame 1361: 335\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,438 - optimization.inference - INFO - Scan time: 5.2374\n", + "2024-12-19 13:15:59,439 - optimization.inference - INFO - Number of candidates by RT in frame 582: 223\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,445 - optimization.inference - INFO - Scan time: 18.6967\n", + "2024-12-19 13:15:59,447 - optimization.inference - INFO - Number of candidates by RT in frame 1366: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,452 - optimization.inference - INFO - Scan time: 5.3241\n", + "2024-12-19 13:15:59,453 - optimization.inference - INFO - Number of candidates by RT in frame 587: 236\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,465 - optimization.inference - INFO - Scan time: 18.7833\n", + "2024-12-19 13:15:59,466 - optimization.inference - INFO - Number of candidates by RT in frame 1371: 296\n", + "2024-12-19 13:15:59,466 - optimization.inference - INFO - Scan time: 5.4095\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,467 - optimization.inference - INFO - Number of candidates by RT in frame 592: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,480 - optimization.inference - INFO - Scan time: 5.4961\n", + "2024-12-19 13:15:59,481 - optimization.inference - INFO - Number of candidates by RT in frame 597: 230\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,482 - optimization.inference - INFO - Scan time: 18.8691\n", + "2024-12-19 13:15:59,483 - optimization.inference - INFO - Number of candidates by RT in frame 1376: 284\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,496 - optimization.inference - INFO - Scan time: 18.9548\n", + "2024-12-19 13:15:59,496 - optimization.inference - INFO - Scan time: 5.5827\n", + "2024-12-19 13:15:59,497 - optimization.inference - INFO - Number of candidates by RT in frame 602: 232\n", + "2024-12-19 13:15:59,498 - optimization.inference - INFO - Number of candidates by RT in frame 1381: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,512 - optimization.inference - INFO - Scan time: 5.6686\n", + "2024-12-19 13:15:59,513 - optimization.inference - INFO - Number of candidates by RT in frame 607: 246\n", + "2024-12-19 13:15:59,514 - optimization.inference - INFO - Scan time: 19.0404\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,515 - optimization.inference - INFO - Number of candidates by RT in frame 1386: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,532 - optimization.inference - INFO - Scan time: 5.7547\n", + "2024-12-19 13:15:59,533 - optimization.inference - INFO - Number of candidates by RT in frame 612: 244\n", + "2024-12-19 13:15:59,534 - optimization.inference - INFO - Scan time: 19.1263\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,535 - optimization.inference - INFO - Number of candidates by RT in frame 1391: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,547 - optimization.inference - INFO - Scan time: 5.8403\n", + "2024-12-19 13:15:59,548 - optimization.inference - INFO - Number of candidates by RT in frame 617: 243\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,554 - optimization.inference - INFO - Scan time: 19.2115\n", + "2024-12-19 13:15:59,555 - optimization.inference - INFO - Number of candidates by RT in frame 1396: 340\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,561 - optimization.inference - INFO - Scan time: 5.9266\n", + "2024-12-19 13:15:59,562 - optimization.inference - INFO - Number of candidates by RT in frame 622: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,572 - optimization.inference - INFO - Scan time: 19.2976\n", + "2024-12-19 13:15:59,574 - optimization.inference - INFO - Number of candidates by RT in frame 1401: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,575 - optimization.inference - INFO - Scan time: 6.0133\n", + "2024-12-19 13:15:59,576 - optimization.inference - INFO - Number of candidates by RT in frame 627: 234\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,591 - optimization.inference - INFO - Scan time: 19.3838\n", + "2024-12-19 13:15:59,591 - optimization.inference - INFO - Scan time: 6.0979\n", + "2024-12-19 13:15:59,592 - optimization.inference - INFO - Number of candidates by RT in frame 632: 246\n", + "2024-12-19 13:15:59,592 - optimization.inference - INFO - Number of candidates by RT in frame 1406: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,604 - optimization.inference - INFO - Scan time: 6.184\n", + "2024-12-19 13:15:59,605 - optimization.inference - INFO - Number of candidates by RT in frame 637: 230\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,607 - optimization.inference - INFO - Scan time: 19.4701\n", + "2024-12-19 13:15:59,608 - optimization.inference - INFO - Number of candidates by RT in frame 1411: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,620 - optimization.inference - INFO - Scan time: 6.2708\n", + "2024-12-19 13:15:59,621 - optimization.inference - INFO - Number of candidates by RT in frame 642: 257\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,627 - optimization.inference - INFO - Scan time: 19.5565\n", + "2024-12-19 13:15:59,628 - optimization.inference - INFO - Number of candidates by RT in frame 1416: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,633 - optimization.inference - INFO - Scan time: 6.3575\n", + "2024-12-19 13:15:59,634 - optimization.inference - INFO - Number of candidates by RT in frame 647: 249\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,643 - optimization.inference - INFO - Scan time: 19.6428\n", + "2024-12-19 13:15:59,644 - optimization.inference - INFO - Number of candidates by RT in frame 1421: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,649 - optimization.inference - INFO - Scan time: 6.4445\n", + "2024-12-19 13:15:59,650 - optimization.inference - INFO - Number of candidates by RT in frame 652: 245\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,660 - optimization.inference - INFO - Scan time: 19.7281\n", + "2024-12-19 13:15:59,661 - optimization.inference - INFO - Number of candidates by RT in frame 1426: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,666 - optimization.inference - INFO - Scan time: 6.5309\n", + "2024-12-19 13:15:59,667 - optimization.inference - INFO - Number of candidates by RT in frame 657: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,678 - optimization.inference - INFO - Scan time: 19.8132\n", + "2024-12-19 13:15:59,680 - optimization.inference - INFO - Number of candidates by RT in frame 1431: 295\n", + "2024-12-19 13:15:59,680 - optimization.inference - INFO - Scan time: 6.6169\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,681 - optimization.inference - INFO - Number of candidates by RT in frame 662: 237\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,695 - optimization.inference - INFO - Scan time: 6.7021\n", + "2024-12-19 13:15:59,696 - optimization.inference - INFO - Number of candidates by RT in frame 667: 241\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,698 - optimization.inference - INFO - Scan time: 19.8984\n", + "2024-12-19 13:15:59,699 - optimization.inference - INFO - Number of candidates by RT in frame 1436: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,707 - optimization.inference - INFO - Scan time: 6.7878\n", + "2024-12-19 13:15:59,708 - optimization.inference - INFO - Number of candidates by RT in frame 672: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,717 - optimization.inference - INFO - Scan time: 19.9843\n", + "2024-12-19 13:15:59,719 - optimization.inference - INFO - Number of candidates by RT in frame 1441: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,723 - optimization.inference - INFO - Scan time: 6.8742\n", + "2024-12-19 13:15:59,724 - optimization.inference - INFO - Number of candidates by RT in frame 677: 247\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,736 - optimization.inference - INFO - Scan time: 20.0694\n", + "2024-12-19 13:15:59,737 - optimization.inference - INFO - Number of candidates by RT in frame 1446: 295\n", + "2024-12-19 13:15:59,737 - optimization.inference - INFO - Scan time: 6.9597\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,738 - optimization.inference - INFO - Number of candidates by RT in frame 682: 228\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,750 - optimization.inference - INFO - Scan time: 7.0465\n", + "2024-12-19 13:15:59,752 - optimization.inference - INFO - Number of candidates by RT in frame 687: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,755 - optimization.inference - INFO - Scan time: 20.1555\n", + "2024-12-19 13:15:59,756 - optimization.inference - INFO - Number of candidates by RT in frame 1451: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,770 - optimization.inference - INFO - Scan time: 7.132\n", + "2024-12-19 13:15:59,771 - optimization.inference - INFO - Number of candidates by RT in frame 692: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,774 - optimization.inference - INFO - Scan time: 20.2416\n", + "2024-12-19 13:15:59,775 - optimization.inference - INFO - Number of candidates by RT in frame 1456: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,785 - optimization.inference - INFO - Scan time: 7.2164\n", + "2024-12-19 13:15:59,786 - optimization.inference - INFO - Number of candidates by RT in frame 697: 245\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,792 - optimization.inference - INFO - Scan time: 20.3264\n", + "2024-12-19 13:15:59,794 - optimization.inference - INFO - Number of candidates by RT in frame 1461: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,800 - optimization.inference - INFO - Scan time: 7.3022\n", + "2024-12-19 13:15:59,801 - optimization.inference - INFO - Number of candidates by RT in frame 702: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,814 - optimization.inference - INFO - Scan time: 20.4117\n", + "2024-12-19 13:15:59,815 - optimization.inference - INFO - Number of candidates by RT in frame 1466: 317\n", + "2024-12-19 13:15:59,815 - optimization.inference - INFO - Scan time: 7.3874\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,816 - optimization.inference - INFO - Number of candidates by RT in frame 707: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,829 - optimization.inference - INFO - Scan time: 7.4739\n", + "2024-12-19 13:15:59,830 - optimization.inference - INFO - Number of candidates by RT in frame 712: 251\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,834 - optimization.inference - INFO - Scan time: 20.4973\n", + "2024-12-19 13:15:59,835 - optimization.inference - INFO - Number of candidates by RT in frame 1471: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,844 - optimization.inference - INFO - Scan time: 7.5602\n", + "2024-12-19 13:15:59,846 - optimization.inference - INFO - Number of candidates by RT in frame 717: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,853 - optimization.inference - INFO - Scan time: 20.5837\n", + "2024-12-19 13:15:59,854 - optimization.inference - INFO - Number of candidates by RT in frame 1476: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,858 - optimization.inference - INFO - Scan time: 7.6459\n", + "2024-12-19 13:15:59,859 - optimization.inference - INFO - Number of candidates by RT in frame 722: 252\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,873 - optimization.inference - INFO - Scan time: 7.7317\n", + "2024-12-19 13:15:59,874 - optimization.inference - INFO - Number of candidates by RT in frame 727: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,876 - optimization.inference - INFO - Scan time: 20.6684\n", + "2024-12-19 13:15:59,877 - optimization.inference - INFO - Number of candidates by RT in frame 1481: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,888 - optimization.inference - INFO - Scan time: 7.8178\n", + "2024-12-19 13:15:59,889 - optimization.inference - INFO - Number of candidates by RT in frame 732: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,892 - optimization.inference - INFO - Scan time: 20.7551\n", + "2024-12-19 13:15:59,893 - optimization.inference - INFO - Number of candidates by RT in frame 1486: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,905 - optimization.inference - INFO - Scan time: 7.9033\n", + "2024-12-19 13:15:59,906 - optimization.inference - INFO - Number of candidates by RT in frame 737: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,910 - optimization.inference - INFO - Scan time: 20.8411\n", + "2024-12-19 13:15:59,911 - optimization.inference - INFO - Number of candidates by RT in frame 1491: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,920 - optimization.inference - INFO - Scan time: 7.9885\n", + "2024-12-19 13:15:59,921 - optimization.inference - INFO - Number of candidates by RT in frame 742: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,927 - optimization.inference - INFO - Scan time: 20.9263\n", + "2024-12-19 13:15:59,928 - optimization.inference - INFO - Number of candidates by RT in frame 1496: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,936 - optimization.inference - INFO - Scan time: 8.0743\n", + "2024-12-19 13:15:59,937 - optimization.inference - INFO - Number of candidates by RT in frame 747: 256\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,949 - optimization.inference - INFO - Scan time: 21.0127\n", + "2024-12-19 13:15:59,950 - optimization.inference - INFO - Number of candidates by RT in frame 1501: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,954 - optimization.inference - INFO - Scan time: 8.1594\n", + "2024-12-19 13:15:59,955 - optimization.inference - INFO - Number of candidates by RT in frame 752: 254\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,968 - optimization.inference - INFO - Scan time: 21.098\n", + "2024-12-19 13:15:59,970 - optimization.inference - INFO - Number of candidates by RT in frame 1506: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,982 - optimization.inference - INFO - Scan time: 8.2455\n", + "2024-12-19 13:15:59,983 - optimization.inference - INFO - Number of candidates by RT in frame 757: 251\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,990 - optimization.inference - INFO - Scan time: 21.1839\n", + "2024-12-19 13:15:59,991 - optimization.inference - INFO - Number of candidates by RT in frame 1511: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:15:59,997 - optimization.inference - INFO - Scan time: 8.3313\n", + "2024-12-19 13:15:59,998 - optimization.inference - INFO - Number of candidates by RT in frame 762: 247\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,011 - optimization.inference - INFO - Scan time: 21.2692\n", + "2024-12-19 13:16:00,012 - optimization.inference - INFO - Number of candidates by RT in frame 1516: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,015 - optimization.inference - INFO - Scan time: 8.4168\n", + "2024-12-19 13:16:00,016 - optimization.inference - INFO - Number of candidates by RT in frame 767: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,032 - optimization.inference - INFO - Scan time: 21.3558\n", + "2024-12-19 13:16:00,032 - optimization.inference - INFO - Scan time: 8.5022\n", + "2024-12-19 13:16:00,033 - optimization.inference - INFO - Number of candidates by RT in frame 1521: 302\n", + "2024-12-19 13:16:00,033 - optimization.inference - INFO - Number of candidates by RT in frame 772: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,051 - optimization.inference - INFO - Scan time: 8.5876\n", + "2024-12-19 13:16:00,052 - optimization.inference - INFO - Scan time: 21.4407\n", + "2024-12-19 13:16:00,053 - optimization.inference - INFO - Number of candidates by RT in frame 777: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,054 - optimization.inference - INFO - Number of candidates by RT in frame 1526: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,070 - optimization.inference - INFO - Scan time: 8.6736\n", + "2024-12-19 13:16:00,071 - optimization.inference - INFO - Number of candidates by RT in frame 782: 270\n", + "2024-12-19 13:16:00,072 - optimization.inference - INFO - Scan time: 21.5252\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,073 - optimization.inference - INFO - Number of candidates by RT in frame 1531: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,087 - optimization.inference - INFO - Scan time: 21.6121\n", + "2024-12-19 13:16:00,089 - optimization.inference - INFO - Number of candidates by RT in frame 1536: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,090 - optimization.inference - INFO - Scan time: 8.759\n", + "2024-12-19 13:16:00,091 - optimization.inference - INFO - Number of candidates by RT in frame 787: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,107 - optimization.inference - INFO - Scan time: 21.6974\n", + "2024-12-19 13:16:00,108 - optimization.inference - INFO - Number of candidates by RT in frame 1541: 310\n", + "2024-12-19 13:16:00,109 - optimization.inference - INFO - Scan time: 8.8452\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,110 - optimization.inference - INFO - Number of candidates by RT in frame 792: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,126 - optimization.inference - INFO - Scan time: 21.7826\n", + "2024-12-19 13:16:00,127 - optimization.inference - INFO - Number of candidates by RT in frame 1546: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,129 - optimization.inference - INFO - Scan time: 8.9306\n", + "2024-12-19 13:16:00,130 - optimization.inference - INFO - Number of candidates by RT in frame 797: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,147 - optimization.inference - INFO - Scan time: 21.8685\n", + "2024-12-19 13:16:00,148 - optimization.inference - INFO - Number of candidates by RT in frame 1551: 327\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,150 - optimization.inference - INFO - Scan time: 9.0152\n", + "2024-12-19 13:16:00,151 - optimization.inference - INFO - Number of candidates by RT in frame 802: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,165 - optimization.inference - INFO - Scan time: 9.101\n", + "2024-12-19 13:16:00,166 - optimization.inference - INFO - Number of candidates by RT in frame 807: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,170 - optimization.inference - INFO - Scan time: 21.9547\n", + "2024-12-19 13:16:00,171 - optimization.inference - INFO - Number of candidates by RT in frame 1556: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,182 - optimization.inference - INFO - Scan time: 9.1871\n", + "2024-12-19 13:16:00,184 - optimization.inference - INFO - Number of candidates by RT in frame 812: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,194 - optimization.inference - INFO - Scan time: 22.0405\n", + "2024-12-19 13:16:00,195 - optimization.inference - INFO - Number of candidates by RT in frame 1561: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,200 - optimization.inference - INFO - Scan time: 9.2721\n", + "2024-12-19 13:16:00,201 - optimization.inference - INFO - Number of candidates by RT in frame 817: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,218 - optimization.inference - INFO - Scan time: 9.358\n", + "2024-12-19 13:16:00,219 - optimization.inference - INFO - Scan time: 22.1266\n", + "2024-12-19 13:16:00,220 - optimization.inference - INFO - Number of candidates by RT in frame 822: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,221 - optimization.inference - INFO - Number of candidates by RT in frame 1566: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,238 - optimization.inference - INFO - Scan time: 9.4446\n", + "2024-12-19 13:16:00,239 - optimization.inference - INFO - Number of candidates by RT in frame 827: 294\n", + "2024-12-19 13:16:00,240 - optimization.inference - INFO - Scan time: 22.2114\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,241 - optimization.inference - INFO - Number of candidates by RT in frame 1571: 314\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,256 - optimization.inference - INFO - Scan time: 9.5302\n", + "2024-12-19 13:16:00,257 - optimization.inference - INFO - Number of candidates by RT in frame 832: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,259 - optimization.inference - INFO - Scan time: 22.2967\n", + "2024-12-19 13:16:00,260 - optimization.inference - INFO - Number of candidates by RT in frame 1576: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,273 - optimization.inference - INFO - Scan time: 9.6159\n", + "2024-12-19 13:16:00,274 - optimization.inference - INFO - Number of candidates by RT in frame 837: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,282 - optimization.inference - INFO - Scan time: 22.3827\n", + "2024-12-19 13:16:00,283 - optimization.inference - INFO - Number of candidates by RT in frame 1581: 317\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,289 - optimization.inference - INFO - Scan time: 9.7017\n", + "2024-12-19 13:16:00,290 - optimization.inference - INFO - Number of candidates by RT in frame 842: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,306 - optimization.inference - INFO - Scan time: 9.7878\n", + "2024-12-19 13:16:00,307 - optimization.inference - INFO - Number of candidates by RT in frame 847: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,312 - optimization.inference - INFO - Scan time: 22.4686\n", + "2024-12-19 13:16:00,313 - optimization.inference - INFO - Number of candidates by RT in frame 1586: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,323 - optimization.inference - INFO - Scan time: 9.8733\n", + "2024-12-19 13:16:00,324 - optimization.inference - INFO - Number of candidates by RT in frame 852: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,336 - optimization.inference - INFO - Scan time: 22.5547\n", + "2024-12-19 13:16:00,337 - optimization.inference - INFO - Number of candidates by RT in frame 1591: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,341 - optimization.inference - INFO - Scan time: 9.9583\n", + "2024-12-19 13:16:00,342 - optimization.inference - INFO - Number of candidates by RT in frame 857: 284\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,354 - optimization.inference - INFO - Scan time: 22.6393\n", + "2024-12-19 13:16:00,355 - optimization.inference - INFO - Number of candidates by RT in frame 1596: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,357 - optimization.inference - INFO - Scan time: 10.0446\n", + "2024-12-19 13:16:00,358 - optimization.inference - INFO - Number of candidates by RT in frame 862: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,372 - optimization.inference - INFO - Scan time: 22.7249\n", + "2024-12-19 13:16:00,372 - optimization.inference - INFO - Scan time: 10.1298\n", + "2024-12-19 13:16:00,373 - optimization.inference - INFO - Number of candidates by RT in frame 867: 268\n", + "2024-12-19 13:16:00,373 - optimization.inference - INFO - Number of candidates by RT in frame 1601: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,387 - optimization.inference - INFO - Scan time: 10.2151\n", + "2024-12-19 13:16:00,388 - optimization.inference - INFO - Number of candidates by RT in frame 872: 263\n", + "2024-12-19 13:16:00,389 - optimization.inference - INFO - Scan time: 22.8103\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,390 - optimization.inference - INFO - Number of candidates by RT in frame 1606: 283\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,404 - optimization.inference - INFO - Scan time: 10.3006\n", + "2024-12-19 13:16:00,406 - optimization.inference - INFO - Number of candidates by RT in frame 877: 266\n", + "2024-12-19 13:16:00,406 - optimization.inference - INFO - Scan time: 22.8971\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,407 - optimization.inference - INFO - Number of candidates by RT in frame 1611: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,419 - optimization.inference - INFO - Scan time: 10.3857\n", + "2024-12-19 13:16:00,421 - optimization.inference - INFO - Number of candidates by RT in frame 882: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,425 - optimization.inference - INFO - Scan time: 22.9835\n", + "2024-12-19 13:16:00,426 - optimization.inference - INFO - Number of candidates by RT in frame 1616: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,437 - optimization.inference - INFO - Scan time: 10.4713\n", + "2024-12-19 13:16:00,438 - optimization.inference - INFO - Number of candidates by RT in frame 887: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,442 - optimization.inference - INFO - Scan time: 23.0695\n", + "2024-12-19 13:16:00,443 - optimization.inference - INFO - Number of candidates by RT in frame 1621: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,452 - optimization.inference - INFO - Scan time: 10.5576\n", + "2024-12-19 13:16:00,454 - optimization.inference - INFO - Number of candidates by RT in frame 892: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,460 - optimization.inference - INFO - Scan time: 23.1551\n", + "2024-12-19 13:16:00,461 - optimization.inference - INFO - Number of candidates by RT in frame 1626: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,468 - optimization.inference - INFO - Scan time: 10.6432\n", + "2024-12-19 13:16:00,470 - optimization.inference - INFO - Number of candidates by RT in frame 897: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,476 - optimization.inference - INFO - Scan time: 23.2409\n", + "2024-12-19 13:16:00,477 - optimization.inference - INFO - Number of candidates by RT in frame 1631: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,486 - optimization.inference - INFO - Scan time: 10.7294\n", + "2024-12-19 13:16:00,487 - optimization.inference - INFO - Number of candidates by RT in frame 902: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,496 - optimization.inference - INFO - Scan time: 23.3263\n", + "2024-12-19 13:16:00,497 - optimization.inference - INFO - Number of candidates by RT in frame 1636: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,504 - optimization.inference - INFO - Scan time: 10.8163\n", + "2024-12-19 13:16:00,505 - optimization.inference - INFO - Number of candidates by RT in frame 907: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,518 - optimization.inference - INFO - Scan time: 23.4119\n", + "2024-12-19 13:16:00,519 - optimization.inference - INFO - Number of candidates by RT in frame 1641: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,521 - optimization.inference - INFO - Scan time: 10.9018\n", + "2024-12-19 13:16:00,522 - optimization.inference - INFO - Number of candidates by RT in frame 912: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,538 - optimization.inference - INFO - Scan time: 10.9869\n", + "2024-12-19 13:16:00,539 - optimization.inference - INFO - Number of candidates by RT in frame 917: 283\n", + "2024-12-19 13:16:00,539 - optimization.inference - INFO - Scan time: 23.4969\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,540 - optimization.inference - INFO - Number of candidates by RT in frame 1646: 294\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,555 - optimization.inference - INFO - Scan time: 11.0732\n", + "2024-12-19 13:16:00,557 - optimization.inference - INFO - Number of candidates by RT in frame 922: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,558 - optimization.inference - INFO - Scan time: 23.5819\n", + "2024-12-19 13:16:00,559 - optimization.inference - INFO - Number of candidates by RT in frame 1651: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,572 - optimization.inference - INFO - Scan time: 11.1592\n", + "2024-12-19 13:16:00,574 - optimization.inference - INFO - Number of candidates by RT in frame 927: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,579 - optimization.inference - INFO - Scan time: 23.668\n", + "2024-12-19 13:16:00,580 - optimization.inference - INFO - Number of candidates by RT in frame 1656: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,595 - optimization.inference - INFO - Scan time: 11.2448\n", + "2024-12-19 13:16:00,596 - optimization.inference - INFO - Number of candidates by RT in frame 932: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,598 - optimization.inference - INFO - Scan time: 23.7537\n", + "2024-12-19 13:16:00,599 - optimization.inference - INFO - Number of candidates by RT in frame 1661: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,613 - optimization.inference - INFO - Scan time: 11.3318\n", + "2024-12-19 13:16:00,614 - optimization.inference - INFO - Number of candidates by RT in frame 937: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,617 - optimization.inference - INFO - Scan time: 23.8401\n", + "2024-12-19 13:16:00,618 - optimization.inference - INFO - Number of candidates by RT in frame 1666: 245\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,631 - optimization.inference - INFO - Scan time: 11.418\n", + "2024-12-19 13:16:00,632 - optimization.inference - INFO - Number of candidates by RT in frame 942: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,635 - optimization.inference - INFO - Scan time: 23.9254\n", + "2024-12-19 13:16:00,636 - optimization.inference - INFO - Number of candidates by RT in frame 1671: 258\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,646 - optimization.inference - INFO - Scan time: 11.5046\n", + "2024-12-19 13:16:00,648 - optimization.inference - INFO - Number of candidates by RT in frame 947: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,651 - optimization.inference - INFO - Scan time: 24.0107\n", + "2024-12-19 13:16:00,652 - optimization.inference - INFO - Number of candidates by RT in frame 1676: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,665 - optimization.inference - INFO - Scan time: 11.5894\n", + "2024-12-19 13:16:00,666 - optimization.inference - INFO - Number of candidates by RT in frame 952: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,668 - optimization.inference - INFO - Scan time: 24.0964\n", + "2024-12-19 13:16:00,669 - optimization.inference - INFO - Number of candidates by RT in frame 1681: 240\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,681 - optimization.inference - INFO - Scan time: 11.6748\n", + "2024-12-19 13:16:00,683 - optimization.inference - INFO - Number of candidates by RT in frame 957: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,685 - optimization.inference - INFO - Scan time: 24.1821\n", + "2024-12-19 13:16:00,686 - optimization.inference - INFO - Number of candidates by RT in frame 1686: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,699 - optimization.inference - INFO - Scan time: 11.7612\n", + "2024-12-19 13:16:00,700 - optimization.inference - INFO - Number of candidates by RT in frame 962: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,704 - optimization.inference - INFO - Scan time: 24.2679\n", + "2024-12-19 13:16:00,706 - optimization.inference - INFO - Number of candidates by RT in frame 1691: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,714 - optimization.inference - INFO - Scan time: 11.8464\n", + "2024-12-19 13:16:00,715 - optimization.inference - INFO - Number of candidates by RT in frame 967: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,726 - optimization.inference - INFO - Scan time: 24.3539\n", + "2024-12-19 13:16:00,727 - optimization.inference - INFO - Number of candidates by RT in frame 1696: 259\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,733 - optimization.inference - INFO - Scan time: 11.9324\n", + "2024-12-19 13:16:00,734 - optimization.inference - INFO - Number of candidates by RT in frame 972: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,745 - optimization.inference - INFO - Scan time: 24.4393\n", + "2024-12-19 13:16:00,746 - optimization.inference - INFO - Number of candidates by RT in frame 1701: 243\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,749 - optimization.inference - INFO - Scan time: 12.0184\n", + "2024-12-19 13:16:00,750 - optimization.inference - INFO - Number of candidates by RT in frame 977: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,764 - optimization.inference - INFO - Scan time: 24.5255\n", + "2024-12-19 13:16:00,765 - optimization.inference - INFO - Number of candidates by RT in frame 1706: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,770 - optimization.inference - INFO - Scan time: 12.1054\n", + "2024-12-19 13:16:00,771 - optimization.inference - INFO - Number of candidates by RT in frame 982: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,782 - optimization.inference - INFO - Scan time: 24.6121\n", + "2024-12-19 13:16:00,783 - optimization.inference - INFO - Number of candidates by RT in frame 1711: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,788 - optimization.inference - INFO - Scan time: 12.1917\n", + "2024-12-19 13:16:00,789 - optimization.inference - INFO - Number of candidates by RT in frame 987: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,800 - optimization.inference - INFO - Scan time: 24.6978\n", + "2024-12-19 13:16:00,802 - optimization.inference - INFO - Number of candidates by RT in frame 1716: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,808 - optimization.inference - INFO - Scan time: 12.2768\n", + "2024-12-19 13:16:00,809 - optimization.inference - INFO - Number of candidates by RT in frame 992: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,818 - optimization.inference - INFO - Scan time: 24.7835\n", + "2024-12-19 13:16:00,820 - optimization.inference - INFO - Number of candidates by RT in frame 1721: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,828 - optimization.inference - INFO - Scan time: 12.3615\n", + "2024-12-19 13:16:00,829 - optimization.inference - INFO - Number of candidates by RT in frame 997: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,840 - optimization.inference - INFO - Scan time: 24.8685\n", + "2024-12-19 13:16:00,841 - optimization.inference - INFO - Number of candidates by RT in frame 1726: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,858 - optimization.inference - INFO - Scan time: 12.4471\n", + "2024-12-19 13:16:00,859 - optimization.inference - INFO - Number of candidates by RT in frame 1002: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,860 - optimization.inference - INFO - Scan time: 24.9535\n", + "2024-12-19 13:16:00,861 - optimization.inference - INFO - Number of candidates by RT in frame 1731: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,876 - optimization.inference - INFO - Scan time: 12.5332\n", + "2024-12-19 13:16:00,877 - optimization.inference - INFO - Scan time: 25.0385\n", + "2024-12-19 13:16:00,878 - optimization.inference - INFO - Number of candidates by RT in frame 1007: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,878 - optimization.inference - INFO - Number of candidates by RT in frame 1736: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,895 - optimization.inference - INFO - Scan time: 25.1242\n", + "2024-12-19 13:16:00,895 - optimization.inference - INFO - Scan time: 12.619\n", + "2024-12-19 13:16:00,896 - optimization.inference - INFO - Number of candidates by RT in frame 1012: 307\n", + "2024-12-19 13:16:00,896 - optimization.inference - INFO - Number of candidates by RT in frame 1741: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,914 - optimization.inference - INFO - Scan time: 12.7045\n", + "2024-12-19 13:16:00,915 - optimization.inference - INFO - Number of candidates by RT in frame 1017: 298\n", + "2024-12-19 13:16:00,915 - optimization.inference - INFO - Scan time: 25.21\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,916 - optimization.inference - INFO - Number of candidates by RT in frame 1746: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,932 - optimization.inference - INFO - Scan time: 12.7899\n", + "2024-12-19 13:16:00,933 - optimization.inference - INFO - Number of candidates by RT in frame 1022: 318\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,937 - optimization.inference - INFO - Scan time: 25.2969\n", + "2024-12-19 13:16:00,938 - optimization.inference - INFO - Number of candidates by RT in frame 1751: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,953 - optimization.inference - INFO - Scan time: 12.8762\n", + "2024-12-19 13:16:00,954 - optimization.inference - INFO - Number of candidates by RT in frame 1027: 335\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,957 - optimization.inference - INFO - Scan time: 25.3828\n", + "2024-12-19 13:16:00,958 - optimization.inference - INFO - Number of candidates by RT in frame 1756: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,973 - optimization.inference - INFO - Scan time: 12.9623\n", + "2024-12-19 13:16:00,974 - optimization.inference - INFO - Number of candidates by RT in frame 1032: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,979 - optimization.inference - INFO - Scan time: 25.4687\n", + "2024-12-19 13:16:00,980 - optimization.inference - INFO - Number of candidates by RT in frame 1761: 283\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:00,996 - optimization.inference - INFO - Scan time: 13.0477\n", + "2024-12-19 13:16:00,998 - optimization.inference - INFO - Number of candidates by RT in frame 1037: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,000 - optimization.inference - INFO - Scan time: 25.5539\n", + "2024-12-19 13:16:01,001 - optimization.inference - INFO - Number of candidates by RT in frame 1766: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,017 - optimization.inference - INFO - Scan time: 13.1337\n", + "2024-12-19 13:16:01,018 - optimization.inference - INFO - Number of candidates by RT in frame 1042: 321\n", + "2024-12-19 13:16:01,019 - optimization.inference - INFO - Scan time: 25.6399\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,020 - optimization.inference - INFO - Number of candidates by RT in frame 1771: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,032 - optimization.inference - INFO - Scan time: 13.2198\n", + "2024-12-19 13:16:01,033 - optimization.inference - INFO - Number of candidates by RT in frame 1047: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,043 - optimization.inference - INFO - Scan time: 25.7256\n", + "2024-12-19 13:16:01,044 - optimization.inference - INFO - Number of candidates by RT in frame 1776: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,050 - optimization.inference - INFO - Scan time: 13.3067\n", + "2024-12-19 13:16:01,051 - optimization.inference - INFO - Number of candidates by RT in frame 1052: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,066 - optimization.inference - INFO - Scan time: 25.812\n", + "2024-12-19 13:16:01,066 - optimization.inference - INFO - Scan time: 13.3928\n", + "2024-12-19 13:16:01,067 - optimization.inference - INFO - Number of candidates by RT in frame 1781: 279\n", + "2024-12-19 13:16:01,067 - optimization.inference - INFO - Number of candidates by RT in frame 1057: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,080 - optimization.inference - INFO - Scan time: 13.4796\n", + "2024-12-19 13:16:01,082 - optimization.inference - INFO - Number of candidates by RT in frame 1062: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,085 - optimization.inference - INFO - Scan time: 25.8976\n", + "2024-12-19 13:16:01,086 - optimization.inference - INFO - Number of candidates by RT in frame 1786: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,098 - optimization.inference - INFO - Scan time: 13.5651\n", + "2024-12-19 13:16:01,099 - optimization.inference - INFO - Number of candidates by RT in frame 1067: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,102 - optimization.inference - INFO - Scan time: 25.9838\n", + "2024-12-19 13:16:01,103 - optimization.inference - INFO - Number of candidates by RT in frame 1791: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,117 - optimization.inference - INFO - Scan time: 13.6514\n", + "2024-12-19 13:16:01,118 - optimization.inference - INFO - Number of candidates by RT in frame 1072: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,122 - optimization.inference - INFO - Scan time: 26.0704\n", + "2024-12-19 13:16:01,123 - optimization.inference - INFO - Number of candidates by RT in frame 1796: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,137 - optimization.inference - INFO - Scan time: 13.7376\n", + "2024-12-19 13:16:01,138 - optimization.inference - INFO - Number of candidates by RT in frame 1077: 328\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,143 - optimization.inference - INFO - Scan time: 26.1567\n", + "2024-12-19 13:16:01,144 - optimization.inference - INFO - Number of candidates by RT in frame 1801: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,154 - optimization.inference - INFO - Scan time: 13.8239\n", + "2024-12-19 13:16:01,155 - optimization.inference - INFO - Number of candidates by RT in frame 1082: 319\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,166 - optimization.inference - INFO - Scan time: 26.2425\n", + "2024-12-19 13:16:01,167 - optimization.inference - INFO - Number of candidates by RT in frame 1806: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,175 - optimization.inference - INFO - Scan time: 13.9094\n", + "2024-12-19 13:16:01,176 - optimization.inference - INFO - Number of candidates by RT in frame 1087: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,188 - optimization.inference - INFO - Scan time: 26.3288\n", + "2024-12-19 13:16:01,189 - optimization.inference - INFO - Number of candidates by RT in frame 1811: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,195 - optimization.inference - INFO - Scan time: 13.9945\n", + "2024-12-19 13:16:01,196 - optimization.inference - INFO - Number of candidates by RT in frame 1092: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,212 - optimization.inference - INFO - Scan time: 26.4146\n", + "2024-12-19 13:16:01,213 - optimization.inference - INFO - Number of candidates by RT in frame 1816: 312\n", + "2024-12-19 13:16:01,213 - optimization.inference - INFO - Scan time: 14.0808\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,214 - optimization.inference - INFO - Number of candidates by RT in frame 1097: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,228 - optimization.inference - INFO - Scan time: 14.1667\n", + "2024-12-19 13:16:01,229 - optimization.inference - INFO - Number of candidates by RT in frame 1102: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,234 - optimization.inference - INFO - Scan time: 26.5003\n", + "2024-12-19 13:16:01,236 - optimization.inference - INFO - Number of candidates by RT in frame 1821: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,246 - optimization.inference - INFO - Scan time: 14.2526\n", + "2024-12-19 13:16:01,247 - optimization.inference - INFO - Number of candidates by RT in frame 1107: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,257 - optimization.inference - INFO - Scan time: 26.5856\n", + "2024-12-19 13:16:01,259 - optimization.inference - INFO - Number of candidates by RT in frame 1826: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,263 - optimization.inference - INFO - Scan time: 14.3382\n", + "2024-12-19 13:16:01,264 - optimization.inference - INFO - Number of candidates by RT in frame 1112: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,280 - optimization.inference - INFO - Scan time: 26.6718\n", + "2024-12-19 13:16:01,281 - optimization.inference - INFO - Number of candidates by RT in frame 1831: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,282 - optimization.inference - INFO - Scan time: 14.4242\n", + "2024-12-19 13:16:01,283 - optimization.inference - INFO - Number of candidates by RT in frame 1117: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,300 - optimization.inference - INFO - Scan time: 14.5098\n", + "2024-12-19 13:16:01,300 - optimization.inference - INFO - Scan time: 26.7578\n", + "2024-12-19 13:16:01,301 - optimization.inference - INFO - Number of candidates by RT in frame 1122: 298\n", + "2024-12-19 13:16:01,301 - optimization.inference - INFO - Number of candidates by RT in frame 1836: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,318 - optimization.inference - INFO - Scan time: 26.8435\n", + "2024-12-19 13:16:01,319 - optimization.inference - INFO - Number of candidates by RT in frame 1841: 262\n", + "2024-12-19 13:16:01,319 - optimization.inference - INFO - Scan time: 14.595\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,320 - optimization.inference - INFO - Number of candidates by RT in frame 1127: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,336 - optimization.inference - INFO - Scan time: 26.9293\n", + "2024-12-19 13:16:01,337 - optimization.inference - INFO - Number of candidates by RT in frame 1846: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,338 - optimization.inference - INFO - Scan time: 14.6812\n", + "2024-12-19 13:16:01,339 - optimization.inference - INFO - Number of candidates by RT in frame 1132: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,356 - optimization.inference - INFO - Scan time: 27.0155\n", + "2024-12-19 13:16:01,358 - optimization.inference - INFO - Number of candidates by RT in frame 1851: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,359 - optimization.inference - INFO - Scan time: 14.767\n", + "2024-12-19 13:16:01,360 - optimization.inference - INFO - Number of candidates by RT in frame 1137: 327\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,376 - optimization.inference - INFO - Scan time: 27.1014\n", + "2024-12-19 13:16:01,377 - optimization.inference - INFO - Number of candidates by RT in frame 1856: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,378 - optimization.inference - INFO - Scan time: 14.8527\n", + "2024-12-19 13:16:01,379 - optimization.inference - INFO - Number of candidates by RT in frame 1142: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,399 - optimization.inference - INFO - Scan time: 27.1864\n", + "2024-12-19 13:16:01,400 - optimization.inference - INFO - Scan time: 14.9379\n", + "2024-12-19 13:16:01,400 - optimization.inference - INFO - Number of candidates by RT in frame 1861: 298\n", + "2024-12-19 13:16:01,401 - optimization.inference - INFO - Number of candidates by RT in frame 1147: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,420 - optimization.inference - INFO - Scan time: 15.0243\n", + "2024-12-19 13:16:01,421 - optimization.inference - INFO - Scan time: 27.272\n", + "2024-12-19 13:16:01,421 - optimization.inference - INFO - Number of candidates by RT in frame 1152: 320\n", + "2024-12-19 13:16:01,422 - optimization.inference - INFO - Number of candidates by RT in frame 1866: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,440 - optimization.inference - INFO - Scan time: 27.3574\n", + "2024-12-19 13:16:01,440 - optimization.inference - INFO - Scan time: 15.1095\n", + "2024-12-19 13:16:01,441 - optimization.inference - INFO - Number of candidates by RT in frame 1871: 270\n", + "2024-12-19 13:16:01,441 - optimization.inference - INFO - Number of candidates by RT in frame 1157: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,456 - optimization.inference - INFO - Scan time: 15.1965\n", + "2024-12-19 13:16:01,457 - optimization.inference - INFO - Number of candidates by RT in frame 1162: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,461 - optimization.inference - INFO - Scan time: 27.4452\n", + "2024-12-19 13:16:01,462 - optimization.inference - INFO - Number of candidates by RT in frame 1876: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,474 - optimization.inference - INFO - Scan time: 15.2818\n", + "2024-12-19 13:16:01,475 - optimization.inference - INFO - Number of candidates by RT in frame 1167: 328\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,478 - optimization.inference - INFO - Scan time: 27.5303\n", + "2024-12-19 13:16:01,479 - optimization.inference - INFO - Number of candidates by RT in frame 1881: 251\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,493 - optimization.inference - INFO - Scan time: 15.368\n", + "2024-12-19 13:16:01,494 - optimization.inference - INFO - Number of candidates by RT in frame 1172: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,496 - optimization.inference - INFO - Scan time: 27.6168\n", + "2024-12-19 13:16:01,497 - optimization.inference - INFO - Number of candidates by RT in frame 1886: 254\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,514 - optimization.inference - INFO - Scan time: 15.4534\n", + "2024-12-19 13:16:01,516 - optimization.inference - INFO - Number of candidates by RT in frame 1177: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,517 - optimization.inference - INFO - Scan time: 27.7029\n", + "2024-12-19 13:16:01,518 - optimization.inference - INFO - Number of candidates by RT in frame 1891: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,536 - optimization.inference - INFO - Scan time: 15.5396\n", + "2024-12-19 13:16:01,537 - optimization.inference - INFO - Scan time: 27.7899\n", + "2024-12-19 13:16:01,538 - optimization.inference - INFO - Number of candidates by RT in frame 1182: 336\n", + "2024-12-19 13:16:01,538 - optimization.inference - INFO - Number of candidates by RT in frame 1896: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,558 - optimization.inference - INFO - Scan time: 15.6258\n", + "2024-12-19 13:16:01,559 - optimization.inference - INFO - Scan time: 27.875\n", + "2024-12-19 13:16:01,559 - optimization.inference - INFO - Number of candidates by RT in frame 1187: 342\n", + "2024-12-19 13:16:01,560 - optimization.inference - INFO - Number of candidates by RT in frame 1901: 253\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,580 - optimization.inference - INFO - Scan time: 27.9605\n", + "2024-12-19 13:16:01,581 - optimization.inference - INFO - Scan time: 15.7108\n", + "2024-12-19 13:16:01,581 - optimization.inference - INFO - Number of candidates by RT in frame 1906: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,583 - optimization.inference - INFO - Number of candidates by RT in frame 1192: 332\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,602 - optimization.inference - INFO - Scan time: 28.0458\n", + "2024-12-19 13:16:01,603 - optimization.inference - INFO - Scan time: 15.7972\n", + "2024-12-19 13:16:01,603 - optimization.inference - INFO - Number of candidates by RT in frame 1911: 257\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,605 - optimization.inference - INFO - Number of candidates by RT in frame 1197: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,623 - optimization.inference - INFO - Scan time: 28.1315\n", + "2024-12-19 13:16:01,623 - optimization.inference - INFO - Scan time: 15.8823\n", + "2024-12-19 13:16:01,624 - optimization.inference - INFO - Number of candidates by RT in frame 1916: 258\n", + "2024-12-19 13:16:01,624 - optimization.inference - INFO - Number of candidates by RT in frame 1202: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,644 - optimization.inference - INFO - Scan time: 15.968\n", + "2024-12-19 13:16:01,644 - optimization.inference - INFO - Scan time: 28.2172\n", + "2024-12-19 13:16:01,645 - optimization.inference - INFO - Number of candidates by RT in frame 1207: 305\n", + "2024-12-19 13:16:01,645 - optimization.inference - INFO - Number of candidates by RT in frame 1921: 247\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,664 - optimization.inference - INFO - Scan time: 16.053\n", + "2024-12-19 13:16:01,665 - optimization.inference - INFO - Scan time: 28.3022\n", + "2024-12-19 13:16:01,665 - optimization.inference - INFO - Number of candidates by RT in frame 1212: 307\n", + "2024-12-19 13:16:01,666 - optimization.inference - INFO - Number of candidates by RT in frame 1926: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,680 - optimization.inference - INFO - Scan time: 28.3877\n", + "2024-12-19 13:16:01,681 - optimization.inference - INFO - Number of candidates by RT in frame 1931: 243\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,683 - optimization.inference - INFO - Scan time: 16.1386\n", + "2024-12-19 13:16:01,684 - optimization.inference - INFO - Number of candidates by RT in frame 1217: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,697 - optimization.inference - INFO - Scan time: 28.4731\n", + "2024-12-19 13:16:01,698 - optimization.inference - INFO - Number of candidates by RT in frame 1936: 236\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,703 - optimization.inference - INFO - Scan time: 16.2256\n", + "2024-12-19 13:16:01,704 - optimization.inference - INFO - Number of candidates by RT in frame 1222: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,714 - optimization.inference - INFO - Scan time: 28.559\n", + "2024-12-19 13:16:01,715 - optimization.inference - INFO - Number of candidates by RT in frame 1941: 235\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,724 - optimization.inference - INFO - Scan time: 16.3106\n", + "2024-12-19 13:16:01,725 - optimization.inference - INFO - Number of candidates by RT in frame 1227: 318\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,731 - optimization.inference - INFO - Scan time: 28.644\n", + "2024-12-19 13:16:01,732 - optimization.inference - INFO - Number of candidates by RT in frame 1946: 222\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,744 - optimization.inference - INFO - Scan time: 16.3962\n", + "2024-12-19 13:16:01,745 - optimization.inference - INFO - Number of candidates by RT in frame 1232: 319\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,749 - optimization.inference - INFO - Scan time: 28.7292\n", + "2024-12-19 13:16:01,750 - optimization.inference - INFO - Number of candidates by RT in frame 1951: 217\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,767 - optimization.inference - INFO - Scan time: 16.4823\n", + "2024-12-19 13:16:01,767 - optimization.inference - INFO - Scan time: 28.8148\n", + "2024-12-19 13:16:01,768 - optimization.inference - INFO - Number of candidates by RT in frame 1237: 332\n", + "2024-12-19 13:16:01,768 - optimization.inference - INFO - Number of candidates by RT in frame 1956: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,783 - optimization.inference - INFO - Scan time: 16.568\n", + "2024-12-19 13:16:01,784 - optimization.inference - INFO - Number of candidates by RT in frame 1242: 310\n", + "2024-12-19 13:16:01,784 - optimization.inference - INFO - Scan time: 28.9006\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,786 - optimization.inference - INFO - Number of candidates by RT in frame 1961: 206\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,802 - optimization.inference - INFO - Scan time: 28.9864\n", + "2024-12-19 13:16:01,803 - optimization.inference - INFO - Number of candidates by RT in frame 1966: 191\n", + "2024-12-19 13:16:01,804 - optimization.inference - INFO - Scan time: 16.6536\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,805 - optimization.inference - INFO - Number of candidates by RT in frame 1247: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,819 - optimization.inference - INFO - Scan time: 29.0726\n", + "2024-12-19 13:16:01,820 - optimization.inference - INFO - Number of candidates by RT in frame 1971: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,823 - optimization.inference - INFO - Scan time: 16.7399\n", + "2024-12-19 13:16:01,824 - optimization.inference - INFO - Number of candidates by RT in frame 1252: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,834 - optimization.inference - INFO - Scan time: 29.158\n", + "2024-12-19 13:16:01,835 - optimization.inference - INFO - Number of candidates by RT in frame 1976: 217\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,840 - optimization.inference - INFO - Scan time: 16.8255\n", + "2024-12-19 13:16:01,841 - optimization.inference - INFO - Number of candidates by RT in frame 1257: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,850 - optimization.inference - INFO - Scan time: 29.2429\n", + "2024-12-19 13:16:01,851 - optimization.inference - INFO - Number of candidates by RT in frame 1981: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,861 - optimization.inference - INFO - Scan time: 16.9103\n", + "2024-12-19 13:16:01,862 - optimization.inference - INFO - Number of candidates by RT in frame 1262: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,866 - optimization.inference - INFO - Scan time: 29.3284\n", + "2024-12-19 13:16:01,867 - optimization.inference - INFO - Number of candidates by RT in frame 1986: 217\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,883 - optimization.inference - INFO - Scan time: 29.4141\n", + "2024-12-19 13:16:01,883 - optimization.inference - INFO - Scan time: 16.996\n", + "2024-12-19 13:16:01,884 - optimization.inference - INFO - Number of candidates by RT in frame 1991: 199\n", + "2024-12-19 13:16:01,884 - optimization.inference - INFO - Number of candidates by RT in frame 1267: 337\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,901 - optimization.inference - INFO - Scan time: 29.5004\n", + "2024-12-19 13:16:01,902 - optimization.inference - INFO - Number of candidates by RT in frame 1996: 207\n", + "2024-12-19 13:16:01,902 - optimization.inference - INFO - Scan time: 17.0822\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,903 - optimization.inference - INFO - Number of candidates by RT in frame 1272: 324\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,920 - optimization.inference - INFO - Scan time: 29.5859\n", + "2024-12-19 13:16:01,921 - optimization.inference - INFO - Number of candidates by RT in frame 2001: 217\n", + "2024-12-19 13:16:01,921 - optimization.inference - INFO - Scan time: 17.1688\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,922 - optimization.inference - INFO - Number of candidates by RT in frame 1277: 317\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,937 - optimization.inference - INFO - Scan time: 29.6719\n", + "2024-12-19 13:16:01,938 - optimization.inference - INFO - Number of candidates by RT in frame 2006: 196\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,939 - optimization.inference - INFO - Scan time: 17.2547\n", + "2024-12-19 13:16:01,940 - optimization.inference - INFO - Number of candidates by RT in frame 1282: 316\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,953 - optimization.inference - INFO - Scan time: 29.7576\n", + "2024-12-19 13:16:01,955 - optimization.inference - INFO - Number of candidates by RT in frame 2011: 203\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,958 - optimization.inference - INFO - Scan time: 17.3409\n", + "2024-12-19 13:16:01,959 - optimization.inference - INFO - Number of candidates by RT in frame 1287: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,969 - optimization.inference - INFO - Scan time: 29.8429\n", + "2024-12-19 13:16:01,970 - optimization.inference - INFO - Number of candidates by RT in frame 2016: 198\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,983 - optimization.inference - INFO - Scan time: 29.9291\n", + "2024-12-19 13:16:01,985 - optimization.inference - INFO - Number of candidates by RT in frame 2021: 207\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:01,988 - optimization.inference - INFO - Scan time: 17.4272\n", + "2024-12-19 13:16:01,989 - optimization.inference - INFO - Number of candidates by RT in frame 1292: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,002 - optimization.inference - INFO - Scan time: 30.0151\n", + "2024-12-19 13:16:02,003 - optimization.inference - INFO - Number of candidates by RT in frame 2026: 196\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,013 - optimization.inference - INFO - Scan time: 17.5131\n", + "2024-12-19 13:16:02,014 - optimization.inference - INFO - Number of candidates by RT in frame 1297: 345\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,022 - optimization.inference - INFO - Scan time: 30.1014\n", + "2024-12-19 13:16:02,023 - optimization.inference - INFO - Number of candidates by RT in frame 2031: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,034 - optimization.inference - INFO - Scan time: 17.5998\n", + "2024-12-19 13:16:02,035 - optimization.inference - INFO - Number of candidates by RT in frame 1302: 335\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,038 - optimization.inference - INFO - Scan time: 30.1874\n", + "2024-12-19 13:16:02,039 - optimization.inference - INFO - Number of candidates by RT in frame 2036: 172\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,052 - optimization.inference - INFO - Scan time: 17.6852\n", + "2024-12-19 13:16:02,052 - optimization.inference - INFO - Scan time: 30.2725\n", + "2024-12-19 13:16:02,053 - optimization.inference - INFO - Number of candidates by RT in frame 1307: 310\n", + "2024-12-19 13:16:02,053 - optimization.inference - INFO - Number of candidates by RT in frame 2041: 177\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,066 - optimization.inference - INFO - Scan time: 30.3589\n", + "2024-12-19 13:16:02,067 - optimization.inference - INFO - Number of candidates by RT in frame 2046: 187\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,073 - optimization.inference - INFO - Scan time: 17.7712\n", + "2024-12-19 13:16:02,074 - optimization.inference - INFO - Number of candidates by RT in frame 1312: 338\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,083 - optimization.inference - INFO - Scan time: 30.445\n", + "2024-12-19 13:16:02,084 - optimization.inference - INFO - Number of candidates by RT in frame 2051: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,092 - optimization.inference - INFO - Scan time: 17.8567\n", + "2024-12-19 13:16:02,093 - optimization.inference - INFO - Number of candidates by RT in frame 1317: 321\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,099 - optimization.inference - INFO - Scan time: 30.5312\n", + "2024-12-19 13:16:02,100 - optimization.inference - INFO - Number of candidates by RT in frame 2056: 233\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,114 - optimization.inference - INFO - Scan time: 17.9428\n", + "2024-12-19 13:16:02,115 - optimization.inference - INFO - Number of candidates by RT in frame 1322: 319\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,116 - optimization.inference - INFO - Scan time: 30.6168\n", + "2024-12-19 13:16:02,117 - optimization.inference - INFO - Number of candidates by RT in frame 2061: 226\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,130 - optimization.inference - INFO - Scan time: 30.7018\n", + "2024-12-19 13:16:02,131 - optimization.inference - INFO - Number of candidates by RT in frame 2066: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,134 - optimization.inference - INFO - Scan time: 18.0283\n", + "2024-12-19 13:16:02,135 - optimization.inference - INFO - Number of candidates by RT in frame 1327: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,148 - optimization.inference - INFO - Scan time: 30.7871\n", + "2024-12-19 13:16:02,149 - optimization.inference - INFO - Number of candidates by RT in frame 2071: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,153 - optimization.inference - INFO - Scan time: 18.1139\n", + "2024-12-19 13:16:02,154 - optimization.inference - INFO - Number of candidates by RT in frame 1332: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,168 - optimization.inference - INFO - Scan time: 30.8734\n", + "2024-12-19 13:16:02,169 - optimization.inference - INFO - Number of candidates by RT in frame 2076: 196\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,173 - optimization.inference - INFO - Scan time: 18.2002\n", + "2024-12-19 13:16:02,174 - optimization.inference - INFO - Number of candidates by RT in frame 1337: 333\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,188 - optimization.inference - INFO - Scan time: 30.9587\n", + "2024-12-19 13:16:02,189 - optimization.inference - INFO - Number of candidates by RT in frame 2081: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,194 - optimization.inference - INFO - Scan time: 18.2861\n", + "2024-12-19 13:16:02,195 - optimization.inference - INFO - Number of candidates by RT in frame 1342: 344\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,206 - optimization.inference - INFO - Scan time: 31.0444\n", + "2024-12-19 13:16:02,207 - optimization.inference - INFO - Number of candidates by RT in frame 2086: 192\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,217 - optimization.inference - INFO - Scan time: 18.371\n", + "2024-12-19 13:16:02,218 - optimization.inference - INFO - Number of candidates by RT in frame 1347: 346\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,222 - optimization.inference - INFO - Scan time: 31.1301\n", + "2024-12-19 13:16:02,223 - optimization.inference - INFO - Number of candidates by RT in frame 2091: 208\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,236 - optimization.inference - INFO - Scan time: 18.4575\n", + "2024-12-19 13:16:02,237 - optimization.inference - INFO - Number of candidates by RT in frame 1352: 310\n", + "2024-12-19 13:16:02,238 - optimization.inference - INFO - Scan time: 31.2156\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,239 - optimization.inference - INFO - Number of candidates by RT in frame 2096: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,256 - optimization.inference - INFO - Scan time: 18.543\n", + "2024-12-19 13:16:02,258 - optimization.inference - INFO - Number of candidates by RT in frame 1357: 321\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,258 - optimization.inference - INFO - Scan time: 31.3015\n", + "2024-12-19 13:16:02,259 - optimization.inference - INFO - Number of candidates by RT in frame 2101: 206\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,276 - optimization.inference - INFO - Scan time: 31.3875\n", + "2024-12-19 13:16:02,277 - optimization.inference - INFO - Number of candidates by RT in frame 2106: 205\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,278 - optimization.inference - INFO - Scan time: 18.6283\n", + "2024-12-19 13:16:02,279 - optimization.inference - INFO - Number of candidates by RT in frame 1362: 340\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,292 - optimization.inference - INFO - Scan time: 31.4733\n", + "2024-12-19 13:16:02,293 - optimization.inference - INFO - Number of candidates by RT in frame 2111: 196\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,301 - optimization.inference - INFO - Scan time: 18.7142\n", + "2024-12-19 13:16:02,302 - optimization.inference - INFO - Number of candidates by RT in frame 1367: 321\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,312 - optimization.inference - INFO - Scan time: 31.5589\n", + "2024-12-19 13:16:02,313 - optimization.inference - INFO - Number of candidates by RT in frame 2116: 182\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,321 - optimization.inference - INFO - Scan time: 18.8002\n", + "2024-12-19 13:16:02,322 - optimization.inference - INFO - Number of candidates by RT in frame 1372: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,329 - optimization.inference - INFO - Scan time: 31.6445\n", + "2024-12-19 13:16:02,330 - optimization.inference - INFO - Number of candidates by RT in frame 2121: 149\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,338 - optimization.inference - INFO - Scan time: 18.8862\n", + "2024-12-19 13:16:02,339 - optimization.inference - INFO - Number of candidates by RT in frame 1377: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,343 - optimization.inference - INFO - Scan time: 31.7303\n", + "2024-12-19 13:16:02,344 - optimization.inference - INFO - Number of candidates by RT in frame 2126: 128\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,352 - optimization.inference - INFO - Scan time: 18.9722\n", + "2024-12-19 13:16:02,353 - optimization.inference - INFO - Number of candidates by RT in frame 1382: 299\n", + "2024-12-19 13:16:02,353 - optimization.inference - INFO - Scan time: 31.816\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,354 - optimization.inference - INFO - Number of candidates by RT in frame 2131: 131\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,369 - optimization.inference - INFO - Scan time: 31.9016\n", + "2024-12-19 13:16:02,370 - optimization.inference - INFO - Scan time: 19.0576\n", + "2024-12-19 13:16:02,370 - optimization.inference - INFO - Number of candidates by RT in frame 2136: 100\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,371 - optimization.inference - INFO - Number of candidates by RT in frame 1387: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,385 - optimization.inference - INFO - Scan time: 31.9882\n", + "2024-12-19 13:16:02,385 - optimization.inference - INFO - Number of candidates by RT in frame 2141: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,391 - optimization.inference - INFO - Scan time: 19.1435\n", + "2024-12-19 13:16:02,392 - optimization.inference - INFO - Number of candidates by RT in frame 1392: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,402 - optimization.inference - INFO - Scan time: 32.0748\n", + "2024-12-19 13:16:02,402 - optimization.inference - INFO - Number of candidates by RT in frame 2146: 27\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,412 - optimization.inference - INFO - Scan time: 19.2285\n", + "2024-12-19 13:16:02,413 - optimization.inference - INFO - Number of candidates by RT in frame 1397: 337\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,415 - optimization.inference - INFO - Scan time: 32.1518\n", + "2024-12-19 13:16:02,416 - optimization.inference - INFO - Number of candidates by RT in frame 2151: 18\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,429 - optimization.inference - INFO - Scan time: 32.1849\n", + "2024-12-19 13:16:02,430 - optimization.inference - INFO - Number of candidates by RT in frame 2156: 17\n", + "2024-12-19 13:16:02,431 - optimization.inference - INFO - Scan time: 19.3147\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,432 - optimization.inference - INFO - Number of candidates by RT in frame 1402: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,442 - optimization.inference - INFO - Scan time: 32.2048\n", + "2024-12-19 13:16:02,442 - optimization.inference - INFO - Number of candidates by RT in frame 2161: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,450 - optimization.inference - INFO - Scan time: 19.401\n", + "2024-12-19 13:16:02,452 - optimization.inference - INFO - Number of candidates by RT in frame 1407: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,454 - optimization.inference - INFO - Scan time: 32.2219\n", + "2024-12-19 13:16:02,455 - optimization.inference - INFO - Number of candidates by RT in frame 2166: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,466 - optimization.inference - INFO - Scan time: 32.2431\n", + "2024-12-19 13:16:02,467 - optimization.inference - INFO - Number of candidates by RT in frame 2171: 14\n", + "2024-12-19 13:16:02,467 - optimization.inference - INFO - Scan time: 19.4873\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,468 - optimization.inference - INFO - Number of candidates by RT in frame 1412: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,477 - optimization.inference - INFO - Scan time: 32.2681\n", + "2024-12-19 13:16:02,478 - optimization.inference - INFO - Number of candidates by RT in frame 2176: 12\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,488 - optimization.inference - INFO - Scan time: 19.5735\n", + "2024-12-19 13:16:02,489 - optimization.inference - INFO - Number of candidates by RT in frame 1417: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,491 - optimization.inference - INFO - Scan time: 32.2881\n", + "2024-12-19 13:16:02,492 - optimization.inference - INFO - Number of candidates by RT in frame 2181: 11\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,504 - optimization.inference - INFO - Scan time: 32.3017\n", + "2024-12-19 13:16:02,505 - optimization.inference - INFO - Scan time: 19.6596\n", + "2024-12-19 13:16:02,505 - optimization.inference - INFO - Number of candidates by RT in frame 2186: 11\n", + "2024-12-19 13:16:02,506 - optimization.inference - INFO - Number of candidates by RT in frame 1422: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,517 - optimization.inference - INFO - Scan time: 32.3154\n", + "2024-12-19 13:16:02,517 - optimization.inference - INFO - Number of candidates by RT in frame 2191: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,523 - optimization.inference - INFO - Scan time: 19.745\n", + "2024-12-19 13:16:02,524 - optimization.inference - INFO - Number of candidates by RT in frame 1427: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,530 - optimization.inference - INFO - Scan time: 32.333\n", + "2024-12-19 13:16:02,531 - optimization.inference - INFO - Number of candidates by RT in frame 2196: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,542 - optimization.inference - INFO - Scan time: 19.8302\n", + "2024-12-19 13:16:02,542 - optimization.inference - INFO - Scan time: 32.3459\n", + "2024-12-19 13:16:02,543 - optimization.inference - INFO - Number of candidates by RT in frame 1432: 298\n", + "2024-12-19 13:16:02,543 - optimization.inference - INFO - Number of candidates by RT in frame 2201: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,553 - optimization.inference - INFO - Scan time: 32.3735\n", + "2024-12-19 13:16:02,554 - optimization.inference - INFO - Number of candidates by RT in frame 2206: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,564 - optimization.inference - INFO - Scan time: 19.9157\n", + "2024-12-19 13:16:02,565 - optimization.inference - INFO - Number of candidates by RT in frame 1437: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,566 - optimization.inference - INFO - Scan time: 32.3926\n", + "2024-12-19 13:16:02,567 - optimization.inference - INFO - Number of candidates by RT in frame 2211: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,578 - optimization.inference - INFO - Scan time: 32.4074\n", + "2024-12-19 13:16:02,579 - optimization.inference - INFO - Number of candidates by RT in frame 2216: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,584 - optimization.inference - INFO - Scan time: 20.0011\n", + "2024-12-19 13:16:02,585 - optimization.inference - INFO - Number of candidates by RT in frame 1442: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,590 - optimization.inference - INFO - Scan time: 32.4266\n", + "2024-12-19 13:16:02,591 - optimization.inference - INFO - Number of candidates by RT in frame 2221: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,602 - optimization.inference - INFO - Scan time: 32.4394\n", + "2024-12-19 13:16:02,603 - optimization.inference - INFO - Number of candidates by RT in frame 2226: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,604 - optimization.inference - INFO - Scan time: 20.0867\n", + "2024-12-19 13:16:02,605 - optimization.inference - INFO - Number of candidates by RT in frame 1447: 294\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,613 - optimization.inference - INFO - Scan time: 32.4515\n", + "2024-12-19 13:16:02,614 - optimization.inference - INFO - Number of candidates by RT in frame 2231: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,624 - optimization.inference - INFO - Scan time: 32.465\n", + "2024-12-19 13:16:02,625 - optimization.inference - INFO - Number of candidates by RT in frame 2236: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,627 - optimization.inference - INFO - Scan time: 20.173\n", + "2024-12-19 13:16:02,629 - optimization.inference - INFO - Number of candidates by RT in frame 1452: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,634 - optimization.inference - INFO - Scan time: 32.4779\n", + "2024-12-19 13:16:02,635 - optimization.inference - INFO - Number of candidates by RT in frame 2241: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,646 - optimization.inference - INFO - Scan time: 32.4906\n", + "2024-12-19 13:16:02,647 - optimization.inference - INFO - Number of candidates by RT in frame 2246: 5\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,658 - optimization.inference - INFO - Scan time: 32.5064\n", + "2024-12-19 13:16:02,659 - optimization.inference - INFO - Number of candidates by RT in frame 2251: 4\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,660 - optimization.inference - INFO - Scan time: 20.2585\n", + "2024-12-19 13:16:02,662 - optimization.inference - INFO - Number of candidates by RT in frame 1457: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,669 - optimization.inference - INFO - Scan time: 32.5206\n", + "2024-12-19 13:16:02,670 - optimization.inference - INFO - Number of candidates by RT in frame 2256: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,679 - optimization.inference - INFO - Scan time: 32.5381\n", + "2024-12-19 13:16:02,680 - optimization.inference - INFO - Number of candidates by RT in frame 2261: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,689 - optimization.inference - INFO - Scan time: 32.555\n", + "2024-12-19 13:16:02,689 - optimization.inference - INFO - Number of candidates by RT in frame 2266: 3\n", + "2024-12-19 13:16:02,690 - optimization.inference - INFO - Scan time: 20.3433\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,691 - optimization.inference - INFO - Number of candidates by RT in frame 1462: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,699 - optimization.inference - INFO - Scan time: 32.5739\n", + "2024-12-19 13:16:02,700 - optimization.inference - INFO - Number of candidates by RT in frame 2271: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,709 - optimization.inference - INFO - Scan time: 32.5868\n", + "2024-12-19 13:16:02,710 - optimization.inference - INFO - Number of candidates by RT in frame 2276: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,716 - optimization.inference - INFO - Scan time: 20.429\n", + "2024-12-19 13:16:02,717 - optimization.inference - INFO - Number of candidates by RT in frame 1467: 324\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,719 - optimization.inference - INFO - Scan time: 32.5997\n", + "2024-12-19 13:16:02,720 - optimization.inference - INFO - Number of candidates by RT in frame 2281: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,727 - optimization.inference - INFO - Scan time: 32.6139\n", + "2024-12-19 13:16:02,728 - optimization.inference - INFO - Number of candidates by RT in frame 2286: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,737 - optimization.inference - INFO - Scan time: 32.6282\n", + "2024-12-19 13:16:02,737 - optimization.inference - INFO - Scan time: 20.5141\n", + "2024-12-19 13:16:02,737 - optimization.inference - INFO - Number of candidates by RT in frame 2291: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,738 - optimization.inference - INFO - Number of candidates by RT in frame 1472: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,746 - optimization.inference - INFO - Scan time: 32.6437\n", + "2024-12-19 13:16:02,747 - optimization.inference - INFO - Number of candidates by RT in frame 2296: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,755 - optimization.inference - INFO - Scan time: 32.6598\n", + "2024-12-19 13:16:02,756 - optimization.inference - INFO - Number of candidates by RT in frame 2301: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,757 - optimization.inference - INFO - Scan time: 20.6006\n", + "2024-12-19 13:16:02,759 - optimization.inference - INFO - Number of candidates by RT in frame 1477: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,764 - optimization.inference - INFO - Scan time: 32.6745\n", + "2024-12-19 13:16:02,765 - optimization.inference - INFO - Number of candidates by RT in frame 2306: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,772 - optimization.inference - INFO - Scan time: 32.6917\n", + "2024-12-19 13:16:02,773 - optimization.inference - INFO - Number of candidates by RT in frame 2311: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,779 - optimization.inference - INFO - Scan time: 20.6859\n", + "2024-12-19 13:16:02,780 - optimization.inference - INFO - Number of candidates by RT in frame 1482: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,781 - optimization.inference - INFO - Scan time: 32.7046\n", + "2024-12-19 13:16:02,782 - optimization.inference - INFO - Number of candidates by RT in frame 2316: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,790 - optimization.inference - INFO - Scan time: 32.72\n", + "2024-12-19 13:16:02,791 - optimization.inference - INFO - Number of candidates by RT in frame 2321: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,797 - optimization.inference - INFO - Scan time: 20.7723\n", + "2024-12-19 13:16:02,798 - optimization.inference - INFO - Scan time: 32.7356\n", + "2024-12-19 13:16:02,799 - optimization.inference - INFO - Number of candidates by RT in frame 1487: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,799 - optimization.inference - INFO - Number of candidates by RT in frame 2326: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,807 - optimization.inference - INFO - Scan time: 32.7489\n", + "2024-12-19 13:16:02,808 - optimization.inference - INFO - Number of candidates by RT in frame 2331: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,815 - optimization.inference - INFO - Scan time: 20.8582\n", + "2024-12-19 13:16:02,816 - optimization.inference - INFO - Number of candidates by RT in frame 1492: 286\n", + "2024-12-19 13:16:02,816 - optimization.inference - INFO - Scan time: 32.766\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,817 - optimization.inference - INFO - Number of candidates by RT in frame 2336: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,824 - optimization.inference - INFO - Scan time: 32.7838\n", + "2024-12-19 13:16:02,825 - optimization.inference - INFO - Number of candidates by RT in frame 2341: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,832 - optimization.inference - INFO - Scan time: 32.7987\n", + "2024-12-19 13:16:02,833 - optimization.inference - INFO - Number of candidates by RT in frame 2346: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,834 - optimization.inference - INFO - Scan time: 20.9435\n", + "2024-12-19 13:16:02,835 - optimization.inference - INFO - Number of candidates by RT in frame 1497: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,840 - optimization.inference - INFO - Scan time: 32.8136\n", + "2024-12-19 13:16:02,840 - optimization.inference - INFO - Number of candidates by RT in frame 2351: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,848 - optimization.inference - INFO - Scan time: 32.8304\n", + "2024-12-19 13:16:02,849 - optimization.inference - INFO - Number of candidates by RT in frame 2356: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,855 - optimization.inference - INFO - Scan time: 21.0299\n", + "2024-12-19 13:16:02,856 - optimization.inference - INFO - Number of candidates by RT in frame 1502: 308\n", + "2024-12-19 13:16:02,856 - optimization.inference - INFO - Scan time: 32.8438\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,857 - optimization.inference - INFO - Number of candidates by RT in frame 2361: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,864 - optimization.inference - INFO - Scan time: 32.8594\n", + "2024-12-19 13:16:02,865 - optimization.inference - INFO - Number of candidates by RT in frame 2366: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,872 - optimization.inference - INFO - Scan time: 32.8722\n", + "2024-12-19 13:16:02,873 - optimization.inference - INFO - Number of candidates by RT in frame 2371: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,874 - optimization.inference - INFO - Scan time: 21.1153\n", + "2024-12-19 13:16:02,875 - optimization.inference - INFO - Number of candidates by RT in frame 1507: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,880 - optimization.inference - INFO - Scan time: 32.8837\n", + "2024-12-19 13:16:02,881 - optimization.inference - INFO - Number of candidates by RT in frame 2376: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,888 - optimization.inference - INFO - Scan time: 32.9006\n", + "2024-12-19 13:16:02,889 - optimization.inference - INFO - Number of candidates by RT in frame 2381: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,894 - optimization.inference - INFO - Scan time: 21.2009\n", + "2024-12-19 13:16:02,895 - optimization.inference - INFO - Number of candidates by RT in frame 1512: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,897 - optimization.inference - INFO - Scan time: 32.9139\n", + "2024-12-19 13:16:02,897 - optimization.inference - INFO - Number of candidates by RT in frame 2386: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,905 - optimization.inference - INFO - Scan time: 32.9264\n", + "2024-12-19 13:16:02,905 - optimization.inference - INFO - Number of candidates by RT in frame 2391: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,912 - optimization.inference - INFO - Scan time: 32.9399\n", + "2024-12-19 13:16:02,913 - optimization.inference - INFO - Number of candidates by RT in frame 2396: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,916 - optimization.inference - INFO - Scan time: 21.2866\n", + "2024-12-19 13:16:02,917 - optimization.inference - INFO - Number of candidates by RT in frame 1517: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,921 - optimization.inference - INFO - Scan time: 32.9521\n", + "2024-12-19 13:16:02,921 - optimization.inference - INFO - Number of candidates by RT in frame 2401: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,928 - optimization.inference - INFO - Scan time: 32.9636\n", + "2024-12-19 13:16:02,929 - optimization.inference - INFO - Number of candidates by RT in frame 2406: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,936 - optimization.inference - INFO - Scan time: 32.9757\n", + "2024-12-19 13:16:02,937 - optimization.inference - INFO - Number of candidates by RT in frame 2411: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,938 - optimization.inference - INFO - Scan time: 21.3726\n", + "2024-12-19 13:16:02,939 - optimization.inference - INFO - Number of candidates by RT in frame 1522: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,943 - optimization.inference - INFO - Scan time: 32.9934\n", + "2024-12-19 13:16:02,944 - optimization.inference - INFO - Number of candidates by RT in frame 2416: 1\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,950 - optimization.inference - INFO - Shape of COO matrix: (2421, 18939)\n", + "2024-12-19 13:16:02,959 - optimization.inference - INFO - Scan time: 21.4574\n", + "2024-12-19 13:16:02,960 - optimization.inference - INFO - Number of candidates by RT in frame 1527: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,978 - optimization.inference - INFO - Scan time: 21.5423\n", + "2024-12-19 13:16:02,979 - optimization.inference - INFO - Number of candidates by RT in frame 1532: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:02,994 - optimization.inference - INFO - Scan time: 21.6293\n", + "2024-12-19 13:16:02,996 - optimization.inference - INFO - Number of candidates by RT in frame 1537: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,014 - optimization.inference - INFO - Scan time: 21.7144\n", + "2024-12-19 13:16:03,015 - optimization.inference - INFO - Number of candidates by RT in frame 1542: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,035 - optimization.inference - INFO - Size of COO matrix in batch 1: 1.619136 Mb\n", + "2024-12-19 13:16:03,035 - optimization.inference - INFO - Scan time: 21.8\n", + "2024-12-19 13:16:03,036 - optimization.inference - INFO - Number of candidates by RT in frame 1547: 332\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,062 - optimization.inference - INFO - Scan time: 21.8857\n", + "2024-12-19 13:16:03,063 - optimization.inference - INFO - Number of candidates by RT in frame 1552: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,088 - optimization.inference - INFO - Scan time: 21.9722\n", + "2024-12-19 13:16:03,090 - optimization.inference - INFO - Number of candidates by RT in frame 1557: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,117 - optimization.inference - INFO - Scan time: 22.0576\n", + "2024-12-19 13:16:03,118 - optimization.inference - INFO - Number of candidates by RT in frame 1562: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,144 - optimization.inference - INFO - Scan time: 22.1437\n", + "2024-12-19 13:16:03,145 - optimization.inference - INFO - Number of candidates by RT in frame 1567: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,186 - optimization.inference - INFO - Scan time: 22.2285\n", + "2024-12-19 13:16:03,187 - optimization.inference - INFO - Number of candidates by RT in frame 1572: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,207 - optimization.inference - INFO - Scan time: 22.3137\n", + "2024-12-19 13:16:03,208 - optimization.inference - INFO - Number of candidates by RT in frame 1577: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,236 - optimization.inference - INFO - Scan time: 22.3996\n", + "2024-12-19 13:16:03,237 - optimization.inference - INFO - Number of candidates by RT in frame 1582: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,261 - optimization.inference - INFO - Scan time: 22.4858\n", + "2024-12-19 13:16:03,262 - optimization.inference - INFO - Number of candidates by RT in frame 1587: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,284 - optimization.inference - INFO - Scan time: 22.5716\n", + "2024-12-19 13:16:03,285 - optimization.inference - INFO - Number of candidates by RT in frame 1592: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,303 - optimization.inference - INFO - Scan time: 22.6564\n", + "2024-12-19 13:16:03,304 - optimization.inference - INFO - Number of candidates by RT in frame 1597: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,322 - optimization.inference - INFO - Scan time: 22.7418\n", + "2024-12-19 13:16:03,323 - optimization.inference - INFO - Number of candidates by RT in frame 1602: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,340 - optimization.inference - INFO - Scan time: 22.828\n", + "2024-12-19 13:16:03,341 - optimization.inference - INFO - Number of candidates by RT in frame 1607: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,358 - optimization.inference - INFO - Scan time: 22.9144\n", + "2024-12-19 13:16:03,359 - optimization.inference - INFO - Number of candidates by RT in frame 1612: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,377 - optimization.inference - INFO - Scan time: 23.0009\n", + "2024-12-19 13:16:03,378 - optimization.inference - INFO - Number of candidates by RT in frame 1617: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,396 - optimization.inference - INFO - Scan time: 23.0863\n", + "2024-12-19 13:16:03,397 - optimization.inference - INFO - Number of candidates by RT in frame 1622: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,416 - optimization.inference - INFO - Scan time: 23.172\n", + "2024-12-19 13:16:03,417 - optimization.inference - INFO - Number of candidates by RT in frame 1627: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,434 - optimization.inference - INFO - Scan time: 23.2577\n", + "2024-12-19 13:16:03,435 - optimization.inference - INFO - Number of candidates by RT in frame 1632: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,455 - optimization.inference - INFO - Scan time: 23.3433\n", + "2024-12-19 13:16:03,456 - optimization.inference - INFO - Number of candidates by RT in frame 1637: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,478 - optimization.inference - INFO - Scan time: 23.4292\n", + "2024-12-19 13:16:03,479 - optimization.inference - INFO - Number of candidates by RT in frame 1642: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,501 - optimization.inference - INFO - Scan time: 23.5138\n", + "2024-12-19 13:16:03,502 - optimization.inference - INFO - Number of candidates by RT in frame 1647: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,520 - optimization.inference - INFO - Scan time: 23.5991\n", + "2024-12-19 13:16:03,521 - optimization.inference - INFO - Number of candidates by RT in frame 1652: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,541 - optimization.inference - INFO - Scan time: 23.6855\n", + "2024-12-19 13:16:03,542 - optimization.inference - INFO - Number of candidates by RT in frame 1657: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,559 - optimization.inference - INFO - Scan time: 23.7706\n", + "2024-12-19 13:16:03,560 - optimization.inference - INFO - Number of candidates by RT in frame 1662: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,579 - optimization.inference - INFO - Scan time: 23.8572\n", + "2024-12-19 13:16:03,580 - optimization.inference - INFO - Number of candidates by RT in frame 1667: 251\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,598 - optimization.inference - INFO - Scan time: 23.9422\n", + "2024-12-19 13:16:03,599 - optimization.inference - INFO - Number of candidates by RT in frame 1672: 255\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,612 - optimization.inference - INFO - Scan time: 24.0279\n", + "2024-12-19 13:16:03,613 - optimization.inference - INFO - Number of candidates by RT in frame 1677: 254\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,631 - optimization.inference - INFO - Scan time: 24.114\n", + "2024-12-19 13:16:03,632 - optimization.inference - INFO - Number of candidates by RT in frame 1682: 245\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,650 - optimization.inference - INFO - Scan time: 24.1995\n", + "2024-12-19 13:16:03,651 - optimization.inference - INFO - Number of candidates by RT in frame 1687: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,670 - optimization.inference - INFO - Scan time: 24.2854\n", + "2024-12-19 13:16:03,671 - optimization.inference - INFO - Number of candidates by RT in frame 1692: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,692 - optimization.inference - INFO - Scan time: 24.3708\n", + "2024-12-19 13:16:03,693 - optimization.inference - INFO - Number of candidates by RT in frame 1697: 258\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,712 - optimization.inference - INFO - Scan time: 24.4566\n", + "2024-12-19 13:16:03,713 - optimization.inference - INFO - Number of candidates by RT in frame 1702: 248\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,732 - optimization.inference - INFO - Scan time: 24.5428\n", + "2024-12-19 13:16:03,734 - optimization.inference - INFO - Number of candidates by RT in frame 1707: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,753 - optimization.inference - INFO - Scan time: 24.6291\n", + "2024-12-19 13:16:03,754 - optimization.inference - INFO - Number of candidates by RT in frame 1712: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,774 - optimization.inference - INFO - Scan time: 24.7146\n", + "2024-12-19 13:16:03,776 - optimization.inference - INFO - Number of candidates by RT in frame 1717: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,795 - optimization.inference - INFO - Scan time: 24.8006\n", + "2024-12-19 13:16:03,796 - optimization.inference - INFO - Number of candidates by RT in frame 1722: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,818 - optimization.inference - INFO - Scan time: 24.8854\n", + "2024-12-19 13:16:03,819 - optimization.inference - INFO - Number of candidates by RT in frame 1727: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,840 - optimization.inference - INFO - Scan time: 24.9704\n", + "2024-12-19 13:16:03,841 - optimization.inference - INFO - Number of candidates by RT in frame 1732: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,857 - optimization.inference - INFO - Scan time: 25.0552\n", + "2024-12-19 13:16:03,858 - optimization.inference - INFO - Number of candidates by RT in frame 1737: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,878 - optimization.inference - INFO - Scan time: 25.1416\n", + "2024-12-19 13:16:03,879 - optimization.inference - INFO - Number of candidates by RT in frame 1742: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,900 - optimization.inference - INFO - Scan time: 25.2274\n", + "2024-12-19 13:16:03,901 - optimization.inference - INFO - Number of candidates by RT in frame 1747: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,922 - optimization.inference - INFO - Scan time: 25.3136\n", + "2024-12-19 13:16:03,924 - optimization.inference - INFO - Number of candidates by RT in frame 1752: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,945 - optimization.inference - INFO - Scan time: 25.3998\n", + "2024-12-19 13:16:03,946 - optimization.inference - INFO - Number of candidates by RT in frame 1757: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,966 - optimization.inference - INFO - Scan time: 25.4855\n", + "2024-12-19 13:16:03,967 - optimization.inference - INFO - Number of candidates by RT in frame 1762: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:03,988 - optimization.inference - INFO - Scan time: 25.5714\n", + "2024-12-19 13:16:03,989 - optimization.inference - INFO - Number of candidates by RT in frame 1767: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,017 - optimization.inference - INFO - Scan time: 25.657\n", + "2024-12-19 13:16:04,019 - optimization.inference - INFO - Number of candidates by RT in frame 1772: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,044 - optimization.inference - INFO - Scan time: 25.7428\n", + "2024-12-19 13:16:04,045 - optimization.inference - INFO - Number of candidates by RT in frame 1777: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,070 - optimization.inference - INFO - Scan time: 25.8289\n", + "2024-12-19 13:16:04,072 - optimization.inference - INFO - Number of candidates by RT in frame 1782: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,092 - optimization.inference - INFO - Scan time: 25.9152\n", + "2024-12-19 13:16:04,093 - optimization.inference - INFO - Number of candidates by RT in frame 1787: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,111 - optimization.inference - INFO - Scan time: 26.0009\n", + "2024-12-19 13:16:04,113 - optimization.inference - INFO - Number of candidates by RT in frame 1792: 258\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,135 - optimization.inference - INFO - Scan time: 26.0877\n", + "2024-12-19 13:16:04,136 - optimization.inference - INFO - Number of candidates by RT in frame 1797: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,159 - optimization.inference - INFO - Scan time: 26.1737\n", + "2024-12-19 13:16:04,160 - optimization.inference - INFO - Number of candidates by RT in frame 1802: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,181 - optimization.inference - INFO - Scan time: 26.2598\n", + "2024-12-19 13:16:04,182 - optimization.inference - INFO - Number of candidates by RT in frame 1807: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,207 - optimization.inference - INFO - Scan time: 26.3463\n", + "2024-12-19 13:16:04,208 - optimization.inference - INFO - Number of candidates by RT in frame 1812: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,232 - optimization.inference - INFO - Scan time: 26.4316\n", + "2024-12-19 13:16:04,233 - optimization.inference - INFO - Number of candidates by RT in frame 1817: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,255 - optimization.inference - INFO - Scan time: 26.5172\n", + "2024-12-19 13:16:04,257 - optimization.inference - INFO - Number of candidates by RT in frame 1822: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,270 - optimization.inference - INFO - Scan time: 0.0121\n", + "2024-12-19 13:16:04,272 - optimization.inference - INFO - Number of candidates by RT in frame 4: 25\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,277 - optimization.inference - INFO - Scan time: 26.6031\n", + "2024-12-19 13:16:04,279 - optimization.inference - INFO - Number of candidates by RT in frame 1827: 276\n", + "2024-12-19 13:16:04,279 - optimization.inference - INFO - Scan time: 0.0236\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,280 - optimization.inference - INFO - Number of candidates by RT in frame 9: 32\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,285 - optimization.inference - INFO - Scan time: 0.0351\n", + "2024-12-19 13:16:04,286 - optimization.inference - INFO - Number of candidates by RT in frame 14: 34\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,291 - optimization.inference - INFO - Scan time: 0.0467\n", + "2024-12-19 13:16:04,292 - optimization.inference - INFO - Number of candidates by RT in frame 19: 34\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,297 - optimization.inference - INFO - Scan time: 0.0582\n", + "2024-12-19 13:16:04,298 - optimization.inference - INFO - Number of candidates by RT in frame 24: 37\n", + "2024-12-19 13:16:04,298 - optimization.inference - INFO - Scan time: 26.6892\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,299 - optimization.inference - INFO - Number of candidates by RT in frame 1832: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,303 - optimization.inference - INFO - Scan time: 0.0697\n", + "2024-12-19 13:16:04,304 - optimization.inference - INFO - Number of candidates by RT in frame 29: 40\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,309 - optimization.inference - INFO - Scan time: 0.0813\n", + "2024-12-19 13:16:04,310 - optimization.inference - INFO - Number of candidates by RT in frame 34: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,319 - optimization.inference - INFO - Scan time: 26.7747\n", + "2024-12-19 13:16:04,321 - optimization.inference - INFO - Number of candidates by RT in frame 1837: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,337 - optimization.inference - INFO - Scan time: 26.8605\n", + "2024-12-19 13:16:04,338 - optimization.inference - INFO - Number of candidates by RT in frame 1842: 258\n", + "2024-12-19 13:16:04,339 - optimization.inference - INFO - Scan time: 0.1063\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,339 - optimization.inference - INFO - Number of candidates by RT in frame 39: 47\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,341 - optimization.inference - INFO - Scan time: 0.0097\n", + "2024-12-19 13:16:04,343 - optimization.inference - INFO - Number of candidates by RT in frame 3: 25\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,346 - optimization.inference - INFO - Scan time: 0.1865\n", + "2024-12-19 13:16:04,347 - optimization.inference - INFO - Number of candidates by RT in frame 44: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,350 - optimization.inference - INFO - Scan time: 0.0213\n", + "2024-12-19 13:16:04,351 - optimization.inference - INFO - Number of candidates by RT in frame 8: 32\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,355 - optimization.inference - INFO - Scan time: 0.26\n", + "2024-12-19 13:16:04,356 - optimization.inference - INFO - Number of candidates by RT in frame 49: 75\n", + "2024-12-19 13:16:04,356 - optimization.inference - INFO - Scan time: 26.9467\n", + "2024-12-19 13:16:04,356 - optimization.inference - INFO - Scan time: 0.0328\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,357 - optimization.inference - INFO - Number of candidates by RT in frame 13: 34\n", + "2024-12-19 13:16:04,357 - optimization.inference - INFO - Number of candidates by RT in frame 1847: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,361 - optimization.inference - INFO - Scan time: 0.3285\n", + "2024-12-19 13:16:04,362 - optimization.inference - INFO - Number of candidates by RT in frame 54: 72\n", + "2024-12-19 13:16:04,362 - optimization.inference - INFO - Scan time: 0.0444\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,363 - optimization.inference - INFO - Number of candidates by RT in frame 18: 34\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,368 - optimization.inference - INFO - Scan time: 0.3998\n", + "2024-12-19 13:16:04,368 - optimization.inference - INFO - Scan time: 0.0559\n", + "2024-12-19 13:16:04,369 - optimization.inference - INFO - Number of candidates by RT in frame 59: 65\n", + "2024-12-19 13:16:04,369 - optimization.inference - INFO - Number of candidates by RT in frame 23: 37\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,374 - optimization.inference - INFO - Scan time: 0.0674\n", + "2024-12-19 13:16:04,375 - optimization.inference - INFO - Scan time: 0.4654\n", + "2024-12-19 13:16:04,375 - optimization.inference - INFO - Number of candidates by RT in frame 28: 40\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,376 - optimization.inference - INFO - Number of candidates by RT in frame 64: 63\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,377 - optimization.inference - INFO - Scan time: 27.0326\n", + "2024-12-19 13:16:04,378 - optimization.inference - INFO - Number of candidates by RT in frame 1852: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,383 - optimization.inference - INFO - Scan time: 0.5174\n", + "2024-12-19 13:16:04,384 - optimization.inference - INFO - Number of candidates by RT in frame 69: 65\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,385 - optimization.inference - INFO - Scan time: 0.0789\n", + "2024-12-19 13:16:04,386 - optimization.inference - INFO - Number of candidates by RT in frame 33: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,391 - optimization.inference - INFO - Scan time: 0.5493\n", + "2024-12-19 13:16:04,392 - optimization.inference - INFO - Number of candidates by RT in frame 74: 67\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,397 - optimization.inference - INFO - Scan time: 27.1184\n", + "2024-12-19 13:16:04,398 - optimization.inference - INFO - Number of candidates by RT in frame 1857: 281\n", + "2024-12-19 13:16:04,399 - optimization.inference - INFO - Scan time: 0.5763\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,399 - optimization.inference - INFO - Number of candidates by RT in frame 79: 67\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,406 - optimization.inference - INFO - Scan time: 0.5985\n", + "2024-12-19 13:16:04,407 - optimization.inference - INFO - Number of candidates by RT in frame 84: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,414 - optimization.inference - INFO - Scan time: 0.6242\n", + "2024-12-19 13:16:04,415 - optimization.inference - INFO - Number of candidates by RT in frame 89: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,418 - optimization.inference - INFO - Scan time: 0.0947\n", + "2024-12-19 13:16:04,418 - optimization.inference - INFO - Scan time: 27.2035\n", + "2024-12-19 13:16:04,419 - optimization.inference - INFO - Number of candidates by RT in frame 38: 47\n", + "2024-12-19 13:16:04,419 - optimization.inference - INFO - Number of candidates by RT in frame 1862: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,422 - optimization.inference - INFO - Scan time: 0.6405\n", + "2024-12-19 13:16:04,423 - optimization.inference - INFO - Number of candidates by RT in frame 94: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,429 - optimization.inference - INFO - Scan time: 0.1712\n", + "2024-12-19 13:16:04,430 - optimization.inference - INFO - Scan time: 0.6602\n", + "2024-12-19 13:16:04,430 - optimization.inference - INFO - Number of candidates by RT in frame 43: 65\n", + "2024-12-19 13:16:04,431 - optimization.inference - INFO - Number of candidates by RT in frame 99: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,436 - optimization.inference - INFO - Scan time: 0.2464\n", + "2024-12-19 13:16:04,437 - optimization.inference - INFO - Number of candidates by RT in frame 48: 74\n", + "2024-12-19 13:16:04,438 - optimization.inference - INFO - Scan time: 0.6766\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,439 - optimization.inference - INFO - Number of candidates by RT in frame 104: 70\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,440 - optimization.inference - INFO - Scan time: 27.289\n", + "2024-12-19 13:16:04,441 - optimization.inference - INFO - Number of candidates by RT in frame 1867: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,446 - optimization.inference - INFO - Scan time: 0.6936\n", + "2024-12-19 13:16:04,447 - optimization.inference - INFO - Number of candidates by RT in frame 109: 69\n", + "2024-12-19 13:16:04,447 - optimization.inference - INFO - Scan time: 0.3183\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,448 - optimization.inference - INFO - Number of candidates by RT in frame 53: 73\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,454 - optimization.inference - INFO - Scan time: 0.707\n", + "2024-12-19 13:16:04,455 - optimization.inference - INFO - Number of candidates by RT in frame 114: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,458 - optimization.inference - INFO - Scan time: 0.3862\n", + "2024-12-19 13:16:04,459 - optimization.inference - INFO - Scan time: 27.3745\n", + "2024-12-19 13:16:04,459 - optimization.inference - INFO - Number of candidates by RT in frame 58: 66\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,460 - optimization.inference - INFO - Number of candidates by RT in frame 1872: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,462 - optimization.inference - INFO - Scan time: 0.7219\n", + "2024-12-19 13:16:04,463 - optimization.inference - INFO - Number of candidates by RT in frame 119: 66\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,470 - optimization.inference - INFO - Scan time: 0.7517\n", + "2024-12-19 13:16:04,470 - optimization.inference - INFO - Scan time: 0.4559\n", + "2024-12-19 13:16:04,471 - optimization.inference - INFO - Number of candidates by RT in frame 124: 63\n", + "2024-12-19 13:16:04,471 - optimization.inference - INFO - Number of candidates by RT in frame 63: 63\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,477 - optimization.inference - INFO - Scan time: 27.4621\n", + "2024-12-19 13:16:04,478 - optimization.inference - INFO - Scan time: 0.7684\n", + "2024-12-19 13:16:04,478 - optimization.inference - INFO - Number of candidates by RT in frame 1877: 262\n", + "2024-12-19 13:16:04,479 - optimization.inference - INFO - Number of candidates by RT in frame 129: 62\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,483 - optimization.inference - INFO - Scan time: 0.5112\n", + "2024-12-19 13:16:04,484 - optimization.inference - INFO - Number of candidates by RT in frame 68: 65\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,486 - optimization.inference - INFO - Scan time: 0.7867\n", + "2024-12-19 13:16:04,487 - optimization.inference - INFO - Number of candidates by RT in frame 134: 59\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,494 - optimization.inference - INFO - Scan time: 0.8079\n", + "2024-12-19 13:16:04,495 - optimization.inference - INFO - Number of candidates by RT in frame 139: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,495 - optimization.inference - INFO - Scan time: 27.5475\n", + "2024-12-19 13:16:04,496 - optimization.inference - INFO - Scan time: 0.5449\n", + "2024-12-19 13:16:04,496 - optimization.inference - INFO - Number of candidates by RT in frame 1882: 242\n", + "2024-12-19 13:16:04,497 - optimization.inference - INFO - Number of candidates by RT in frame 73: 66\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,502 - optimization.inference - INFO - Scan time: 0.8304\n", + "2024-12-19 13:16:04,502 - optimization.inference - INFO - Number of candidates by RT in frame 144: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,509 - optimization.inference - INFO - Scan time: 0.5704\n", + "2024-12-19 13:16:04,509 - optimization.inference - INFO - Scan time: 0.8484\n", + "2024-12-19 13:16:04,510 - optimization.inference - INFO - Number of candidates by RT in frame 78: 67\n", + "2024-12-19 13:16:04,510 - optimization.inference - INFO - Number of candidates by RT in frame 149: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,513 - optimization.inference - INFO - Scan time: 27.6343\n", + "2024-12-19 13:16:04,514 - optimization.inference - INFO - Number of candidates by RT in frame 1887: 254\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,517 - optimization.inference - INFO - Scan time: 0.8617\n", + "2024-12-19 13:16:04,518 - optimization.inference - INFO - Number of candidates by RT in frame 154: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,522 - optimization.inference - INFO - Scan time: 0.5935\n", + "2024-12-19 13:16:04,523 - optimization.inference - INFO - Number of candidates by RT in frame 83: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,525 - optimization.inference - INFO - Scan time: 0.8791\n", + "2024-12-19 13:16:04,526 - optimization.inference - INFO - Number of candidates by RT in frame 159: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,532 - optimization.inference - INFO - Scan time: 27.7203\n", + "2024-12-19 13:16:04,533 - optimization.inference - INFO - Scan time: 0.8966\n", + "2024-12-19 13:16:04,533 - optimization.inference - INFO - Number of candidates by RT in frame 1892: 275\n", + "2024-12-19 13:16:04,533 - optimization.inference - INFO - Number of candidates by RT in frame 164: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,536 - optimization.inference - INFO - Scan time: 0.6198\n", + "2024-12-19 13:16:04,537 - optimization.inference - INFO - Number of candidates by RT in frame 88: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,540 - optimization.inference - INFO - Scan time: 0.9148\n", + "2024-12-19 13:16:04,541 - optimization.inference - INFO - Number of candidates by RT in frame 169: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,548 - optimization.inference - INFO - Scan time: 0.9349\n", + "2024-12-19 13:16:04,549 - optimization.inference - INFO - Number of candidates by RT in frame 174: 57\n", + "2024-12-19 13:16:04,549 - optimization.inference - INFO - Scan time: 0.6382\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,550 - optimization.inference - INFO - Number of candidates by RT in frame 93: 68\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,553 - optimization.inference - INFO - Scan time: 27.8068\n", + "2024-12-19 13:16:04,554 - optimization.inference - INFO - Number of candidates by RT in frame 1897: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,556 - optimization.inference - INFO - Scan time: 0.9534\n", + "2024-12-19 13:16:04,557 - optimization.inference - INFO - Number of candidates by RT in frame 179: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,563 - optimization.inference - INFO - Scan time: 0.6572\n", + "2024-12-19 13:16:04,564 - optimization.inference - INFO - Scan time: 0.9703\n", + "2024-12-19 13:16:04,564 - optimization.inference - INFO - Number of candidates by RT in frame 98: 69\n", + "2024-12-19 13:16:04,565 - optimization.inference - INFO - Number of candidates by RT in frame 184: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,572 - optimization.inference - INFO - Scan time: 0.9949\n", + "2024-12-19 13:16:04,572 - optimization.inference - INFO - Scan time: 27.8923\n", + "2024-12-19 13:16:04,572 - optimization.inference - INFO - Number of candidates by RT in frame 189: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,573 - optimization.inference - INFO - Number of candidates by RT in frame 1902: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,577 - optimization.inference - INFO - Scan time: 0.6743\n", + "2024-12-19 13:16:04,578 - optimization.inference - INFO - Number of candidates by RT in frame 103: 70\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,579 - optimization.inference - INFO - Scan time: 1.0099\n", + "2024-12-19 13:16:04,580 - optimization.inference - INFO - Number of candidates by RT in frame 194: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,587 - optimization.inference - INFO - Scan time: 1.034\n", + "2024-12-19 13:16:04,587 - optimization.inference - INFO - Number of candidates by RT in frame 199: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,591 - optimization.inference - INFO - Scan time: 0.6899\n", + "2024-12-19 13:16:04,592 - optimization.inference - INFO - Number of candidates by RT in frame 108: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,594 - optimization.inference - INFO - Scan time: 27.9778\n", + "2024-12-19 13:16:04,594 - optimization.inference - INFO - Scan time: 1.0538\n", + "2024-12-19 13:16:04,595 - optimization.inference - INFO - Number of candidates by RT in frame 1907: 267\n", + "2024-12-19 13:16:04,595 - optimization.inference - INFO - Number of candidates by RT in frame 204: 47\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,602 - optimization.inference - INFO - Scan time: 1.0727\n", + "2024-12-19 13:16:04,602 - optimization.inference - INFO - Number of candidates by RT in frame 209: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,604 - optimization.inference - INFO - Scan time: 0.7047\n", + "2024-12-19 13:16:04,605 - optimization.inference - INFO - Number of candidates by RT in frame 113: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,609 - optimization.inference - INFO - Scan time: 1.0903\n", + "2024-12-19 13:16:04,610 - optimization.inference - INFO - Number of candidates by RT in frame 214: 44\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,614 - optimization.inference - INFO - Scan time: 28.063\n", + "2024-12-19 13:16:04,616 - optimization.inference - INFO - Number of candidates by RT in frame 1912: 263\n", + "2024-12-19 13:16:04,617 - optimization.inference - INFO - Scan time: 1.1052\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,617 - optimization.inference - INFO - Number of candidates by RT in frame 219: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,618 - optimization.inference - INFO - Scan time: 0.7196\n", + "2024-12-19 13:16:04,619 - optimization.inference - INFO - Number of candidates by RT in frame 118: 66\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,624 - optimization.inference - INFO - Scan time: 1.1328\n", + "2024-12-19 13:16:04,625 - optimization.inference - INFO - Number of candidates by RT in frame 224: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,632 - optimization.inference - INFO - Scan time: 1.1582\n", + "2024-12-19 13:16:04,632 - optimization.inference - INFO - Scan time: 0.7445\n", + "2024-12-19 13:16:04,632 - optimization.inference - INFO - Number of candidates by RT in frame 229: 45\n", + "2024-12-19 13:16:04,633 - optimization.inference - INFO - Number of candidates by RT in frame 123: 63\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,639 - optimization.inference - INFO - Scan time: 1.1752\n", + "2024-12-19 13:16:04,640 - optimization.inference - INFO - Number of candidates by RT in frame 234: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,644 - optimization.inference - INFO - Scan time: 28.1488\n", + "2024-12-19 13:16:04,645 - optimization.inference - INFO - Number of candidates by RT in frame 1917: 251\n", + "2024-12-19 13:16:04,647 - optimization.inference - INFO - Scan time: 1.1929\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,648 - optimization.inference - INFO - Number of candidates by RT in frame 239: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,653 - optimization.inference - INFO - Scan time: 0.7647\n", + "2024-12-19 13:16:04,654 - optimization.inference - INFO - Number of candidates by RT in frame 128: 62\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,655 - optimization.inference - INFO - Scan time: 1.2062\n", + "2024-12-19 13:16:04,656 - optimization.inference - INFO - Number of candidates by RT in frame 244: 47\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,663 - optimization.inference - INFO - Scan time: 1.2218\n", + "2024-12-19 13:16:04,663 - optimization.inference - INFO - Number of candidates by RT in frame 249: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,666 - optimization.inference - INFO - Scan time: 0.7844\n", + "2024-12-19 13:16:04,668 - optimization.inference - INFO - Number of candidates by RT in frame 133: 59\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,670 - optimization.inference - INFO - Scan time: 1.2366\n", + "2024-12-19 13:16:04,671 - optimization.inference - INFO - Number of candidates by RT in frame 254: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,674 - optimization.inference - INFO - Scan time: 28.2341\n", + "2024-12-19 13:16:04,676 - optimization.inference - INFO - Number of candidates by RT in frame 1922: 252\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,678 - optimization.inference - INFO - Scan time: 1.2514\n", + "2024-12-19 13:16:04,679 - optimization.inference - INFO - Number of candidates by RT in frame 259: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,680 - optimization.inference - INFO - Scan time: 0.8042\n", + "2024-12-19 13:16:04,681 - optimization.inference - INFO - Number of candidates by RT in frame 138: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,686 - optimization.inference - INFO - Scan time: 1.2723\n", + "2024-12-19 13:16:04,686 - optimization.inference - INFO - Number of candidates by RT in frame 264: 49\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,693 - optimization.inference - INFO - Scan time: 0.8246\n", + "2024-12-19 13:16:04,694 - optimization.inference - INFO - Scan time: 1.2934\n", + "2024-12-19 13:16:04,694 - optimization.inference - INFO - Number of candidates by RT in frame 143: 55\n", + "2024-12-19 13:16:04,694 - optimization.inference - INFO - Number of candidates by RT in frame 269: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,701 - optimization.inference - INFO - Scan time: 1.3123\n", + "2024-12-19 13:16:04,702 - optimization.inference - INFO - Scan time: 28.3194\n", + "2024-12-19 13:16:04,702 - optimization.inference - INFO - Number of candidates by RT in frame 274: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,703 - optimization.inference - INFO - Number of candidates by RT in frame 1927: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,706 - optimization.inference - INFO - Scan time: 0.8461\n", + "2024-12-19 13:16:04,707 - optimization.inference - INFO - Number of candidates by RT in frame 148: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,709 - optimization.inference - INFO - Scan time: 1.3314\n", + "2024-12-19 13:16:04,710 - optimization.inference - INFO - Number of candidates by RT in frame 279: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,717 - optimization.inference - INFO - Scan time: 1.3502\n", + "2024-12-19 13:16:04,718 - optimization.inference - INFO - Number of candidates by RT in frame 284: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,719 - optimization.inference - INFO - Scan time: 0.8588\n", + "2024-12-19 13:16:04,720 - optimization.inference - INFO - Number of candidates by RT in frame 153: 55\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,725 - optimization.inference - INFO - Scan time: 1.3659\n", + "2024-12-19 13:16:04,725 - optimization.inference - INFO - Number of candidates by RT in frame 289: 51\n", + "2024-12-19 13:16:04,726 - optimization.inference - INFO - Scan time: 28.4048\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,727 - optimization.inference - INFO - Number of candidates by RT in frame 1932: 235\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,732 - optimization.inference - INFO - Scan time: 0.8762\n", + "2024-12-19 13:16:04,732 - optimization.inference - INFO - Scan time: 1.3834\n", + "2024-12-19 13:16:04,733 - optimization.inference - INFO - Number of candidates by RT in frame 158: 56\n", + "2024-12-19 13:16:04,733 - optimization.inference - INFO - Number of candidates by RT in frame 294: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,740 - optimization.inference - INFO - Scan time: 1.4005\n", + "2024-12-19 13:16:04,741 - optimization.inference - INFO - Number of candidates by RT in frame 299: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,745 - optimization.inference - INFO - Scan time: 0.8929\n", + "2024-12-19 13:16:04,746 - optimization.inference - INFO - Number of candidates by RT in frame 163: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,748 - optimization.inference - INFO - Scan time: 1.4182\n", + "2024-12-19 13:16:04,749 - optimization.inference - INFO - Number of candidates by RT in frame 304: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,750 - optimization.inference - INFO - Scan time: 28.4902\n", + "2024-12-19 13:16:04,753 - optimization.inference - INFO - Number of candidates by RT in frame 1937: 233\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,755 - optimization.inference - INFO - Scan time: 1.4358\n", + "2024-12-19 13:16:04,756 - optimization.inference - INFO - Number of candidates by RT in frame 309: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,759 - optimization.inference - INFO - Scan time: 0.9104\n", + "2024-12-19 13:16:04,760 - optimization.inference - INFO - Number of candidates by RT in frame 168: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,763 - optimization.inference - INFO - Scan time: 1.4528\n", + "2024-12-19 13:16:04,764 - optimization.inference - INFO - Number of candidates by RT in frame 314: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,771 - optimization.inference - INFO - Scan time: 1.4663\n", + "2024-12-19 13:16:04,771 - optimization.inference - INFO - Scan time: 0.9306\n", + "2024-12-19 13:16:04,772 - optimization.inference - INFO - Number of candidates by RT in frame 319: 51\n", + "2024-12-19 13:16:04,772 - optimization.inference - INFO - Number of candidates by RT in frame 173: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,777 - optimization.inference - INFO - Scan time: 28.5761\n", + "2024-12-19 13:16:04,778 - optimization.inference - INFO - Number of candidates by RT in frame 1942: 238\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,779 - optimization.inference - INFO - Scan time: 1.4826\n", + "2024-12-19 13:16:04,780 - optimization.inference - INFO - Number of candidates by RT in frame 324: 51\n", + "2024-12-19 13:16:04,780 - optimization.inference - INFO - Scan time: 0.951\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,781 - optimization.inference - INFO - Number of candidates by RT in frame 178: 57\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,787 - optimization.inference - INFO - Scan time: 1.4988\n", + "2024-12-19 13:16:04,788 - optimization.inference - INFO - Scan time: 0.968\n", + "2024-12-19 13:16:04,788 - optimization.inference - INFO - Number of candidates by RT in frame 329: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,789 - optimization.inference - INFO - Number of candidates by RT in frame 183: 56\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,795 - optimization.inference - INFO - Scan time: 1.5162\n", + "2024-12-19 13:16:04,796 - optimization.inference - INFO - Scan time: 0.9899\n", + "2024-12-19 13:16:04,796 - optimization.inference - INFO - Number of candidates by RT in frame 334: 52\n", + "2024-12-19 13:16:04,796 - optimization.inference - INFO - Number of candidates by RT in frame 188: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,801 - optimization.inference - INFO - Scan time: 28.6609\n", + "2024-12-19 13:16:04,803 - optimization.inference - INFO - Number of candidates by RT in frame 1947: 212\n", + "2024-12-19 13:16:04,803 - optimization.inference - INFO - Scan time: 1.5374\n", + "2024-12-19 13:16:04,803 - optimization.inference - INFO - Scan time: 1.0076\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,804 - optimization.inference - INFO - Number of candidates by RT in frame 339: 51\n", + "2024-12-19 13:16:04,804 - optimization.inference - INFO - Number of candidates by RT in frame 193: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,811 - optimization.inference - INFO - Scan time: 1.0296\n", + "2024-12-19 13:16:04,811 - optimization.inference - INFO - Scan time: 1.5537\n", + "2024-12-19 13:16:04,812 - optimization.inference - INFO - Number of candidates by RT in frame 198: 51\n", + "2024-12-19 13:16:04,812 - optimization.inference - INFO - Number of candidates by RT in frame 344: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,819 - optimization.inference - INFO - Scan time: 1.0515\n", + "2024-12-19 13:16:04,819 - optimization.inference - INFO - Scan time: 1.5749\n", + "2024-12-19 13:16:04,819 - optimization.inference - INFO - Number of candidates by RT in frame 203: 47\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,820 - optimization.inference - INFO - Number of candidates by RT in frame 349: 54\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,826 - optimization.inference - INFO - Scan time: 1.0683\n", + "2024-12-19 13:16:04,827 - optimization.inference - INFO - Number of candidates by RT in frame 208: 46\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,828 - optimization.inference - INFO - Scan time: 1.603\n", + "2024-12-19 13:16:04,828 - optimization.inference - INFO - Number of candidates by RT in frame 354: 56\n", + "2024-12-19 13:16:04,829 - optimization.inference - INFO - Scan time: 28.7462\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,830 - optimization.inference - INFO - Number of candidates by RT in frame 1952: 211\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,833 - optimization.inference - INFO - Scan time: 1.088\n", + "2024-12-19 13:16:04,834 - optimization.inference - INFO - Number of candidates by RT in frame 213: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,836 - optimization.inference - INFO - Scan time: 1.6449\n", + "2024-12-19 13:16:04,837 - optimization.inference - INFO - Number of candidates by RT in frame 359: 66\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,841 - optimization.inference - INFO - Scan time: 1.1008\n", + "2024-12-19 13:16:04,842 - optimization.inference - INFO - Number of candidates by RT in frame 218: 45\n", + "2024-12-19 13:16:04,842 - optimization.inference - INFO - Scan time: 1.6688\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,843 - optimization.inference - INFO - Number of candidates by RT in frame 364: 78\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,849 - optimization.inference - INFO - Scan time: 1.127\n", + "2024-12-19 13:16:04,849 - optimization.inference - INFO - Scan time: 1.699\n", + "2024-12-19 13:16:04,849 - optimization.inference - INFO - Number of candidates by RT in frame 223: 45\n", + "2024-12-19 13:16:04,850 - optimization.inference - INFO - Number of candidates by RT in frame 369: 89\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,853 - optimization.inference - INFO - Scan time: 28.832\n", + "2024-12-19 13:16:04,854 - optimization.inference - INFO - Number of candidates by RT in frame 1957: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,856 - optimization.inference - INFO - Scan time: 1.1523\n", + "2024-12-19 13:16:04,857 - optimization.inference - INFO - Number of candidates by RT in frame 228: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,858 - optimization.inference - INFO - Scan time: 1.7396\n", + "2024-12-19 13:16:04,859 - optimization.inference - INFO - Number of candidates by RT in frame 374: 113\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,864 - optimization.inference - INFO - Scan time: 1.1729\n", + "2024-12-19 13:16:04,865 - optimization.inference - INFO - Number of candidates by RT in frame 233: 45\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,868 - optimization.inference - INFO - Scan time: 1.8078\n", + "2024-12-19 13:16:04,869 - optimization.inference - INFO - Number of candidates by RT in frame 379: 125\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,871 - optimization.inference - INFO - Scan time: 28.918\n", + "2024-12-19 13:16:04,872 - optimization.inference - INFO - Number of candidates by RT in frame 1962: 203\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,877 - optimization.inference - INFO - Scan time: 1.1906\n", + "2024-12-19 13:16:04,878 - optimization.inference - INFO - Number of candidates by RT in frame 238: 46\n", + "2024-12-19 13:16:04,878 - optimization.inference - INFO - Scan time: 1.8934\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,879 - optimization.inference - INFO - Number of candidates by RT in frame 384: 129\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,885 - optimization.inference - INFO - Scan time: 1.2033\n", + "2024-12-19 13:16:04,886 - optimization.inference - INFO - Number of candidates by RT in frame 243: 47\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,889 - optimization.inference - INFO - Scan time: 1.9768\n", + "2024-12-19 13:16:04,890 - optimization.inference - INFO - Number of candidates by RT in frame 389: 109\n", + "2024-12-19 13:16:04,890 - optimization.inference - INFO - Scan time: 29.0037\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,891 - optimization.inference - INFO - Number of candidates by RT in frame 1967: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,893 - optimization.inference - INFO - Scan time: 1.2195\n", + "2024-12-19 13:16:04,894 - optimization.inference - INFO - Number of candidates by RT in frame 248: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,898 - optimization.inference - INFO - Scan time: 2.0345\n", + "2024-12-19 13:16:04,899 - optimization.inference - INFO - Number of candidates by RT in frame 394: 112\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,901 - optimization.inference - INFO - Scan time: 1.2329\n", + "2024-12-19 13:16:04,902 - optimization.inference - INFO - Number of candidates by RT in frame 253: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,907 - optimization.inference - INFO - Scan time: 2.1135\n", + "2024-12-19 13:16:04,907 - optimization.inference - INFO - Scan time: 29.0901\n", + "2024-12-19 13:16:04,908 - optimization.inference - INFO - Number of candidates by RT in frame 399: 102\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,909 - optimization.inference - INFO - Number of candidates by RT in frame 1972: 204\n", + "2024-12-19 13:16:04,909 - optimization.inference - INFO - Scan time: 1.2485\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,910 - optimization.inference - INFO - Number of candidates by RT in frame 258: 48\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,915 - optimization.inference - INFO - Scan time: 2.1904\n", + "2024-12-19 13:16:04,916 - optimization.inference - INFO - Number of candidates by RT in frame 404: 122\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,917 - optimization.inference - INFO - Scan time: 1.27\n", + "2024-12-19 13:16:04,918 - optimization.inference - INFO - Number of candidates by RT in frame 263: 49\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,920 - optimization.inference - INFO - Scan time: 29.1749\n", + "2024-12-19 13:16:04,921 - optimization.inference - INFO - Number of candidates by RT in frame 1977: 214\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,924 - optimization.inference - INFO - Scan time: 2.2699\n", + "2024-12-19 13:16:04,925 - optimization.inference - INFO - Number of candidates by RT in frame 409: 149\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,926 - optimization.inference - INFO - Scan time: 1.2883\n", + "2024-12-19 13:16:04,926 - optimization.inference - INFO - Number of candidates by RT in frame 268: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,934 - optimization.inference - INFO - Scan time: 1.3087\n", + "2024-12-19 13:16:04,935 - optimization.inference - INFO - Number of candidates by RT in frame 273: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,935 - optimization.inference - INFO - Scan time: 2.3554\n", + "2024-12-19 13:16:04,936 - optimization.inference - INFO - Number of candidates by RT in frame 414: 175\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,937 - optimization.inference - INFO - Scan time: 29.2601\n", + "2024-12-19 13:16:04,938 - optimization.inference - INFO - Number of candidates by RT in frame 1982: 211\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,942 - optimization.inference - INFO - Scan time: 1.3271\n", + "2024-12-19 13:16:04,943 - optimization.inference - INFO - Number of candidates by RT in frame 278: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,946 - optimization.inference - INFO - Scan time: 2.44\n", + "2024-12-19 13:16:04,947 - optimization.inference - INFO - Number of candidates by RT in frame 419: 187\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,950 - optimization.inference - INFO - Scan time: 1.3479\n", + "2024-12-19 13:16:04,951 - optimization.inference - INFO - Number of candidates by RT in frame 283: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,954 - optimization.inference - INFO - Scan time: 29.3454\n", + "2024-12-19 13:16:04,955 - optimization.inference - INFO - Number of candidates by RT in frame 1987: 210\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,958 - optimization.inference - INFO - Scan time: 1.3615\n", + "2024-12-19 13:16:04,958 - optimization.inference - INFO - Scan time: 2.5265\n", + "2024-12-19 13:16:04,959 - optimization.inference - INFO - Number of candidates by RT in frame 288: 51\n", + "2024-12-19 13:16:04,959 - optimization.inference - INFO - Number of candidates by RT in frame 424: 183\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,967 - optimization.inference - INFO - Scan time: 1.3811\n", + "2024-12-19 13:16:04,967 - optimization.inference - INFO - Number of candidates by RT in frame 293: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,968 - optimization.inference - INFO - Scan time: 29.4313\n", + "2024-12-19 13:16:04,969 - optimization.inference - INFO - Number of candidates by RT in frame 1992: 200\n", + "2024-12-19 13:16:04,969 - optimization.inference - INFO - Scan time: 2.6111\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,970 - optimization.inference - INFO - Number of candidates by RT in frame 429: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,975 - optimization.inference - INFO - Scan time: 1.3982\n", + "2024-12-19 13:16:04,975 - optimization.inference - INFO - Number of candidates by RT in frame 298: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,982 - optimization.inference - INFO - Scan time: 2.6967\n", + "2024-12-19 13:16:04,983 - optimization.inference - INFO - Scan time: 1.4131\n", + "2024-12-19 13:16:04,983 - optimization.inference - INFO - Number of candidates by RT in frame 434: 212\n", + "2024-12-19 13:16:04,983 - optimization.inference - INFO - Number of candidates by RT in frame 303: 54\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,986 - optimization.inference - INFO - Scan time: 29.5175\n", + "2024-12-19 13:16:04,987 - optimization.inference - INFO - Number of candidates by RT in frame 1997: 211\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,991 - optimization.inference - INFO - Scan time: 1.4329\n", + "2024-12-19 13:16:04,992 - optimization.inference - INFO - Number of candidates by RT in frame 308: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,995 - optimization.inference - INFO - Scan time: 2.7831\n", + "2024-12-19 13:16:04,996 - optimization.inference - INFO - Number of candidates by RT in frame 439: 225\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:04,999 - optimization.inference - INFO - Scan time: 1.4505\n", + "2024-12-19 13:16:05,000 - optimization.inference - INFO - Number of candidates by RT in frame 313: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,002 - optimization.inference - INFO - Scan time: 29.6029\n", + "2024-12-19 13:16:05,003 - optimization.inference - INFO - Number of candidates by RT in frame 2002: 212\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,008 - optimization.inference - INFO - Scan time: 1.4627\n", + "2024-12-19 13:16:05,008 - optimization.inference - INFO - Scan time: 2.8683\n", + "2024-12-19 13:16:05,008 - optimization.inference - INFO - Number of candidates by RT in frame 318: 52\n", + "2024-12-19 13:16:05,009 - optimization.inference - INFO - Number of candidates by RT in frame 444: 231\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,016 - optimization.inference - INFO - Scan time: 1.4803\n", + "2024-12-19 13:16:05,017 - optimization.inference - INFO - Number of candidates by RT in frame 323: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,021 - optimization.inference - INFO - Scan time: 2.9542\n", + "2024-12-19 13:16:05,021 - optimization.inference - INFO - Scan time: 29.6889\n", + "2024-12-19 13:16:05,022 - optimization.inference - INFO - Number of candidates by RT in frame 449: 232\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,023 - optimization.inference - INFO - Number of candidates by RT in frame 2007: 192\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,024 - optimization.inference - INFO - Scan time: 1.4965\n", + "2024-12-19 13:16:05,025 - optimization.inference - INFO - Number of candidates by RT in frame 328: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,033 - optimization.inference - INFO - Scan time: 1.5139\n", + "2024-12-19 13:16:05,034 - optimization.inference - INFO - Number of candidates by RT in frame 333: 53\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,035 - optimization.inference - INFO - Scan time: 3.0409\n", + "2024-12-19 13:16:05,036 - optimization.inference - INFO - Number of candidates by RT in frame 454: 224\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,038 - optimization.inference - INFO - Scan time: 29.7744\n", + "2024-12-19 13:16:05,039 - optimization.inference - INFO - Number of candidates by RT in frame 2012: 200\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,041 - optimization.inference - INFO - Scan time: 1.5309\n", + "2024-12-19 13:16:05,042 - optimization.inference - INFO - Number of candidates by RT in frame 338: 51\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,047 - optimization.inference - INFO - Scan time: 3.1267\n", + "2024-12-19 13:16:05,048 - optimization.inference - INFO - Number of candidates by RT in frame 459: 227\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,050 - optimization.inference - INFO - Scan time: 1.5514\n", + "2024-12-19 13:16:05,051 - optimization.inference - INFO - Number of candidates by RT in frame 343: 52\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,054 - optimization.inference - INFO - Scan time: 29.86\n", + "2024-12-19 13:16:05,055 - optimization.inference - INFO - Number of candidates by RT in frame 2017: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,059 - optimization.inference - INFO - Scan time: 1.5706\n", + "2024-12-19 13:16:05,060 - optimization.inference - INFO - Number of candidates by RT in frame 348: 54\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,060 - optimization.inference - INFO - Scan time: 3.2127\n", + "2024-12-19 13:16:05,061 - optimization.inference - INFO - Number of candidates by RT in frame 464: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,066 - optimization.inference - INFO - Scan time: 29.9463\n", + "2024-12-19 13:16:05,067 - optimization.inference - INFO - Number of candidates by RT in frame 2022: 209\n", + "2024-12-19 13:16:05,067 - optimization.inference - INFO - Scan time: 1.5964\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,068 - optimization.inference - INFO - Number of candidates by RT in frame 353: 58\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,074 - optimization.inference - INFO - Scan time: 3.2986\n", + "2024-12-19 13:16:05,075 - optimization.inference - INFO - Number of candidates by RT in frame 469: 223\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,076 - optimization.inference - INFO - Scan time: 1.6355\n", + "2024-12-19 13:16:05,077 - optimization.inference - INFO - Number of candidates by RT in frame 358: 64\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,082 - optimization.inference - INFO - Scan time: 1.6659\n", + "2024-12-19 13:16:05,083 - optimization.inference - INFO - Number of candidates by RT in frame 363: 73\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,086 - optimization.inference - INFO - Scan time: 30.0324\n", + "2024-12-19 13:16:05,086 - optimization.inference - INFO - Scan time: 3.3851\n", + "2024-12-19 13:16:05,087 - optimization.inference - INFO - Number of candidates by RT in frame 2027: 198\n", + "2024-12-19 13:16:05,087 - optimization.inference - INFO - Number of candidates by RT in frame 474: 214\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,090 - optimization.inference - INFO - Scan time: 1.6925\n", + "2024-12-19 13:16:05,091 - optimization.inference - INFO - Number of candidates by RT in frame 368: 88\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,100 - optimization.inference - INFO - Scan time: 1.7316\n", + "2024-12-19 13:16:05,101 - optimization.inference - INFO - Number of candidates by RT in frame 373: 101\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,102 - optimization.inference - INFO - Scan time: 3.4709\n", + "2024-12-19 13:16:05,103 - optimization.inference - INFO - Number of candidates by RT in frame 479: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,106 - optimization.inference - INFO - Scan time: 30.1183\n", + "2024-12-19 13:16:05,107 - optimization.inference - INFO - Number of candidates by RT in frame 2032: 194\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,112 - optimization.inference - INFO - Scan time: 3.557\n", + "2024-12-19 13:16:05,113 - optimization.inference - INFO - Number of candidates by RT in frame 484: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,115 - optimization.inference - INFO - Scan time: 1.7914\n", + "2024-12-19 13:16:05,116 - optimization.inference - INFO - Number of candidates by RT in frame 378: 121\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,120 - optimization.inference - INFO - Scan time: 30.2043\n", + "2024-12-19 13:16:05,121 - optimization.inference - INFO - Number of candidates by RT in frame 2037: 165\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,125 - optimization.inference - INFO - Scan time: 3.6427\n", + "2024-12-19 13:16:05,126 - optimization.inference - INFO - Scan time: 1.8761\n", + "2024-12-19 13:16:05,126 - optimization.inference - INFO - Number of candidates by RT in frame 489: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,127 - optimization.inference - INFO - Number of candidates by RT in frame 383: 126\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,133 - optimization.inference - INFO - Scan time: 30.2898\n", + "2024-12-19 13:16:05,135 - optimization.inference - INFO - Number of candidates by RT in frame 2042: 175\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,137 - optimization.inference - INFO - Scan time: 1.9604\n", + "2024-12-19 13:16:05,138 - optimization.inference - INFO - Number of candidates by RT in frame 388: 109\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,139 - optimization.inference - INFO - Scan time: 3.7282\n", + "2024-12-19 13:16:05,140 - optimization.inference - INFO - Number of candidates by RT in frame 494: 210\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,146 - optimization.inference - INFO - Scan time: 2.0273\n", + "2024-12-19 13:16:05,146 - optimization.inference - INFO - Number of candidates by RT in frame 393: 112\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,148 - optimization.inference - INFO - Scan time: 30.3762\n", + "2024-12-19 13:16:05,149 - optimization.inference - INFO - Number of candidates by RT in frame 2047: 188\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,152 - optimization.inference - INFO - Scan time: 3.8142\n", + "2024-12-19 13:16:05,153 - optimization.inference - INFO - Number of candidates by RT in frame 499: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,155 - optimization.inference - INFO - Scan time: 2.0984\n", + "2024-12-19 13:16:05,156 - optimization.inference - INFO - Number of candidates by RT in frame 398: 104\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,164 - optimization.inference - INFO - Scan time: 3.8994\n", + "2024-12-19 13:16:05,164 - optimization.inference - INFO - Number of candidates by RT in frame 504: 203\n", + "2024-12-19 13:16:05,165 - optimization.inference - INFO - Scan time: 2.1742\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,165 - optimization.inference - INFO - Number of candidates by RT in frame 403: 128\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,167 - optimization.inference - INFO - Scan time: 30.4623\n", + "2024-12-19 13:16:05,168 - optimization.inference - INFO - Number of candidates by RT in frame 2052: 212\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,175 - optimization.inference - INFO - Scan time: 3.9845\n", + "2024-12-19 13:16:05,175 - optimization.inference - INFO - Scan time: 2.2537\n", + "2024-12-19 13:16:05,176 - optimization.inference - INFO - Number of candidates by RT in frame 509: 182\n", + "2024-12-19 13:16:05,176 - optimization.inference - INFO - Number of candidates by RT in frame 408: 137\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,183 - optimization.inference - INFO - Scan time: 30.5483\n", + "2024-12-19 13:16:05,184 - optimization.inference - INFO - Number of candidates by RT in frame 2057: 223\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,186 - optimization.inference - INFO - Scan time: 2.338\n", + "2024-12-19 13:16:05,187 - optimization.inference - INFO - Number of candidates by RT in frame 413: 168\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,188 - optimization.inference - INFO - Scan time: 4.0707\n", + "2024-12-19 13:16:05,189 - optimization.inference - INFO - Number of candidates by RT in frame 514: 190\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,199 - optimization.inference - INFO - Scan time: 2.4226\n", + "2024-12-19 13:16:05,200 - optimization.inference - INFO - Scan time: 4.1564\n", + "2024-12-19 13:16:05,200 - optimization.inference - INFO - Number of candidates by RT in frame 418: 190\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,201 - optimization.inference - INFO - Scan time: 30.634\n", + "2024-12-19 13:16:05,201 - optimization.inference - INFO - Number of candidates by RT in frame 519: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,202 - optimization.inference - INFO - Number of candidates by RT in frame 2062: 222\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,211 - optimization.inference - INFO - Scan time: 4.2418\n", + "2024-12-19 13:16:05,212 - optimization.inference - INFO - Number of candidates by RT in frame 524: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,213 - optimization.inference - INFO - Scan time: 2.509\n", + "2024-12-19 13:16:05,216 - optimization.inference - INFO - Scan time: 30.7188\n", + "2024-12-19 13:16:05,214 - optimization.inference - INFO - Number of candidates by RT in frame 423: 186\n", + "2024-12-19 13:16:05,218 - optimization.inference - INFO - Number of candidates by RT in frame 2067: 214\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,227 - optimization.inference - INFO - Scan time: 4.3279\n", + "2024-12-19 13:16:05,228 - optimization.inference - INFO - Number of candidates by RT in frame 529: 213\n", + "2024-12-19 13:16:05,228 - optimization.inference - INFO - Scan time: 2.595\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,229 - optimization.inference - INFO - Number of candidates by RT in frame 428: 201\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,234 - optimization.inference - INFO - Scan time: 30.8042\n", + "2024-12-19 13:16:05,235 - optimization.inference - INFO - Number of candidates by RT in frame 2072: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,241 - optimization.inference - INFO - Scan time: 4.4132\n", + "2024-12-19 13:16:05,242 - optimization.inference - INFO - Scan time: 2.6795\n", + "2024-12-19 13:16:05,243 - optimization.inference - INFO - Number of candidates by RT in frame 534: 206\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,243 - optimization.inference - INFO - Number of candidates by RT in frame 433: 208\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,252 - optimization.inference - INFO - Scan time: 30.8907\n", + "2024-12-19 13:16:05,254 - optimization.inference - INFO - Number of candidates by RT in frame 2077: 190\n", + "2024-12-19 13:16:05,254 - optimization.inference - INFO - Scan time: 2.7658\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,255 - optimization.inference - INFO - Number of candidates by RT in frame 438: 225\n", + "2024-12-19 13:16:05,255 - optimization.inference - INFO - Scan time: 4.4978\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,256 - optimization.inference - INFO - Number of candidates by RT in frame 539: 196\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,266 - optimization.inference - INFO - Scan time: 2.851\n", + "2024-12-19 13:16:05,266 - optimization.inference - INFO - Scan time: 30.9756\n", + "2024-12-19 13:16:05,267 - optimization.inference - INFO - Number of candidates by RT in frame 443: 227\n", + "2024-12-19 13:16:05,267 - optimization.inference - INFO - Number of candidates by RT in frame 2082: 201\n", + "2024-12-19 13:16:05,268 - optimization.inference - INFO - Scan time: 4.5831\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,268 - optimization.inference - INFO - Number of candidates by RT in frame 544: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,279 - optimization.inference - INFO - Scan time: 4.6695\n", + "2024-12-19 13:16:05,280 - optimization.inference - INFO - Number of candidates by RT in frame 549: 211\n", + "2024-12-19 13:16:05,280 - optimization.inference - INFO - Scan time: 2.9371\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,281 - optimization.inference - INFO - Number of candidates by RT in frame 448: 225\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,284 - optimization.inference - INFO - Scan time: 31.0615\n", + "2024-12-19 13:16:05,285 - optimization.inference - INFO - Number of candidates by RT in frame 2087: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,291 - optimization.inference - INFO - Scan time: 4.7548\n", + "2024-12-19 13:16:05,292 - optimization.inference - INFO - Number of candidates by RT in frame 554: 212\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,295 - optimization.inference - INFO - Scan time: 3.0236\n", + "2024-12-19 13:16:05,296 - optimization.inference - INFO - Number of candidates by RT in frame 453: 227\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,300 - optimization.inference - INFO - Scan time: 31.1474\n", + "2024-12-19 13:16:05,301 - optimization.inference - INFO - Number of candidates by RT in frame 2092: 208\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,304 - optimization.inference - INFO - Scan time: 4.8408\n", + "2024-12-19 13:16:05,305 - optimization.inference - INFO - Number of candidates by RT in frame 559: 228\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,309 - optimization.inference - INFO - Scan time: 3.1093\n", + "2024-12-19 13:16:05,310 - optimization.inference - INFO - Number of candidates by RT in frame 458: 228\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,314 - optimization.inference - INFO - Scan time: 4.9266\n", + "2024-12-19 13:16:05,315 - optimization.inference - INFO - Number of candidates by RT in frame 564: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,316 - optimization.inference - INFO - Scan time: 31.2331\n", + "2024-12-19 13:16:05,317 - optimization.inference - INFO - Number of candidates by RT in frame 2097: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,327 - optimization.inference - INFO - Scan time: 5.013\n", + "2024-12-19 13:16:05,328 - optimization.inference - INFO - Number of candidates by RT in frame 569: 227\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,331 - optimization.inference - INFO - Scan time: 3.1955\n", + "2024-12-19 13:16:05,333 - optimization.inference - INFO - Number of candidates by RT in frame 463: 224\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,335 - optimization.inference - INFO - Scan time: 31.3186\n", + "2024-12-19 13:16:05,336 - optimization.inference - INFO - Number of candidates by RT in frame 2102: 208\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,344 - optimization.inference - INFO - Scan time: 5.0993\n", + "2024-12-19 13:16:05,345 - optimization.inference - INFO - Number of candidates by RT in frame 574: 238\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,348 - optimization.inference - INFO - Scan time: 3.2817\n", + "2024-12-19 13:16:05,349 - optimization.inference - INFO - Number of candidates by RT in frame 468: 228\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,352 - optimization.inference - INFO - Scan time: 31.4047\n", + "2024-12-19 13:16:05,353 - optimization.inference - INFO - Number of candidates by RT in frame 2107: 193\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,359 - optimization.inference - INFO - Scan time: 3.3677\n", + "2024-12-19 13:16:05,360 - optimization.inference - INFO - Number of candidates by RT in frame 473: 216\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,361 - optimization.inference - INFO - Scan time: 5.1855\n", + "2024-12-19 13:16:05,362 - optimization.inference - INFO - Number of candidates by RT in frame 579: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,375 - optimization.inference - INFO - Scan time: 31.4905\n", + "2024-12-19 13:16:05,376 - optimization.inference - INFO - Scan time: 5.2718\n", + "2024-12-19 13:16:05,376 - optimization.inference - INFO - Number of candidates by RT in frame 2112: 195\n", + "2024-12-19 13:16:05,376 - optimization.inference - INFO - Scan time: 3.4537\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,377 - optimization.inference - INFO - Number of candidates by RT in frame 584: 232\n", + "2024-12-19 13:16:05,377 - optimization.inference - INFO - Number of candidates by RT in frame 478: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,387 - optimization.inference - INFO - Scan time: 3.5398\n", + "2024-12-19 13:16:05,388 - optimization.inference - INFO - Number of candidates by RT in frame 483: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,392 - optimization.inference - INFO - Scan time: 5.3582\n", + "2024-12-19 13:16:05,393 - optimization.inference - INFO - Number of candidates by RT in frame 589: 239\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,397 - optimization.inference - INFO - Scan time: 31.576\n", + "2024-12-19 13:16:05,398 - optimization.inference - INFO - Number of candidates by RT in frame 2117: 174\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,400 - optimization.inference - INFO - Scan time: 3.626\n", + "2024-12-19 13:16:05,401 - optimization.inference - INFO - Number of candidates by RT in frame 488: 216\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,405 - optimization.inference - INFO - Scan time: 5.4444\n", + "2024-12-19 13:16:05,406 - optimization.inference - INFO - Number of candidates by RT in frame 594: 230\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,414 - optimization.inference - INFO - Scan time: 3.711\n", + "2024-12-19 13:16:05,414 - optimization.inference - INFO - Scan time: 31.6615\n", + "2024-12-19 13:16:05,415 - optimization.inference - INFO - Number of candidates by RT in frame 493: 213\n", + "2024-12-19 13:16:05,415 - optimization.inference - INFO - Number of candidates by RT in frame 2122: 146\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,419 - optimization.inference - INFO - Scan time: 5.531\n", + "2024-12-19 13:16:05,420 - optimization.inference - INFO - Number of candidates by RT in frame 599: 238\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,428 - optimization.inference - INFO - Scan time: 31.7475\n", + "2024-12-19 13:16:05,428 - optimization.inference - INFO - Scan time: 3.7971\n", + "2024-12-19 13:16:05,429 - optimization.inference - INFO - Number of candidates by RT in frame 2127: 129\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,429 - optimization.inference - INFO - Number of candidates by RT in frame 498: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,433 - optimization.inference - INFO - Scan time: 5.6172\n", + "2024-12-19 13:16:05,434 - optimization.inference - INFO - Number of candidates by RT in frame 604: 236\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,439 - optimization.inference - INFO - Scan time: 31.833\n", + "2024-12-19 13:16:05,440 - optimization.inference - INFO - Number of candidates by RT in frame 2132: 125\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,441 - optimization.inference - INFO - Scan time: 3.8824\n", + "2024-12-19 13:16:05,442 - optimization.inference - INFO - Number of candidates by RT in frame 503: 204\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,446 - optimization.inference - INFO - Scan time: 5.7027\n", + "2024-12-19 13:16:05,447 - optimization.inference - INFO - Number of candidates by RT in frame 609: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,450 - optimization.inference - INFO - Scan time: 31.9191\n", + "2024-12-19 13:16:05,451 - optimization.inference - INFO - Number of candidates by RT in frame 2137: 91\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,458 - optimization.inference - INFO - Scan time: 3.9676\n", + "2024-12-19 13:16:05,458 - optimization.inference - INFO - Scan time: 5.7887\n", + "2024-12-19 13:16:05,459 - optimization.inference - INFO - Number of candidates by RT in frame 508: 188\n", + "2024-12-19 13:16:05,459 - optimization.inference - INFO - Number of candidates by RT in frame 614: 238\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,463 - optimization.inference - INFO - Scan time: 32.0051\n", + "2024-12-19 13:16:05,464 - optimization.inference - INFO - Number of candidates by RT in frame 2142: 50\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,470 - optimization.inference - INFO - Scan time: 4.0537\n", + "2024-12-19 13:16:05,472 - optimization.inference - INFO - Number of candidates by RT in frame 513: 182\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,473 - optimization.inference - INFO - Scan time: 5.8752\n", + "2024-12-19 13:16:05,474 - optimization.inference - INFO - Number of candidates by RT in frame 619: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,478 - optimization.inference - INFO - Scan time: 32.091\n", + "2024-12-19 13:16:05,479 - optimization.inference - INFO - Number of candidates by RT in frame 2147: 22\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,484 - optimization.inference - INFO - Scan time: 4.1397\n", + "2024-12-19 13:16:05,485 - optimization.inference - INFO - Number of candidates by RT in frame 518: 195\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,486 - optimization.inference - INFO - Scan time: 5.9616\n", + "2024-12-19 13:16:05,487 - optimization.inference - INFO - Number of candidates by RT in frame 624: 234\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,492 - optimization.inference - INFO - Scan time: 32.1577\n", + "2024-12-19 13:16:05,493 - optimization.inference - INFO - Number of candidates by RT in frame 2152: 18\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,496 - optimization.inference - INFO - Scan time: 4.2249\n", + "2024-12-19 13:16:05,497 - optimization.inference - INFO - Number of candidates by RT in frame 523: 201\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,499 - optimization.inference - INFO - Scan time: 6.0471\n", + "2024-12-19 13:16:05,500 - optimization.inference - INFO - Number of candidates by RT in frame 629: 240\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,506 - optimization.inference - INFO - Scan time: 32.19\n", + "2024-12-19 13:16:05,506 - optimization.inference - INFO - Number of candidates by RT in frame 2157: 16\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,512 - optimization.inference - INFO - Scan time: 6.1324\n", + "2024-12-19 13:16:05,512 - optimization.inference - INFO - Scan time: 4.3109\n", + "2024-12-19 13:16:05,513 - optimization.inference - INFO - Number of candidates by RT in frame 634: 244\n", + "2024-12-19 13:16:05,513 - optimization.inference - INFO - Number of candidates by RT in frame 528: 210\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,517 - optimization.inference - INFO - Scan time: 32.2071\n", + "2024-12-19 13:16:05,517 - optimization.inference - INFO - Number of candidates by RT in frame 2162: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,525 - optimization.inference - INFO - Scan time: 6.2187\n", + "2024-12-19 13:16:05,526 - optimization.inference - INFO - Number of candidates by RT in frame 639: 245\n", + "2024-12-19 13:16:05,526 - optimization.inference - INFO - Scan time: 4.396\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,527 - optimization.inference - INFO - Number of candidates by RT in frame 533: 206\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,529 - optimization.inference - INFO - Scan time: 32.227\n", + "2024-12-19 13:16:05,530 - optimization.inference - INFO - Number of candidates by RT in frame 2167: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,539 - optimization.inference - INFO - Scan time: 32.2475\n", + "2024-12-19 13:16:05,540 - optimization.inference - INFO - Number of candidates by RT in frame 2172: 13\n", + "2024-12-19 13:16:05,540 - optimization.inference - INFO - Scan time: 4.4811\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,541 - optimization.inference - INFO - Scan time: 6.3053\n", + "2024-12-19 13:16:05,541 - optimization.inference - INFO - Number of candidates by RT in frame 538: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,542 - optimization.inference - INFO - Number of candidates by RT in frame 644: 257\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,551 - optimization.inference - INFO - Scan time: 32.2739\n", + "2024-12-19 13:16:05,552 - optimization.inference - INFO - Number of candidates by RT in frame 2177: 12\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,553 - optimization.inference - INFO - Scan time: 4.5662\n", + "2024-12-19 13:16:05,553 - optimization.inference - INFO - Scan time: 6.3922\n", + "2024-12-19 13:16:05,554 - optimization.inference - INFO - Number of candidates by RT in frame 543: 211\n", + "2024-12-19 13:16:05,554 - optimization.inference - INFO - Number of candidates by RT in frame 649: 229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,564 - optimization.inference - INFO - Scan time: 32.2904\n", + "2024-12-19 13:16:05,564 - optimization.inference - INFO - Number of candidates by RT in frame 2182: 11\n", + "2024-12-19 13:16:05,565 - optimization.inference - INFO - Scan time: 4.652\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,566 - optimization.inference - INFO - Number of candidates by RT in frame 548: 213\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,568 - optimization.inference - INFO - Scan time: 6.4787\n", + "2024-12-19 13:16:05,569 - optimization.inference - INFO - Number of candidates by RT in frame 654: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,576 - optimization.inference - INFO - Scan time: 32.304\n", + "2024-12-19 13:16:05,577 - optimization.inference - INFO - Number of candidates by RT in frame 2187: 11\n", + "2024-12-19 13:16:05,577 - optimization.inference - INFO - Scan time: 4.7378\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,578 - optimization.inference - INFO - Number of candidates by RT in frame 553: 216\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,582 - optimization.inference - INFO - Scan time: 6.5656\n", + "2024-12-19 13:16:05,583 - optimization.inference - INFO - Number of candidates by RT in frame 659: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,588 - optimization.inference - INFO - Scan time: 32.3191\n", + "2024-12-19 13:16:05,589 - optimization.inference - INFO - Number of candidates by RT in frame 2192: 10\n", + "2024-12-19 13:16:05,590 - optimization.inference - INFO - Scan time: 4.8239\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,591 - optimization.inference - INFO - Number of candidates by RT in frame 558: 224\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,599 - optimization.inference - INFO - Scan time: 6.651\n", + "2024-12-19 13:16:05,600 - optimization.inference - INFO - Number of candidates by RT in frame 664: 240\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,601 - optimization.inference - INFO - Scan time: 4.9097\n", + "2024-12-19 13:16:05,601 - optimization.inference - INFO - Scan time: 32.3366\n", + "2024-12-19 13:16:05,602 - optimization.inference - INFO - Number of candidates by RT in frame 2197: 10\n", + "2024-12-19 13:16:05,602 - optimization.inference - INFO - Number of candidates by RT in frame 563: 234\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,611 - optimization.inference - INFO - Scan time: 6.7358\n", + "2024-12-19 13:16:05,612 - optimization.inference - INFO - Scan time: 32.3503\n", + "2024-12-19 13:16:05,612 - optimization.inference - INFO - Number of candidates by RT in frame 669: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,613 - optimization.inference - INFO - Number of candidates by RT in frame 2202: 10\n", + "2024-12-19 13:16:05,613 - optimization.inference - INFO - Scan time: 4.9956\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,614 - optimization.inference - INFO - Number of candidates by RT in frame 568: 224\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,622 - optimization.inference - INFO - Scan time: 32.3772\n", + "2024-12-19 13:16:05,623 - optimization.inference - INFO - Number of candidates by RT in frame 2207: 9\n", + "2024-12-19 13:16:05,624 - optimization.inference - INFO - Scan time: 6.822\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,625 - optimization.inference - INFO - Number of candidates by RT in frame 674: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,631 - optimization.inference - INFO - Scan time: 5.0825\n", + "2024-12-19 13:16:05,632 - optimization.inference - INFO - Number of candidates by RT in frame 573: 235\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,634 - optimization.inference - INFO - Scan time: 32.3963\n", + "2024-12-19 13:16:05,635 - optimization.inference - INFO - Number of candidates by RT in frame 2212: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,638 - optimization.inference - INFO - Scan time: 6.9079\n", + "2024-12-19 13:16:05,639 - optimization.inference - INFO - Number of candidates by RT in frame 679: 256\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,645 - optimization.inference - INFO - Scan time: 5.1681\n", + "2024-12-19 13:16:05,646 - optimization.inference - INFO - Scan time: 32.4125\n", + "2024-12-19 13:16:05,646 - optimization.inference - INFO - Number of candidates by RT in frame 578: 231\n", + "2024-12-19 13:16:05,646 - optimization.inference - INFO - Number of candidates by RT in frame 2217: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,653 - optimization.inference - INFO - Scan time: 6.9946\n", + "2024-12-19 13:16:05,654 - optimization.inference - INFO - Number of candidates by RT in frame 684: 234\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,657 - optimization.inference - INFO - Scan time: 32.4289\n", + "2024-12-19 13:16:05,658 - optimization.inference - INFO - Number of candidates by RT in frame 2222: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,665 - optimization.inference - INFO - Scan time: 5.2543\n", + "2024-12-19 13:16:05,665 - optimization.inference - INFO - Scan time: 7.0805\n", + "2024-12-19 13:16:05,666 - optimization.inference - INFO - Number of candidates by RT in frame 583: 226\n", + "2024-12-19 13:16:05,666 - optimization.inference - INFO - Number of candidates by RT in frame 689: 237\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,668 - optimization.inference - INFO - Scan time: 32.4423\n", + "2024-12-19 13:16:05,668 - optimization.inference - INFO - Number of candidates by RT in frame 2227: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,677 - optimization.inference - INFO - Scan time: 32.4552\n", + "2024-12-19 13:16:05,678 - optimization.inference - INFO - Number of candidates by RT in frame 2232: 6\n", + "2024-12-19 13:16:05,678 - optimization.inference - INFO - Scan time: 7.1659\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,679 - optimization.inference - INFO - Scan time: 5.3411\n", + "2024-12-19 13:16:05,679 - optimization.inference - INFO - Number of candidates by RT in frame 694: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,680 - optimization.inference - INFO - Number of candidates by RT in frame 588: 238\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,686 - optimization.inference - INFO - Scan time: 32.4673\n", + "2024-12-19 13:16:05,686 - optimization.inference - INFO - Number of candidates by RT in frame 2237: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,692 - optimization.inference - INFO - Scan time: 5.4269\n", + "2024-12-19 13:16:05,693 - optimization.inference - INFO - Number of candidates by RT in frame 593: 234\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,696 - optimization.inference - INFO - Scan time: 32.4808\n", + "2024-12-19 13:16:05,697 - optimization.inference - INFO - Number of candidates by RT in frame 2242: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,698 - optimization.inference - INFO - Scan time: 7.2506\n", + "2024-12-19 13:16:05,699 - optimization.inference - INFO - Number of candidates by RT in frame 699: 248\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,707 - optimization.inference - INFO - Scan time: 32.493\n", + "2024-12-19 13:16:05,707 - optimization.inference - INFO - Scan time: 5.5136\n", + "2024-12-19 13:16:05,708 - optimization.inference - INFO - Number of candidates by RT in frame 2247: 5\n", + "2024-12-19 13:16:05,708 - optimization.inference - INFO - Number of candidates by RT in frame 598: 238\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,713 - optimization.inference - INFO - Scan time: 7.3366\n", + "2024-12-19 13:16:05,714 - optimization.inference - INFO - Number of candidates by RT in frame 704: 259\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,718 - optimization.inference - INFO - Scan time: 32.5087\n", + "2024-12-19 13:16:05,719 - optimization.inference - INFO - Number of candidates by RT in frame 2252: 4\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,721 - optimization.inference - INFO - Scan time: 5.6001\n", + "2024-12-19 13:16:05,722 - optimization.inference - INFO - Number of candidates by RT in frame 603: 238\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,724 - optimization.inference - INFO - Scan time: 7.4219\n", + "2024-12-19 13:16:05,725 - optimization.inference - INFO - Number of candidates by RT in frame 709: 258\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,728 - optimization.inference - INFO - Scan time: 32.5257\n", + "2024-12-19 13:16:05,729 - optimization.inference - INFO - Number of candidates by RT in frame 2257: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,736 - optimization.inference - INFO - Scan time: 5.6859\n", + "2024-12-19 13:16:05,737 - optimization.inference - INFO - Number of candidates by RT in frame 608: 245\n", + "2024-12-19 13:16:05,737 - optimization.inference - INFO - Scan time: 32.5424\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,738 - optimization.inference - INFO - Number of candidates by RT in frame 2262: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,740 - optimization.inference - INFO - Scan time: 7.5085\n", + "2024-12-19 13:16:05,741 - optimization.inference - INFO - Number of candidates by RT in frame 714: 252\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,747 - optimization.inference - INFO - Scan time: 32.5586\n", + "2024-12-19 13:16:05,748 - optimization.inference - INFO - Number of candidates by RT in frame 2267: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,749 - optimization.inference - INFO - Scan time: 5.7717\n", + "2024-12-19 13:16:05,750 - optimization.inference - INFO - Number of candidates by RT in frame 613: 240\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,755 - optimization.inference - INFO - Scan time: 7.5942\n", + "2024-12-19 13:16:05,756 - optimization.inference - INFO - Number of candidates by RT in frame 719: 252\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,757 - optimization.inference - INFO - Scan time: 32.5762\n", + "2024-12-19 13:16:05,758 - optimization.inference - INFO - Number of candidates by RT in frame 2272: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,763 - optimization.inference - INFO - Scan time: 5.8579\n", + "2024-12-19 13:16:05,764 - optimization.inference - INFO - Number of candidates by RT in frame 618: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,767 - optimization.inference - INFO - Scan time: 7.6797\n", + "2024-12-19 13:16:05,767 - optimization.inference - INFO - Scan time: 32.5891\n", + "2024-12-19 13:16:05,768 - optimization.inference - INFO - Number of candidates by RT in frame 724: 259\n", + "2024-12-19 13:16:05,768 - optimization.inference - INFO - Number of candidates by RT in frame 2277: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,776 - optimization.inference - INFO - Scan time: 32.602\n", + "2024-12-19 13:16:05,777 - optimization.inference - INFO - Scan time: 5.9441\n", + "2024-12-19 13:16:05,777 - optimization.inference - INFO - Number of candidates by RT in frame 2282: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,778 - optimization.inference - INFO - Number of candidates by RT in frame 623: 230\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,782 - optimization.inference - INFO - Scan time: 7.766\n", + "2024-12-19 13:16:05,783 - optimization.inference - INFO - Number of candidates by RT in frame 729: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,785 - optimization.inference - INFO - Scan time: 32.6162\n", + "2024-12-19 13:16:05,786 - optimization.inference - INFO - Number of candidates by RT in frame 2287: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,790 - optimization.inference - INFO - Scan time: 6.0303\n", + "2024-12-19 13:16:05,791 - optimization.inference - INFO - Number of candidates by RT in frame 628: 233\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,794 - optimization.inference - INFO - Scan time: 32.6305\n", + "2024-12-19 13:16:05,794 - optimization.inference - INFO - Number of candidates by RT in frame 2292: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,797 - optimization.inference - INFO - Scan time: 7.8517\n", + "2024-12-19 13:16:05,798 - optimization.inference - INFO - Number of candidates by RT in frame 734: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,803 - optimization.inference - INFO - Scan time: 32.6473\n", + "2024-12-19 13:16:05,803 - optimization.inference - INFO - Number of candidates by RT in frame 2297: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,805 - optimization.inference - INFO - Scan time: 6.1152\n", + "2024-12-19 13:16:05,806 - optimization.inference - INFO - Number of candidates by RT in frame 633: 249\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,811 - optimization.inference - INFO - Scan time: 32.6628\n", + "2024-12-19 13:16:05,812 - optimization.inference - INFO - Number of candidates by RT in frame 2302: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,813 - optimization.inference - INFO - Scan time: 7.9375\n", + "2024-12-19 13:16:05,814 - optimization.inference - INFO - Number of candidates by RT in frame 739: 284\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,818 - optimization.inference - INFO - Scan time: 6.2013\n", + "2024-12-19 13:16:05,819 - optimization.inference - INFO - Number of candidates by RT in frame 638: 237\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,820 - optimization.inference - INFO - Scan time: 32.6785\n", + "2024-12-19 13:16:05,820 - optimization.inference - INFO - Number of candidates by RT in frame 2307: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,827 - optimization.inference - INFO - Scan time: 8.0225\n", + "2024-12-19 13:16:05,828 - optimization.inference - INFO - Scan time: 32.6954\n", + "2024-12-19 13:16:05,828 - optimization.inference - INFO - Number of candidates by RT in frame 744: 263\n", + "2024-12-19 13:16:05,829 - optimization.inference - INFO - Number of candidates by RT in frame 2312: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,834 - optimization.inference - INFO - Scan time: 6.2883\n", + "2024-12-19 13:16:05,835 - optimization.inference - INFO - Number of candidates by RT in frame 643: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,836 - optimization.inference - INFO - Scan time: 32.7069\n", + "2024-12-19 13:16:05,837 - optimization.inference - INFO - Number of candidates by RT in frame 2317: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,843 - optimization.inference - INFO - Scan time: 8.1086\n", + "2024-12-19 13:16:05,844 - optimization.inference - INFO - Number of candidates by RT in frame 749: 255\n", + "2024-12-19 13:16:05,845 - optimization.inference - INFO - Scan time: 32.7229\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,846 - optimization.inference - INFO - Number of candidates by RT in frame 2322: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,847 - optimization.inference - INFO - Scan time: 6.3749\n", + "2024-12-19 13:16:05,848 - optimization.inference - INFO - Number of candidates by RT in frame 648: 236\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,853 - optimization.inference - INFO - Scan time: 32.7379\n", + "2024-12-19 13:16:05,854 - optimization.inference - INFO - Number of candidates by RT in frame 2327: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,860 - optimization.inference - INFO - Scan time: 8.1937\n", + "2024-12-19 13:16:05,861 - optimization.inference - INFO - Number of candidates by RT in frame 754: 252\n", + "2024-12-19 13:16:05,861 - optimization.inference - INFO - Scan time: 32.7518\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,862 - optimization.inference - INFO - Number of candidates by RT in frame 2332: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,862 - optimization.inference - INFO - Scan time: 6.4616\n", + "2024-12-19 13:16:05,863 - optimization.inference - INFO - Number of candidates by RT in frame 653: 244\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,870 - optimization.inference - INFO - Scan time: 32.7726\n", + "2024-12-19 13:16:05,870 - optimization.inference - INFO - Number of candidates by RT in frame 2337: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,875 - optimization.inference - INFO - Scan time: 8.2802\n", + "2024-12-19 13:16:05,876 - optimization.inference - INFO - Number of candidates by RT in frame 759: 253\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,877 - optimization.inference - INFO - Scan time: 32.7868\n", + "2024-12-19 13:16:05,878 - optimization.inference - INFO - Number of candidates by RT in frame 2342: 2\n", + "2024-12-19 13:16:05,879 - optimization.inference - INFO - Scan time: 6.5481\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,880 - optimization.inference - INFO - Number of candidates by RT in frame 658: 245\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,884 - optimization.inference - INFO - Scan time: 32.801\n", + "2024-12-19 13:16:05,885 - optimization.inference - INFO - Number of candidates by RT in frame 2347: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,890 - optimization.inference - INFO - Scan time: 8.3658\n", + "2024-12-19 13:16:05,891 - optimization.inference - INFO - Number of candidates by RT in frame 764: 249\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,892 - optimization.inference - INFO - Scan time: 32.8173\n", + "2024-12-19 13:16:05,893 - optimization.inference - INFO - Number of candidates by RT in frame 2352: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,893 - optimization.inference - INFO - Scan time: 6.6338\n", + "2024-12-19 13:16:05,894 - optimization.inference - INFO - Number of candidates by RT in frame 663: 237\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,900 - optimization.inference - INFO - Scan time: 32.834\n", + "2024-12-19 13:16:05,901 - optimization.inference - INFO - Number of candidates by RT in frame 2357: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,907 - optimization.inference - INFO - Scan time: 6.7189\n", + "2024-12-19 13:16:05,908 - optimization.inference - INFO - Number of candidates by RT in frame 668: 239\n", + "2024-12-19 13:16:05,908 - optimization.inference - INFO - Scan time: 32.8461\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,909 - optimization.inference - INFO - Number of candidates by RT in frame 2362: 2\n", + "2024-12-19 13:16:05,909 - optimization.inference - INFO - Scan time: 8.451\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,910 - optimization.inference - INFO - Number of candidates by RT in frame 769: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,916 - optimization.inference - INFO - Scan time: 32.8617\n", + "2024-12-19 13:16:05,916 - optimization.inference - INFO - Number of candidates by RT in frame 2367: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,919 - optimization.inference - INFO - Scan time: 6.8049\n", + "2024-12-19 13:16:05,920 - optimization.inference - INFO - Number of candidates by RT in frame 673: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,923 - optimization.inference - INFO - Scan time: 32.8745\n", + "2024-12-19 13:16:05,924 - optimization.inference - INFO - Scan time: 8.5363\n", + "2024-12-19 13:16:05,924 - optimization.inference - INFO - Number of candidates by RT in frame 2372: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,925 - optimization.inference - INFO - Number of candidates by RT in frame 774: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,931 - optimization.inference - INFO - Scan time: 32.886\n", + "2024-12-19 13:16:05,931 - optimization.inference - INFO - Number of candidates by RT in frame 2377: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,934 - optimization.inference - INFO - Scan time: 6.8911\n", + "2024-12-19 13:16:05,935 - optimization.inference - INFO - Number of candidates by RT in frame 678: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,938 - optimization.inference - INFO - Scan time: 32.9035\n", + "2024-12-19 13:16:05,939 - optimization.inference - INFO - Number of candidates by RT in frame 2382: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,942 - optimization.inference - INFO - Scan time: 8.6222\n", + "2024-12-19 13:16:05,943 - optimization.inference - INFO - Number of candidates by RT in frame 779: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,946 - optimization.inference - INFO - Scan time: 32.9162\n", + "2024-12-19 13:16:05,947 - optimization.inference - INFO - Number of candidates by RT in frame 2387: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,948 - optimization.inference - INFO - Scan time: 6.9773\n", + "2024-12-19 13:16:05,949 - optimization.inference - INFO - Number of candidates by RT in frame 683: 226\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,954 - optimization.inference - INFO - Scan time: 32.9301\n", + "2024-12-19 13:16:05,955 - optimization.inference - INFO - Number of candidates by RT in frame 2392: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,961 - optimization.inference - INFO - Scan time: 7.0634\n", + "2024-12-19 13:16:05,961 - optimization.inference - INFO - Scan time: 8.7078\n", + "2024-12-19 13:16:05,961 - optimization.inference - INFO - Scan time: 32.9422\n", + "2024-12-19 13:16:05,962 - optimization.inference - INFO - Number of candidates by RT in frame 688: 237\n", + "2024-12-19 13:16:05,962 - optimization.inference - INFO - Number of candidates by RT in frame 784: 273\n", + "2024-12-19 13:16:05,962 - optimization.inference - INFO - Number of candidates by RT in frame 2397: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,968 - optimization.inference - INFO - Scan time: 32.9544\n", + "2024-12-19 13:16:05,969 - optimization.inference - INFO - Number of candidates by RT in frame 2402: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,975 - optimization.inference - INFO - Scan time: 32.9659\n", + "2024-12-19 13:16:05,976 - optimization.inference - INFO - Scan time: 7.149\n", + "2024-12-19 13:16:05,976 - optimization.inference - INFO - Number of candidates by RT in frame 2407: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,977 - optimization.inference - INFO - Number of candidates by RT in frame 693: 252\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,977 - optimization.inference - INFO - Scan time: 8.7935\n", + "2024-12-19 13:16:05,978 - optimization.inference - INFO - Number of candidates by RT in frame 789: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,982 - optimization.inference - INFO - Scan time: 32.9815\n", + "2024-12-19 13:16:05,983 - optimization.inference - INFO - Number of candidates by RT in frame 2412: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,989 - optimization.inference - INFO - Scan time: 32.9957\n", + "2024-12-19 13:16:05,990 - optimization.inference - INFO - Number of candidates by RT in frame 2417: 1\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,993 - optimization.inference - INFO - Scan time: 7.2336\n", + "2024-12-19 13:16:05,994 - optimization.inference - INFO - Number of candidates by RT in frame 698: 248\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:05,996 - optimization.inference - INFO - Scan time: 8.8798\n", + "2024-12-19 13:16:05,996 - optimization.inference - INFO - Shape of COO matrix: (2421, 18939)\n", + "2024-12-19 13:16:05,997 - optimization.inference - INFO - Number of candidates by RT in frame 794: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,008 - optimization.inference - INFO - Scan time: 7.3196\n", + "2024-12-19 13:16:06,009 - optimization.inference - INFO - Number of candidates by RT in frame 703: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,018 - optimization.inference - INFO - Scan time: 8.9646\n", + "2024-12-19 13:16:06,019 - optimization.inference - INFO - Number of candidates by RT in frame 799: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,022 - optimization.inference - INFO - Scan time: 7.4047\n", + "2024-12-19 13:16:06,023 - optimization.inference - INFO - Number of candidates by RT in frame 708: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,035 - optimization.inference - INFO - Scan time: 9.0494\n", + "2024-12-19 13:16:06,036 - optimization.inference - INFO - Number of candidates by RT in frame 804: 277\n", + "2024-12-19 13:16:06,037 - optimization.inference - INFO - Scan time: 7.4912\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,038 - optimization.inference - INFO - Number of candidates by RT in frame 713: 247\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,051 - optimization.inference - INFO - Scan time: 9.1353\n", + "2024-12-19 13:16:06,052 - optimization.inference - INFO - Number of candidates by RT in frame 809: 267\n", + "2024-12-19 13:16:06,052 - optimization.inference - INFO - Scan time: 7.5771\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,053 - optimization.inference - INFO - Number of candidates by RT in frame 718: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,066 - optimization.inference - INFO - Scan time: 7.6628\n", + "2024-12-19 13:16:06,066 - optimization.inference - INFO - Scan time: 9.2211\n", + "2024-12-19 13:16:06,067 - optimization.inference - INFO - Number of candidates by RT in frame 723: 257\n", + "2024-12-19 13:16:06,067 - optimization.inference - INFO - Number of candidates by RT in frame 814: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,080 - optimization.inference - INFO - Size of COO matrix in batch 2: 1.621032 Mb\n", + "2024-12-19 13:16:06,082 - optimization.inference - INFO - Scan time: 7.7491\n", + "2024-12-19 13:16:06,083 - optimization.inference - INFO - Number of candidates by RT in frame 728: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,084 - optimization.inference - INFO - Scan time: 9.3062\n", + "2024-12-19 13:16:06,085 - optimization.inference - INFO - Number of candidates by RT in frame 819: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,096 - optimization.inference - INFO - Scan time: 7.8345\n", + "2024-12-19 13:16:06,097 - optimization.inference - INFO - Number of candidates by RT in frame 733: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,102 - optimization.inference - INFO - Scan time: 9.3916\n", + "2024-12-19 13:16:06,103 - optimization.inference - INFO - Number of candidates by RT in frame 824: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,112 - optimization.inference - INFO - Scan time: 7.9206\n", + "2024-12-19 13:16:06,113 - optimization.inference - INFO - Number of candidates by RT in frame 738: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,119 - optimization.inference - INFO - Scan time: 9.4792\n", + "2024-12-19 13:16:06,120 - optimization.inference - INFO - Number of candidates by RT in frame 829: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,127 - optimization.inference - INFO - Scan time: 8.0056\n", + "2024-12-19 13:16:06,128 - optimization.inference - INFO - Number of candidates by RT in frame 743: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,135 - optimization.inference - INFO - Scan time: 9.5646\n", + "2024-12-19 13:16:06,136 - optimization.inference - INFO - Number of candidates by RT in frame 834: 294\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,143 - optimization.inference - INFO - Scan time: 8.0912\n", + "2024-12-19 13:16:06,144 - optimization.inference - INFO - Number of candidates by RT in frame 748: 251\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,153 - optimization.inference - INFO - Scan time: 9.65\n", + "2024-12-19 13:16:06,154 - optimization.inference - INFO - Number of candidates by RT in frame 839: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,159 - optimization.inference - INFO - Scan time: 8.1767\n", + "2024-12-19 13:16:06,160 - optimization.inference - INFO - Number of candidates by RT in frame 753: 253\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,170 - optimization.inference - INFO - Scan time: 9.7364\n", + "2024-12-19 13:16:06,171 - optimization.inference - INFO - Number of candidates by RT in frame 844: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,179 - optimization.inference - INFO - Scan time: 8.2629\n", + "2024-12-19 13:16:06,180 - optimization.inference - INFO - Number of candidates by RT in frame 758: 251\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,185 - optimization.inference - INFO - Scan time: 9.8214\n", + "2024-12-19 13:16:06,186 - optimization.inference - INFO - Number of candidates by RT in frame 849: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,193 - optimization.inference - INFO - Scan time: 8.3483\n", + "2024-12-19 13:16:06,194 - optimization.inference - INFO - Number of candidates by RT in frame 763: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,203 - optimization.inference - INFO - Scan time: 9.9075\n", + "2024-12-19 13:16:06,204 - optimization.inference - INFO - Number of candidates by RT in frame 854: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,211 - optimization.inference - INFO - Scan time: 8.4341\n", + "2024-12-19 13:16:06,212 - optimization.inference - INFO - Number of candidates by RT in frame 768: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,219 - optimization.inference - INFO - Scan time: 9.9926\n", + "2024-12-19 13:16:06,221 - optimization.inference - INFO - Number of candidates by RT in frame 859: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,226 - optimization.inference - INFO - Scan time: 8.5192\n", + "2024-12-19 13:16:06,227 - optimization.inference - INFO - Number of candidates by RT in frame 773: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,234 - optimization.inference - INFO - Scan time: 10.0787\n", + "2024-12-19 13:16:06,235 - optimization.inference - INFO - Number of candidates by RT in frame 864: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,244 - optimization.inference - INFO - Scan time: 8.6049\n", + "2024-12-19 13:16:06,245 - optimization.inference - INFO - Number of candidates by RT in frame 778: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,248 - optimization.inference - INFO - Scan time: 10.1635\n", + "2024-12-19 13:16:06,249 - optimization.inference - INFO - Number of candidates by RT in frame 869: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,261 - optimization.inference - INFO - Scan time: 8.6911\n", + "2024-12-19 13:16:06,262 - optimization.inference - INFO - Number of candidates by RT in frame 783: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,264 - optimization.inference - INFO - Scan time: 10.2492\n", + "2024-12-19 13:16:06,265 - optimization.inference - INFO - Number of candidates by RT in frame 874: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,279 - optimization.inference - INFO - Scan time: 8.7761\n", + "2024-12-19 13:16:06,279 - optimization.inference - INFO - Scan time: 10.3345\n", + "2024-12-19 13:16:06,280 - optimization.inference - INFO - Number of candidates by RT in frame 788: 273\n", + "2024-12-19 13:16:06,280 - optimization.inference - INFO - Number of candidates by RT in frame 879: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,295 - optimization.inference - INFO - Scan time: 10.4197\n", + "2024-12-19 13:16:06,296 - optimization.inference - INFO - Number of candidates by RT in frame 884: 267\n", + "2024-12-19 13:16:06,296 - optimization.inference - INFO - Scan time: 8.8623\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,297 - optimization.inference - INFO - Number of candidates by RT in frame 793: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,311 - optimization.inference - INFO - Scan time: 10.506\n", + "2024-12-19 13:16:06,312 - optimization.inference - INFO - Number of candidates by RT in frame 889: 257\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,314 - optimization.inference - INFO - Scan time: 8.9475\n", + "2024-12-19 13:16:06,315 - optimization.inference - INFO - Number of candidates by RT in frame 798: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,324 - optimization.inference - INFO - Scan time: 10.5918\n", + "2024-12-19 13:16:06,325 - optimization.inference - INFO - Number of candidates by RT in frame 894: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,331 - optimization.inference - INFO - Scan time: 9.0325\n", + "2024-12-19 13:16:06,332 - optimization.inference - INFO - Number of candidates by RT in frame 803: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,340 - optimization.inference - INFO - Scan time: 10.6782\n", + "2024-12-19 13:16:06,341 - optimization.inference - INFO - Number of candidates by RT in frame 899: 284\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,346 - optimization.inference - INFO - Scan time: 9.1179\n", + "2024-12-19 13:16:06,347 - optimization.inference - INFO - Number of candidates by RT in frame 808: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,358 - optimization.inference - INFO - Scan time: 10.7644\n", + "2024-12-19 13:16:06,359 - optimization.inference - INFO - Number of candidates by RT in frame 904: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,361 - optimization.inference - INFO - Scan time: 9.2042\n", + "2024-12-19 13:16:06,362 - optimization.inference - INFO - Number of candidates by RT in frame 813: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,374 - optimization.inference - INFO - Scan time: 10.8502\n", + "2024-12-19 13:16:06,375 - optimization.inference - INFO - Number of candidates by RT in frame 909: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,378 - optimization.inference - INFO - Scan time: 9.289\n", + "2024-12-19 13:16:06,379 - optimization.inference - INFO - Number of candidates by RT in frame 818: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,390 - optimization.inference - INFO - Scan time: 10.9358\n", + "2024-12-19 13:16:06,391 - optimization.inference - INFO - Number of candidates by RT in frame 914: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,395 - optimization.inference - INFO - Scan time: 9.3747\n", + "2024-12-19 13:16:06,396 - optimization.inference - INFO - Number of candidates by RT in frame 823: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,404 - optimization.inference - INFO - Scan time: 11.0215\n", + "2024-12-19 13:16:06,405 - optimization.inference - INFO - Number of candidates by RT in frame 919: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,412 - optimization.inference - INFO - Scan time: 9.4618\n", + "2024-12-19 13:16:06,413 - optimization.inference - INFO - Number of candidates by RT in frame 828: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,422 - optimization.inference - INFO - Scan time: 11.1077\n", + "2024-12-19 13:16:06,423 - optimization.inference - INFO - Number of candidates by RT in frame 924: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,428 - optimization.inference - INFO - Scan time: 9.5475\n", + "2024-12-19 13:16:06,430 - optimization.inference - INFO - Number of candidates by RT in frame 833: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,438 - optimization.inference - INFO - Scan time: 11.1934\n", + "2024-12-19 13:16:06,439 - optimization.inference - INFO - Number of candidates by RT in frame 929: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,445 - optimization.inference - INFO - Scan time: 9.6328\n", + "2024-12-19 13:16:06,446 - optimization.inference - INFO - Number of candidates by RT in frame 838: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,455 - optimization.inference - INFO - Scan time: 11.2798\n", + "2024-12-19 13:16:06,456 - optimization.inference - INFO - Number of candidates by RT in frame 934: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,462 - optimization.inference - INFO - Scan time: 9.7188\n", + "2024-12-19 13:16:06,463 - optimization.inference - INFO - Number of candidates by RT in frame 843: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,476 - optimization.inference - INFO - Scan time: 11.3662\n", + "2024-12-19 13:16:06,477 - optimization.inference - INFO - Number of candidates by RT in frame 939: 304\n", + "2024-12-19 13:16:06,477 - optimization.inference - INFO - Scan time: 9.8047\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,478 - optimization.inference - INFO - Number of candidates by RT in frame 848: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,490 - optimization.inference - INFO - Scan time: 11.4528\n", + "2024-12-19 13:16:06,491 - optimization.inference - INFO - Number of candidates by RT in frame 944: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,496 - optimization.inference - INFO - Scan time: 9.8907\n", + "2024-12-19 13:16:06,497 - optimization.inference - INFO - Number of candidates by RT in frame 853: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,505 - optimization.inference - INFO - Scan time: 11.5385\n", + "2024-12-19 13:16:06,506 - optimization.inference - INFO - Number of candidates by RT in frame 949: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,513 - optimization.inference - INFO - Scan time: 9.9752\n", + "2024-12-19 13:16:06,514 - optimization.inference - INFO - Number of candidates by RT in frame 858: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,527 - optimization.inference - INFO - Scan time: 11.6238\n", + "2024-12-19 13:16:06,528 - optimization.inference - INFO - Number of candidates by RT in frame 954: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,530 - optimization.inference - INFO - Scan time: 10.0616\n", + "2024-12-19 13:16:06,531 - optimization.inference - INFO - Number of candidates by RT in frame 863: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,544 - optimization.inference - INFO - Scan time: 10.1469\n", + "2024-12-19 13:16:06,544 - optimization.inference - INFO - Scan time: 11.7093\n", + "2024-12-19 13:16:06,545 - optimization.inference - INFO - Number of candidates by RT in frame 868: 268\n", + "2024-12-19 13:16:06,545 - optimization.inference - INFO - Number of candidates by RT in frame 959: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,559 - optimization.inference - INFO - Scan time: 10.2321\n", + "2024-12-19 13:16:06,560 - optimization.inference - INFO - Number of candidates by RT in frame 873: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,563 - optimization.inference - INFO - Scan time: 11.7952\n", + "2024-12-19 13:16:06,564 - optimization.inference - INFO - Number of candidates by RT in frame 964: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,575 - optimization.inference - INFO - Scan time: 10.3176\n", + "2024-12-19 13:16:06,576 - optimization.inference - INFO - Number of candidates by RT in frame 878: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,582 - optimization.inference - INFO - Scan time: 11.8807\n", + "2024-12-19 13:16:06,583 - optimization.inference - INFO - Number of candidates by RT in frame 969: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,589 - optimization.inference - INFO - Scan time: 10.4029\n", + "2024-12-19 13:16:06,590 - optimization.inference - INFO - Number of candidates by RT in frame 883: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,604 - optimization.inference - INFO - Scan time: 10.4887\n", + "2024-12-19 13:16:06,606 - optimization.inference - INFO - Number of candidates by RT in frame 888: 258\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,611 - optimization.inference - INFO - Scan time: 11.9668\n", + "2024-12-19 13:16:06,612 - optimization.inference - INFO - Number of candidates by RT in frame 974: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,619 - optimization.inference - INFO - Scan time: 10.5745\n", + "2024-12-19 13:16:06,620 - optimization.inference - INFO - Number of candidates by RT in frame 893: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,625 - optimization.inference - INFO - Scan time: 12.0535\n", + "2024-12-19 13:16:06,626 - optimization.inference - INFO - Number of candidates by RT in frame 979: 314\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,635 - optimization.inference - INFO - Scan time: 10.6607\n", + "2024-12-19 13:16:06,636 - optimization.inference - INFO - Number of candidates by RT in frame 898: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,646 - optimization.inference - INFO - Scan time: 12.1397\n", + "2024-12-19 13:16:06,647 - optimization.inference - INFO - Number of candidates by RT in frame 984: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,652 - optimization.inference - INFO - Scan time: 10.7469\n", + "2024-12-19 13:16:06,653 - optimization.inference - INFO - Number of candidates by RT in frame 903: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,659 - optimization.inference - INFO - Scan time: 12.2258\n", + "2024-12-19 13:16:06,660 - optimization.inference - INFO - Number of candidates by RT in frame 989: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,668 - optimization.inference - INFO - Scan time: 10.8334\n", + "2024-12-19 13:16:06,669 - optimization.inference - INFO - Number of candidates by RT in frame 908: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,676 - optimization.inference - INFO - Scan time: 12.3106\n", + "2024-12-19 13:16:06,677 - optimization.inference - INFO - Number of candidates by RT in frame 994: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,685 - optimization.inference - INFO - Scan time: 10.9186\n", + "2024-12-19 13:16:06,686 - optimization.inference - INFO - Number of candidates by RT in frame 913: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,692 - optimization.inference - INFO - Scan time: 12.3956\n", + "2024-12-19 13:16:06,693 - optimization.inference - INFO - Number of candidates by RT in frame 999: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,700 - optimization.inference - INFO - Scan time: 11.0044\n", + "2024-12-19 13:16:06,701 - optimization.inference - INFO - Number of candidates by RT in frame 918: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,709 - optimization.inference - INFO - Scan time: 12.482\n", + "2024-12-19 13:16:06,710 - optimization.inference - INFO - Number of candidates by RT in frame 1004: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,717 - optimization.inference - INFO - Scan time: 11.0906\n", + "2024-12-19 13:16:06,718 - optimization.inference - INFO - Number of candidates by RT in frame 923: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,728 - optimization.inference - INFO - Scan time: 12.5676\n", + "2024-12-19 13:16:06,729 - optimization.inference - INFO - Number of candidates by RT in frame 1009: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,733 - optimization.inference - INFO - Scan time: 11.1763\n", + "2024-12-19 13:16:06,734 - optimization.inference - INFO - Number of candidates by RT in frame 928: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,745 - optimization.inference - INFO - Scan time: 12.6528\n", + "2024-12-19 13:16:06,747 - optimization.inference - INFO - Number of candidates by RT in frame 1014: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,752 - optimization.inference - INFO - Scan time: 11.2622\n", + "2024-12-19 13:16:06,753 - optimization.inference - INFO - Number of candidates by RT in frame 933: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,763 - optimization.inference - INFO - Scan time: 12.7386\n", + "2024-12-19 13:16:06,764 - optimization.inference - INFO - Number of candidates by RT in frame 1019: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,769 - optimization.inference - INFO - Scan time: 11.3489\n", + "2024-12-19 13:16:06,770 - optimization.inference - INFO - Number of candidates by RT in frame 938: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,781 - optimization.inference - INFO - Scan time: 12.8243\n", + "2024-12-19 13:16:06,782 - optimization.inference - INFO - Number of candidates by RT in frame 1024: 327\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,784 - optimization.inference - INFO - Scan time: 11.4352\n", + "2024-12-19 13:16:06,785 - optimization.inference - INFO - Number of candidates by RT in frame 943: 294\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,798 - optimization.inference - INFO - Scan time: 11.5216\n", + "2024-12-19 13:16:06,799 - optimization.inference - INFO - Number of candidates by RT in frame 948: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,802 - optimization.inference - INFO - Scan time: 12.9109\n", + "2024-12-19 13:16:06,803 - optimization.inference - INFO - Number of candidates by RT in frame 1029: 338\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,817 - optimization.inference - INFO - Scan time: 11.6069\n", + "2024-12-19 13:16:06,818 - optimization.inference - INFO - Number of candidates by RT in frame 953: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,821 - optimization.inference - INFO - Scan time: 12.9965\n", + "2024-12-19 13:16:06,822 - optimization.inference - INFO - Number of candidates by RT in frame 1034: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,832 - optimization.inference - INFO - Scan time: 11.6924\n", + "2024-12-19 13:16:06,833 - optimization.inference - INFO - Number of candidates by RT in frame 958: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,841 - optimization.inference - INFO - Scan time: 13.082\n", + "2024-12-19 13:16:06,842 - optimization.inference - INFO - Number of candidates by RT in frame 1039: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,849 - optimization.inference - INFO - Scan time: 11.7782\n", + "2024-12-19 13:16:06,850 - optimization.inference - INFO - Number of candidates by RT in frame 963: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,858 - optimization.inference - INFO - Scan time: 13.1679\n", + "2024-12-19 13:16:06,859 - optimization.inference - INFO - Number of candidates by RT in frame 1044: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,864 - optimization.inference - INFO - Scan time: 11.8637\n", + "2024-12-19 13:16:06,865 - optimization.inference - INFO - Number of candidates by RT in frame 968: 294\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,875 - optimization.inference - INFO - Scan time: 13.2546\n", + "2024-12-19 13:16:06,876 - optimization.inference - INFO - Number of candidates by RT in frame 1049: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,881 - optimization.inference - INFO - Scan time: 11.9499\n", + "2024-12-19 13:16:06,882 - optimization.inference - INFO - Number of candidates by RT in frame 973: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,890 - optimization.inference - INFO - Scan time: 13.3412\n", + "2024-12-19 13:16:06,891 - optimization.inference - INFO - Number of candidates by RT in frame 1054: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,895 - optimization.inference - INFO - Scan time: 12.0359\n", + "2024-12-19 13:16:06,896 - optimization.inference - INFO - Number of candidates by RT in frame 978: 316\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,906 - optimization.inference - INFO - Scan time: 13.4276\n", + "2024-12-19 13:16:06,907 - optimization.inference - INFO - Number of candidates by RT in frame 1059: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,917 - optimization.inference - INFO - Scan time: 12.1229\n", + "2024-12-19 13:16:06,918 - optimization.inference - INFO - Number of candidates by RT in frame 983: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,923 - optimization.inference - INFO - Scan time: 13.5138\n", + "2024-12-19 13:16:06,924 - optimization.inference - INFO - Number of candidates by RT in frame 1064: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,934 - optimization.inference - INFO - Scan time: 12.2088\n", + "2024-12-19 13:16:06,935 - optimization.inference - INFO - Number of candidates by RT in frame 988: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,940 - optimization.inference - INFO - Scan time: 13.5998\n", + "2024-12-19 13:16:06,941 - optimization.inference - INFO - Number of candidates by RT in frame 1069: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,955 - optimization.inference - INFO - Scan time: 12.2938\n", + "2024-12-19 13:16:06,956 - optimization.inference - INFO - Number of candidates by RT in frame 993: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,957 - optimization.inference - INFO - Scan time: 13.6859\n", + "2024-12-19 13:16:06,958 - optimization.inference - INFO - Number of candidates by RT in frame 1074: 324\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,975 - optimization.inference - INFO - Scan time: 12.3786\n", + "2024-12-19 13:16:06,976 - optimization.inference - INFO - Scan time: 13.772\n", + "2024-12-19 13:16:06,976 - optimization.inference - INFO - Number of candidates by RT in frame 998: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,977 - optimization.inference - INFO - Number of candidates by RT in frame 1079: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:06,994 - optimization.inference - INFO - Scan time: 13.8579\n", + "2024-12-19 13:16:06,995 - optimization.inference - INFO - Number of candidates by RT in frame 1084: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,005 - optimization.inference - INFO - Scan time: 12.4645\n", + "2024-12-19 13:16:07,006 - optimization.inference - INFO - Number of candidates by RT in frame 1003: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,014 - optimization.inference - INFO - Scan time: 13.9434\n", + "2024-12-19 13:16:07,015 - optimization.inference - INFO - Number of candidates by RT in frame 1089: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,023 - optimization.inference - INFO - Scan time: 12.5502\n", + "2024-12-19 13:16:07,024 - optimization.inference - INFO - Number of candidates by RT in frame 1008: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,032 - optimization.inference - INFO - Scan time: 14.0285\n", + "2024-12-19 13:16:07,033 - optimization.inference - INFO - Number of candidates by RT in frame 1094: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,040 - optimization.inference - INFO - Scan time: 12.6359\n", + "2024-12-19 13:16:07,042 - optimization.inference - INFO - Number of candidates by RT in frame 1013: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,048 - optimization.inference - INFO - Scan time: 14.1149\n", + "2024-12-19 13:16:07,049 - optimization.inference - INFO - Number of candidates by RT in frame 1099: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,057 - optimization.inference - INFO - Scan time: 12.7217\n", + "2024-12-19 13:16:07,058 - optimization.inference - INFO - Number of candidates by RT in frame 1018: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,063 - optimization.inference - INFO - Scan time: 14.2007\n", + "2024-12-19 13:16:07,064 - optimization.inference - INFO - Number of candidates by RT in frame 1104: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,076 - optimization.inference - INFO - Scan time: 12.8072\n", + "2024-12-19 13:16:07,077 - optimization.inference - INFO - Number of candidates by RT in frame 1023: 324\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,079 - optimization.inference - INFO - Scan time: 14.287\n", + "2024-12-19 13:16:07,080 - optimization.inference - INFO - Number of candidates by RT in frame 1109: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,096 - optimization.inference - INFO - Scan time: 14.3727\n", + "2024-12-19 13:16:07,097 - optimization.inference - INFO - Number of candidates by RT in frame 1114: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,098 - optimization.inference - INFO - Scan time: 12.8937\n", + "2024-12-19 13:16:07,099 - optimization.inference - INFO - Number of candidates by RT in frame 1028: 339\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,112 - optimization.inference - INFO - Scan time: 14.4584\n", + "2024-12-19 13:16:07,113 - optimization.inference - INFO - Number of candidates by RT in frame 1119: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,118 - optimization.inference - INFO - Scan time: 12.9795\n", + "2024-12-19 13:16:07,119 - optimization.inference - INFO - Number of candidates by RT in frame 1033: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,135 - optimization.inference - INFO - Scan time: 14.5441\n", + "2024-12-19 13:16:07,136 - optimization.inference - INFO - Number of candidates by RT in frame 1124: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,138 - optimization.inference - INFO - Scan time: 13.0646\n", + "2024-12-19 13:16:07,139 - optimization.inference - INFO - Number of candidates by RT in frame 1038: 328\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,156 - optimization.inference - INFO - Scan time: 13.1504\n", + "2024-12-19 13:16:07,157 - optimization.inference - INFO - Scan time: 14.6294\n", + "2024-12-19 13:16:07,157 - optimization.inference - INFO - Number of candidates by RT in frame 1043: 318\n", + "2024-12-19 13:16:07,158 - optimization.inference - INFO - Number of candidates by RT in frame 1129: 332\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,173 - optimization.inference - INFO - Scan time: 13.2372\n", + "2024-12-19 13:16:07,174 - optimization.inference - INFO - Number of candidates by RT in frame 1048: 281\n", + "2024-12-19 13:16:07,175 - optimization.inference - INFO - Scan time: 14.7153\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,176 - optimization.inference - INFO - Number of candidates by RT in frame 1134: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,189 - optimization.inference - INFO - Scan time: 13.3238\n", + "2024-12-19 13:16:07,190 - optimization.inference - INFO - Number of candidates by RT in frame 1053: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,195 - optimization.inference - INFO - Scan time: 14.8019\n", + "2024-12-19 13:16:07,196 - optimization.inference - INFO - Number of candidates by RT in frame 1139: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,205 - optimization.inference - INFO - Scan time: 13.4097\n", + "2024-12-19 13:16:07,206 - optimization.inference - INFO - Number of candidates by RT in frame 1058: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,216 - optimization.inference - INFO - Scan time: 14.8865\n", + "2024-12-19 13:16:07,217 - optimization.inference - INFO - Number of candidates by RT in frame 1144: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,219 - optimization.inference - INFO - Scan time: 13.4969\n", + "2024-12-19 13:16:07,220 - optimization.inference - INFO - Number of candidates by RT in frame 1063: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,237 - optimization.inference - INFO - Scan time: 13.5823\n", + "2024-12-19 13:16:07,237 - optimization.inference - INFO - Scan time: 14.9725\n", + "2024-12-19 13:16:07,238 - optimization.inference - INFO - Number of candidates by RT in frame 1068: 302\n", + "2024-12-19 13:16:07,238 - optimization.inference - INFO - Number of candidates by RT in frame 1149: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,255 - optimization.inference - INFO - Scan time: 13.6686\n", + "2024-12-19 13:16:07,256 - optimization.inference - INFO - Number of candidates by RT in frame 1073: 322\n", + "2024-12-19 13:16:07,256 - optimization.inference - INFO - Scan time: 15.0583\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,257 - optimization.inference - INFO - Number of candidates by RT in frame 1154: 314\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,274 - optimization.inference - INFO - Scan time: 15.1442\n", + "2024-12-19 13:16:07,275 - optimization.inference - INFO - Scan time: 13.7551\n", + "2024-12-19 13:16:07,275 - optimization.inference - INFO - Number of candidates by RT in frame 1159: 314\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,276 - optimization.inference - INFO - Number of candidates by RT in frame 1078: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,289 - optimization.inference - INFO - Scan time: 15.2306\n", + "2024-12-19 13:16:07,290 - optimization.inference - INFO - Number of candidates by RT in frame 1164: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,292 - optimization.inference - INFO - Scan time: 13.8408\n", + "2024-12-19 13:16:07,293 - optimization.inference - INFO - Number of candidates by RT in frame 1083: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,305 - optimization.inference - INFO - Scan time: 15.316\n", + "2024-12-19 13:16:07,306 - optimization.inference - INFO - Number of candidates by RT in frame 1169: 319\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,313 - optimization.inference - INFO - Scan time: 13.9265\n", + "2024-12-19 13:16:07,314 - optimization.inference - INFO - Number of candidates by RT in frame 1088: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,322 - optimization.inference - INFO - Scan time: 15.402\n", + "2024-12-19 13:16:07,323 - optimization.inference - INFO - Number of candidates by RT in frame 1174: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,332 - optimization.inference - INFO - Scan time: 14.0116\n", + "2024-12-19 13:16:07,333 - optimization.inference - INFO - Number of candidates by RT in frame 1093: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,341 - optimization.inference - INFO - Scan time: 15.4881\n", + "2024-12-19 13:16:07,342 - optimization.inference - INFO - Number of candidates by RT in frame 1179: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,348 - optimization.inference - INFO - Scan time: 14.098\n", + "2024-12-19 13:16:07,349 - optimization.inference - INFO - Number of candidates by RT in frame 1098: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,363 - optimization.inference - INFO - Scan time: 14.1836\n", + "2024-12-19 13:16:07,363 - optimization.inference - INFO - Scan time: 15.5741\n", + "2024-12-19 13:16:07,364 - optimization.inference - INFO - Number of candidates by RT in frame 1103: 276\n", + "2024-12-19 13:16:07,364 - optimization.inference - INFO - Number of candidates by RT in frame 1184: 337\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,379 - optimization.inference - INFO - Scan time: 14.2702\n", + "2024-12-19 13:16:07,380 - optimization.inference - INFO - Number of candidates by RT in frame 1108: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,383 - optimization.inference - INFO - Scan time: 15.6598\n", + "2024-12-19 13:16:07,384 - optimization.inference - INFO - Number of candidates by RT in frame 1189: 333\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,396 - optimization.inference - INFO - Scan time: 14.3556\n", + "2024-12-19 13:16:07,397 - optimization.inference - INFO - Number of candidates by RT in frame 1113: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,403 - optimization.inference - INFO - Scan time: 15.7455\n", + "2024-12-19 13:16:07,404 - optimization.inference - INFO - Number of candidates by RT in frame 1194: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,413 - optimization.inference - INFO - Scan time: 14.4412\n", + "2024-12-19 13:16:07,414 - optimization.inference - INFO - Number of candidates by RT in frame 1118: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,423 - optimization.inference - INFO - Scan time: 15.8315\n", + "2024-12-19 13:16:07,424 - optimization.inference - INFO - Number of candidates by RT in frame 1199: 324\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,431 - optimization.inference - INFO - Scan time: 14.5271\n", + "2024-12-19 13:16:07,433 - optimization.inference - INFO - Number of candidates by RT in frame 1123: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,441 - optimization.inference - INFO - Scan time: 15.9162\n", + "2024-12-19 13:16:07,443 - optimization.inference - INFO - Number of candidates by RT in frame 1204: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,452 - optimization.inference - INFO - Scan time: 14.6122\n", + "2024-12-19 13:16:07,453 - optimization.inference - INFO - Number of candidates by RT in frame 1128: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,460 - optimization.inference - INFO - Scan time: 16.0022\n", + "2024-12-19 13:16:07,461 - optimization.inference - INFO - Number of candidates by RT in frame 1209: 317\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,469 - optimization.inference - INFO - Scan time: 14.698\n", + "2024-12-19 13:16:07,470 - optimization.inference - INFO - Number of candidates by RT in frame 1133: 341\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,479 - optimization.inference - INFO - Scan time: 16.0867\n", + "2024-12-19 13:16:07,480 - optimization.inference - INFO - Number of candidates by RT in frame 1214: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,495 - optimization.inference - INFO - Scan time: 14.7844\n", + "2024-12-19 13:16:07,496 - optimization.inference - INFO - Number of candidates by RT in frame 1138: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,497 - optimization.inference - INFO - Scan time: 16.1734\n", + "2024-12-19 13:16:07,498 - optimization.inference - INFO - Number of candidates by RT in frame 1219: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,515 - optimization.inference - INFO - Scan time: 14.8694\n", + "2024-12-19 13:16:07,515 - optimization.inference - INFO - Scan time: 16.2595\n", + "2024-12-19 13:16:07,516 - optimization.inference - INFO - Number of candidates by RT in frame 1143: 320\n", + "2024-12-19 13:16:07,516 - optimization.inference - INFO - Number of candidates by RT in frame 1224: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,535 - optimization.inference - INFO - Scan time: 16.3445\n", + "2024-12-19 13:16:07,536 - optimization.inference - INFO - Scan time: 14.9555\n", + "2024-12-19 13:16:07,536 - optimization.inference - INFO - Number of candidates by RT in frame 1229: 316\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,537 - optimization.inference - INFO - Number of candidates by RT in frame 1148: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,556 - optimization.inference - INFO - Scan time: 16.4307\n", + "2024-12-19 13:16:07,557 - optimization.inference - INFO - Number of candidates by RT in frame 1234: 332\n", + "2024-12-19 13:16:07,558 - optimization.inference - INFO - Scan time: 15.0414\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,559 - optimization.inference - INFO - Number of candidates by RT in frame 1153: 316\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,575 - optimization.inference - INFO - Scan time: 16.5167\n", + "2024-12-19 13:16:07,576 - optimization.inference - INFO - Scan time: 15.1271\n", + "2024-12-19 13:16:07,576 - optimization.inference - INFO - Number of candidates by RT in frame 1239: 333\n", + "2024-12-19 13:16:07,577 - optimization.inference - INFO - Number of candidates by RT in frame 1158: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,591 - optimization.inference - INFO - Scan time: 15.2134\n", + "2024-12-19 13:16:07,592 - optimization.inference - INFO - Number of candidates by RT in frame 1163: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,594 - optimization.inference - INFO - Scan time: 16.6021\n", + "2024-12-19 13:16:07,595 - optimization.inference - INFO - Number of candidates by RT in frame 1244: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,608 - optimization.inference - INFO - Scan time: 15.2987\n", + "2024-12-19 13:16:07,609 - optimization.inference - INFO - Number of candidates by RT in frame 1168: 316\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,612 - optimization.inference - INFO - Scan time: 16.6881\n", + "2024-12-19 13:16:07,614 - optimization.inference - INFO - Number of candidates by RT in frame 1249: 317\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,627 - optimization.inference - INFO - Scan time: 15.3849\n", + "2024-12-19 13:16:07,628 - optimization.inference - INFO - Number of candidates by RT in frame 1173: 335\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,631 - optimization.inference - INFO - Scan time: 16.7736\n", + "2024-12-19 13:16:07,632 - optimization.inference - INFO - Number of candidates by RT in frame 1254: 318\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,646 - optimization.inference - INFO - Scan time: 15.4707\n", + "2024-12-19 13:16:07,648 - optimization.inference - INFO - Number of candidates by RT in frame 1178: 340\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,649 - optimization.inference - INFO - Scan time: 16.8595\n", + "2024-12-19 13:16:07,650 - optimization.inference - INFO - Number of candidates by RT in frame 1259: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,668 - optimization.inference - INFO - Scan time: 15.557\n", + "2024-12-19 13:16:07,669 - optimization.inference - INFO - Number of candidates by RT in frame 1183: 335\n", + "2024-12-19 13:16:07,669 - optimization.inference - INFO - Scan time: 16.9447\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,670 - optimization.inference - INFO - Number of candidates by RT in frame 1264: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,688 - optimization.inference - INFO - Scan time: 15.6429\n", + "2024-12-19 13:16:07,689 - optimization.inference - INFO - Number of candidates by RT in frame 1188: 340\n", + "2024-12-19 13:16:07,690 - optimization.inference - INFO - Scan time: 17.0306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,691 - optimization.inference - INFO - Number of candidates by RT in frame 1269: 327\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,707 - optimization.inference - INFO - Scan time: 17.1167\n", + "2024-12-19 13:16:07,708 - optimization.inference - INFO - Number of candidates by RT in frame 1274: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,709 - optimization.inference - INFO - Scan time: 15.7283\n", + "2024-12-19 13:16:07,710 - optimization.inference - INFO - Number of candidates by RT in frame 1193: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,721 - optimization.inference - INFO - Scan time: 17.2032\n", + "2024-12-19 13:16:07,723 - optimization.inference - INFO - Number of candidates by RT in frame 1279: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,731 - optimization.inference - INFO - Scan time: 15.8145\n", + "2024-12-19 13:16:07,732 - optimization.inference - INFO - Number of candidates by RT in frame 1198: 328\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,740 - optimization.inference - INFO - Scan time: 17.2895\n", + "2024-12-19 13:16:07,741 - optimization.inference - INFO - Number of candidates by RT in frame 1284: 330\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,750 - optimization.inference - INFO - Scan time: 15.8993\n", + "2024-12-19 13:16:07,751 - optimization.inference - INFO - Number of candidates by RT in frame 1203: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,760 - optimization.inference - INFO - Scan time: 17.375\n", + "2024-12-19 13:16:07,761 - optimization.inference - INFO - Number of candidates by RT in frame 1289: 327\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,771 - optimization.inference - INFO - Scan time: 15.9853\n", + "2024-12-19 13:16:07,772 - optimization.inference - INFO - Number of candidates by RT in frame 1208: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,780 - optimization.inference - INFO - Scan time: 17.462\n", + "2024-12-19 13:16:07,781 - optimization.inference - INFO - Number of candidates by RT in frame 1294: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,791 - optimization.inference - INFO - Scan time: 16.0698\n", + "2024-12-19 13:16:07,792 - optimization.inference - INFO - Number of candidates by RT in frame 1213: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,801 - optimization.inference - INFO - Scan time: 17.5476\n", + "2024-12-19 13:16:07,802 - optimization.inference - INFO - Number of candidates by RT in frame 1299: 349\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,819 - optimization.inference - INFO - Scan time: 16.156\n", + "2024-12-19 13:16:07,820 - optimization.inference - INFO - Number of candidates by RT in frame 1218: 298\n", + "2024-12-19 13:16:07,820 - optimization.inference - INFO - Scan time: 17.6339\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,821 - optimization.inference - INFO - Number of candidates by RT in frame 1304: 319\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,841 - optimization.inference - INFO - Scan time: 16.2424\n", + "2024-12-19 13:16:07,841 - optimization.inference - INFO - Scan time: 17.7196\n", + "2024-12-19 13:16:07,842 - optimization.inference - INFO - Number of candidates by RT in frame 1223: 325\n", + "2024-12-19 13:16:07,842 - optimization.inference - INFO - Number of candidates by RT in frame 1309: 318\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,860 - optimization.inference - INFO - Scan time: 16.3275\n", + "2024-12-19 13:16:07,861 - optimization.inference - INFO - Number of candidates by RT in frame 1228: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,862 - optimization.inference - INFO - Scan time: 17.8054\n", + "2024-12-19 13:16:07,863 - optimization.inference - INFO - Number of candidates by RT in frame 1314: 330\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,881 - optimization.inference - INFO - Scan time: 16.4135\n", + "2024-12-19 13:16:07,882 - optimization.inference - INFO - Scan time: 17.8911\n", + "2024-12-19 13:16:07,882 - optimization.inference - INFO - Number of candidates by RT in frame 1233: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,883 - optimization.inference - INFO - Number of candidates by RT in frame 1319: 318\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,902 - optimization.inference - INFO - Scan time: 16.4996\n", + "2024-12-19 13:16:07,903 - optimization.inference - INFO - Scan time: 17.9767\n", + "2024-12-19 13:16:07,903 - optimization.inference - INFO - Number of candidates by RT in frame 1238: 333\n", + "2024-12-19 13:16:07,904 - optimization.inference - INFO - Number of candidates by RT in frame 1324: 330\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,920 - optimization.inference - INFO - Scan time: 16.5851\n", + "2024-12-19 13:16:07,921 - optimization.inference - INFO - Number of candidates by RT in frame 1243: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,923 - optimization.inference - INFO - Scan time: 18.0621\n", + "2024-12-19 13:16:07,924 - optimization.inference - INFO - Number of candidates by RT in frame 1329: 322\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,940 - optimization.inference - INFO - Scan time: 16.6707\n", + "2024-12-19 13:16:07,941 - optimization.inference - INFO - Number of candidates by RT in frame 1248: 313\n", + "2024-12-19 13:16:07,941 - optimization.inference - INFO - Scan time: 18.1484\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,942 - optimization.inference - INFO - Number of candidates by RT in frame 1334: 334\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,959 - optimization.inference - INFO - Scan time: 16.7568\n", + "2024-12-19 13:16:07,960 - optimization.inference - INFO - Number of candidates by RT in frame 1253: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,961 - optimization.inference - INFO - Scan time: 18.2347\n", + "2024-12-19 13:16:07,962 - optimization.inference - INFO - Number of candidates by RT in frame 1339: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,976 - optimization.inference - INFO - Scan time: 16.8426\n", + "2024-12-19 13:16:07,978 - optimization.inference - INFO - Number of candidates by RT in frame 1258: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,983 - optimization.inference - INFO - Scan time: 18.3201\n", + "2024-12-19 13:16:07,984 - optimization.inference - INFO - Number of candidates by RT in frame 1344: 349\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:07,997 - optimization.inference - INFO - Scan time: 16.9275\n", + "2024-12-19 13:16:07,998 - optimization.inference - INFO - Number of candidates by RT in frame 1263: 331\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,001 - optimization.inference - INFO - Scan time: 18.4053\n", + "2024-12-19 13:16:08,002 - optimization.inference - INFO - Number of candidates by RT in frame 1349: 330\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,018 - optimization.inference - INFO - Scan time: 17.0131\n", + "2024-12-19 13:16:08,019 - optimization.inference - INFO - Number of candidates by RT in frame 1268: 332\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,020 - optimization.inference - INFO - Scan time: 18.4917\n", + "2024-12-19 13:16:08,021 - optimization.inference - INFO - Number of candidates by RT in frame 1354: 317\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,036 - optimization.inference - INFO - Scan time: 17.0995\n", + "2024-12-19 13:16:08,037 - optimization.inference - INFO - Number of candidates by RT in frame 1273: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,039 - optimization.inference - INFO - Scan time: 18.577\n", + "2024-12-19 13:16:08,040 - optimization.inference - INFO - Number of candidates by RT in frame 1359: 321\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,053 - optimization.inference - INFO - Scan time: 17.1861\n", + "2024-12-19 13:16:08,054 - optimization.inference - INFO - Number of candidates by RT in frame 1278: 317\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,060 - optimization.inference - INFO - Scan time: 18.6624\n", + "2024-12-19 13:16:08,061 - optimization.inference - INFO - Number of candidates by RT in frame 1364: 329\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,071 - optimization.inference - INFO - Scan time: 17.2719\n", + "2024-12-19 13:16:08,072 - optimization.inference - INFO - Number of candidates by RT in frame 1283: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,081 - optimization.inference - INFO - Scan time: 18.7485\n", + "2024-12-19 13:16:08,082 - optimization.inference - INFO - Number of candidates by RT in frame 1369: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,093 - optimization.inference - INFO - Scan time: 17.3577\n", + "2024-12-19 13:16:08,094 - optimization.inference - INFO - Number of candidates by RT in frame 1288: 333\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,100 - optimization.inference - INFO - Scan time: 18.8349\n", + "2024-12-19 13:16:08,101 - optimization.inference - INFO - Number of candidates by RT in frame 1374: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,113 - optimization.inference - INFO - Scan time: 17.4446\n", + "2024-12-19 13:16:08,114 - optimization.inference - INFO - Number of candidates by RT in frame 1293: 321\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,116 - optimization.inference - INFO - Scan time: 18.9207\n", + "2024-12-19 13:16:08,117 - optimization.inference - INFO - Number of candidates by RT in frame 1379: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,132 - optimization.inference - INFO - Scan time: 19.0062\n", + "2024-12-19 13:16:08,133 - optimization.inference - INFO - Number of candidates by RT in frame 1384: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,135 - optimization.inference - INFO - Scan time: 17.5304\n", + "2024-12-19 13:16:08,136 - optimization.inference - INFO - Number of candidates by RT in frame 1298: 348\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,148 - optimization.inference - INFO - Scan time: 19.0921\n", + "2024-12-19 13:16:08,150 - optimization.inference - INFO - Number of candidates by RT in frame 1389: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,155 - optimization.inference - INFO - Scan time: 17.6169\n", + "2024-12-19 13:16:08,156 - optimization.inference - INFO - Number of candidates by RT in frame 1303: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,170 - optimization.inference - INFO - Scan time: 19.1772\n", + "2024-12-19 13:16:08,171 - optimization.inference - INFO - Number of candidates by RT in frame 1394: 332\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,174 - optimization.inference - INFO - Scan time: 17.7023\n", + "2024-12-19 13:16:08,175 - optimization.inference - INFO - Number of candidates by RT in frame 1308: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,188 - optimization.inference - INFO - Scan time: 19.2633\n", + "2024-12-19 13:16:08,189 - optimization.inference - INFO - Number of candidates by RT in frame 1399: 327\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,195 - optimization.inference - INFO - Scan time: 17.7886\n", + "2024-12-19 13:16:08,196 - optimization.inference - INFO - Number of candidates by RT in frame 1313: 337\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,205 - optimization.inference - INFO - Scan time: 19.3491\n", + "2024-12-19 13:16:08,206 - optimization.inference - INFO - Number of candidates by RT in frame 1404: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,214 - optimization.inference - INFO - Scan time: 17.8738\n", + "2024-12-19 13:16:08,215 - optimization.inference - INFO - Number of candidates by RT in frame 1318: 312\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,224 - optimization.inference - INFO - Scan time: 19.4356\n", + "2024-12-19 13:16:08,225 - optimization.inference - INFO - Number of candidates by RT in frame 1409: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,234 - optimization.inference - INFO - Scan time: 17.9597\n", + "2024-12-19 13:16:08,235 - optimization.inference - INFO - Number of candidates by RT in frame 1323: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,241 - optimization.inference - INFO - Scan time: 19.5218\n", + "2024-12-19 13:16:08,242 - optimization.inference - INFO - Number of candidates by RT in frame 1414: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,253 - optimization.inference - INFO - Scan time: 18.045\n", + "2024-12-19 13:16:08,254 - optimization.inference - INFO - Number of candidates by RT in frame 1328: 330\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,260 - optimization.inference - INFO - Scan time: 19.6084\n", + "2024-12-19 13:16:08,261 - optimization.inference - INFO - Number of candidates by RT in frame 1419: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,271 - optimization.inference - INFO - Scan time: 18.1313\n", + "2024-12-19 13:16:08,272 - optimization.inference - INFO - Number of candidates by RT in frame 1333: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,277 - optimization.inference - INFO - Scan time: 19.6938\n", + "2024-12-19 13:16:08,278 - optimization.inference - INFO - Number of candidates by RT in frame 1424: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,291 - optimization.inference - INFO - Scan time: 18.2172\n", + "2024-12-19 13:16:08,292 - optimization.inference - INFO - Number of candidates by RT in frame 1338: 333\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,294 - optimization.inference - INFO - Scan time: 19.7789\n", + "2024-12-19 13:16:08,295 - optimization.inference - INFO - Number of candidates by RT in frame 1429: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,313 - optimization.inference - INFO - Scan time: 19.8641\n", + "2024-12-19 13:16:08,313 - optimization.inference - INFO - Scan time: 18.3034\n", + "2024-12-19 13:16:08,314 - optimization.inference - INFO - Number of candidates by RT in frame 1434: 315\n", + "2024-12-19 13:16:08,314 - optimization.inference - INFO - Number of candidates by RT in frame 1343: 348\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,334 - optimization.inference - INFO - Scan time: 19.95\n", + "2024-12-19 13:16:08,334 - optimization.inference - INFO - Scan time: 18.388\n", + "2024-12-19 13:16:08,335 - optimization.inference - INFO - Number of candidates by RT in frame 1439: 291\n", + "2024-12-19 13:16:08,335 - optimization.inference - INFO - Number of candidates by RT in frame 1348: 335\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,352 - optimization.inference - INFO - Scan time: 20.0351\n", + "2024-12-19 13:16:08,353 - optimization.inference - INFO - Number of candidates by RT in frame 1444: 289\n", + "2024-12-19 13:16:08,353 - optimization.inference - INFO - Scan time: 18.4743\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,354 - optimization.inference - INFO - Number of candidates by RT in frame 1353: 316\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,373 - optimization.inference - INFO - Scan time: 20.1209\n", + "2024-12-19 13:16:08,374 - optimization.inference - INFO - Scan time: 18.56\n", + "2024-12-19 13:16:08,374 - optimization.inference - INFO - Number of candidates by RT in frame 1449: 294\n", + "2024-12-19 13:16:08,375 - optimization.inference - INFO - Number of candidates by RT in frame 1358: 325\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,395 - optimization.inference - INFO - Scan time: 18.6453\n", + "2024-12-19 13:16:08,396 - optimization.inference - INFO - Number of candidates by RT in frame 1363: 335\n", + "2024-12-19 13:16:08,396 - optimization.inference - INFO - Scan time: 20.2074\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,397 - optimization.inference - INFO - Number of candidates by RT in frame 1454: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,415 - optimization.inference - INFO - Scan time: 20.2926\n", + "2024-12-19 13:16:08,416 - optimization.inference - INFO - Scan time: 18.7313\n", + "2024-12-19 13:16:08,416 - optimization.inference - INFO - Number of candidates by RT in frame 1459: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,417 - optimization.inference - INFO - Number of candidates by RT in frame 1368: 314\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,435 - optimization.inference - INFO - Scan time: 18.8176\n", + "2024-12-19 13:16:08,435 - optimization.inference - INFO - Scan time: 20.3776\n", + "2024-12-19 13:16:08,436 - optimization.inference - INFO - Number of candidates by RT in frame 1373: 288\n", + "2024-12-19 13:16:08,436 - optimization.inference - INFO - Number of candidates by RT in frame 1464: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,452 - optimization.inference - INFO - Scan time: 18.9036\n", + "2024-12-19 13:16:08,453 - optimization.inference - INFO - Number of candidates by RT in frame 1378: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,455 - optimization.inference - INFO - Scan time: 20.4632\n", + "2024-12-19 13:16:08,456 - optimization.inference - INFO - Number of candidates by RT in frame 1469: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,466 - optimization.inference - INFO - Scan time: 18.9892\n", + "2024-12-19 13:16:08,467 - optimization.inference - INFO - Number of candidates by RT in frame 1383: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,474 - optimization.inference - INFO - Scan time: 20.5487\n", + "2024-12-19 13:16:08,475 - optimization.inference - INFO - Number of candidates by RT in frame 1474: 297\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,481 - optimization.inference - INFO - Scan time: 19.0751\n", + "2024-12-19 13:16:08,482 - optimization.inference - INFO - Number of candidates by RT in frame 1388: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,496 - optimization.inference - INFO - Scan time: 20.6343\n", + "2024-12-19 13:16:08,497 - optimization.inference - INFO - Number of candidates by RT in frame 1479: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,502 - optimization.inference - INFO - Scan time: 19.1605\n", + "2024-12-19 13:16:08,503 - optimization.inference - INFO - Number of candidates by RT in frame 1393: 327\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,514 - optimization.inference - INFO - Scan time: 20.7203\n", + "2024-12-19 13:16:08,515 - optimization.inference - INFO - Number of candidates by RT in frame 1484: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,522 - optimization.inference - INFO - Scan time: 19.2459\n", + "2024-12-19 13:16:08,523 - optimization.inference - INFO - Number of candidates by RT in frame 1398: 332\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,532 - optimization.inference - INFO - Scan time: 20.8067\n", + "2024-12-19 13:16:08,533 - optimization.inference - INFO - Number of candidates by RT in frame 1489: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,540 - optimization.inference - INFO - Scan time: 19.3322\n", + "2024-12-19 13:16:08,541 - optimization.inference - INFO - Number of candidates by RT in frame 1403: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,548 - optimization.inference - INFO - Scan time: 20.8922\n", + "2024-12-19 13:16:08,549 - optimization.inference - INFO - Number of candidates by RT in frame 1494: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,561 - optimization.inference - INFO - Scan time: 19.4182\n", + "2024-12-19 13:16:08,562 - optimization.inference - INFO - Number of candidates by RT in frame 1408: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,567 - optimization.inference - INFO - Scan time: 20.9779\n", + "2024-12-19 13:16:08,568 - optimization.inference - INFO - Number of candidates by RT in frame 1499: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,577 - optimization.inference - INFO - Scan time: 19.5048\n", + "2024-12-19 13:16:08,578 - optimization.inference - INFO - Number of candidates by RT in frame 1413: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,586 - optimization.inference - INFO - Scan time: 21.0642\n", + "2024-12-19 13:16:08,587 - optimization.inference - INFO - Number of candidates by RT in frame 1504: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,598 - optimization.inference - INFO - Scan time: 19.5909\n", + "2024-12-19 13:16:08,599 - optimization.inference - INFO - Number of candidates by RT in frame 1418: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,605 - optimization.inference - INFO - Scan time: 21.1493\n", + "2024-12-19 13:16:08,606 - optimization.inference - INFO - Number of candidates by RT in frame 1509: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,615 - optimization.inference - INFO - Scan time: 19.6762\n", + "2024-12-19 13:16:08,616 - optimization.inference - INFO - Number of candidates by RT in frame 1423: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,624 - optimization.inference - INFO - Scan time: 21.2348\n", + "2024-12-19 13:16:08,625 - optimization.inference - INFO - Number of candidates by RT in frame 1514: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,633 - optimization.inference - INFO - Scan time: 19.762\n", + "2024-12-19 13:16:08,634 - optimization.inference - INFO - Number of candidates by RT in frame 1428: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,644 - optimization.inference - INFO - Scan time: 21.3214\n", + "2024-12-19 13:16:08,645 - optimization.inference - INFO - Number of candidates by RT in frame 1519: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,652 - optimization.inference - INFO - Scan time: 19.8471\n", + "2024-12-19 13:16:08,653 - optimization.inference - INFO - Number of candidates by RT in frame 1433: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,664 - optimization.inference - INFO - Scan time: 21.4069\n", + "2024-12-19 13:16:08,665 - optimization.inference - INFO - Number of candidates by RT in frame 1524: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,672 - optimization.inference - INFO - Scan time: 19.9326\n", + "2024-12-19 13:16:08,673 - optimization.inference - INFO - Number of candidates by RT in frame 1438: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,686 - optimization.inference - INFO - Scan time: 21.4913\n", + "2024-12-19 13:16:08,687 - optimization.inference - INFO - Number of candidates by RT in frame 1529: 304\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,690 - optimization.inference - INFO - Scan time: 20.018\n", + "2024-12-19 13:16:08,691 - optimization.inference - INFO - Number of candidates by RT in frame 1443: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,707 - optimization.inference - INFO - Scan time: 21.5772\n", + "2024-12-19 13:16:08,708 - optimization.inference - INFO - Number of candidates by RT in frame 1534: 299\n", + "2024-12-19 13:16:08,708 - optimization.inference - INFO - Scan time: 20.104\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,709 - optimization.inference - INFO - Number of candidates by RT in frame 1448: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,728 - optimization.inference - INFO - Scan time: 20.1903\n", + "2024-12-19 13:16:08,728 - optimization.inference - INFO - Scan time: 21.6633\n", + "2024-12-19 13:16:08,729 - optimization.inference - INFO - Number of candidates by RT in frame 1453: 302\n", + "2024-12-19 13:16:08,729 - optimization.inference - INFO - Number of candidates by RT in frame 1539: 299\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,747 - optimization.inference - INFO - Scan time: 21.7481\n", + "2024-12-19 13:16:08,748 - optimization.inference - INFO - Scan time: 20.2755\n", + "2024-12-19 13:16:08,748 - optimization.inference - INFO - Number of candidates by RT in frame 1544: 321\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,749 - optimization.inference - INFO - Number of candidates by RT in frame 1458: 308\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,768 - optimization.inference - INFO - Scan time: 20.3607\n", + "2024-12-19 13:16:08,769 - optimization.inference - INFO - Scan time: 21.8345\n", + "2024-12-19 13:16:08,769 - optimization.inference - INFO - Number of candidates by RT in frame 1463: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,770 - optimization.inference - INFO - Number of candidates by RT in frame 1549: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,789 - optimization.inference - INFO - Scan time: 20.4459\n", + "2024-12-19 13:16:08,790 - optimization.inference - INFO - Number of candidates by RT in frame 1468: 318\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,794 - optimization.inference - INFO - Scan time: 21.9202\n", + "2024-12-19 13:16:08,795 - optimization.inference - INFO - Number of candidates by RT in frame 1554: 323\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,809 - optimization.inference - INFO - Scan time: 20.5316\n", + "2024-12-19 13:16:08,811 - optimization.inference - INFO - Number of candidates by RT in frame 1473: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,823 - optimization.inference - INFO - Scan time: 22.0061\n", + "2024-12-19 13:16:08,824 - optimization.inference - INFO - Number of candidates by RT in frame 1559: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,829 - optimization.inference - INFO - Scan time: 20.6174\n", + "2024-12-19 13:16:08,830 - optimization.inference - INFO - Number of candidates by RT in frame 1478: 306\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,849 - optimization.inference - INFO - Scan time: 22.092\n", + "2024-12-19 13:16:08,849 - optimization.inference - INFO - Scan time: 20.7029\n", + "2024-12-19 13:16:08,850 - optimization.inference - INFO - Number of candidates by RT in frame 1483: 295\n", + "2024-12-19 13:16:08,851 - optimization.inference - INFO - Number of candidates by RT in frame 1564: 315\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,866 - optimization.inference - INFO - Scan time: 20.7894\n", + "2024-12-19 13:16:08,868 - optimization.inference - INFO - Number of candidates by RT in frame 1488: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,874 - optimization.inference - INFO - Scan time: 22.1775\n", + "2024-12-19 13:16:08,875 - optimization.inference - INFO - Number of candidates by RT in frame 1569: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,883 - optimization.inference - INFO - Scan time: 20.8752\n", + "2024-12-19 13:16:08,884 - optimization.inference - INFO - Number of candidates by RT in frame 1493: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,900 - optimization.inference - INFO - Scan time: 20.9605\n", + "2024-12-19 13:16:08,902 - optimization.inference - INFO - Number of candidates by RT in frame 1498: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,913 - optimization.inference - INFO - Scan time: 22.2628\n", + "2024-12-19 13:16:08,914 - optimization.inference - INFO - Number of candidates by RT in frame 1574: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,921 - optimization.inference - INFO - Scan time: 21.0469\n", + "2024-12-19 13:16:08,922 - optimization.inference - INFO - Number of candidates by RT in frame 1503: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,934 - optimization.inference - INFO - Scan time: 22.3482\n", + "2024-12-19 13:16:08,935 - optimization.inference - INFO - Number of candidates by RT in frame 1579: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,939 - optimization.inference - INFO - Scan time: 21.1323\n", + "2024-12-19 13:16:08,940 - optimization.inference - INFO - Number of candidates by RT in frame 1508: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,957 - optimization.inference - INFO - Scan time: 21.2179\n", + "2024-12-19 13:16:08,958 - optimization.inference - INFO - Number of candidates by RT in frame 1513: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,960 - optimization.inference - INFO - Scan time: 22.4336\n", + "2024-12-19 13:16:08,961 - optimization.inference - INFO - Number of candidates by RT in frame 1584: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,979 - optimization.inference - INFO - Scan time: 21.3041\n", + "2024-12-19 13:16:08,980 - optimization.inference - INFO - Number of candidates by RT in frame 1518: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:08,981 - optimization.inference - INFO - Scan time: 22.5201\n", + "2024-12-19 13:16:08,982 - optimization.inference - INFO - Number of candidates by RT in frame 1589: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,001 - optimization.inference - INFO - Scan time: 21.39\n", + "2024-12-19 13:16:09,001 - optimization.inference - INFO - Scan time: 22.6052\n", + "2024-12-19 13:16:09,002 - optimization.inference - INFO - Number of candidates by RT in frame 1523: 293\n", + "2024-12-19 13:16:09,002 - optimization.inference - INFO - Number of candidates by RT in frame 1594: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,019 - optimization.inference - INFO - Scan time: 22.6902\n", + "2024-12-19 13:16:09,020 - optimization.inference - INFO - Number of candidates by RT in frame 1599: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,021 - optimization.inference - INFO - Scan time: 21.4744\n", + "2024-12-19 13:16:09,022 - optimization.inference - INFO - Number of candidates by RT in frame 1528: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,038 - optimization.inference - INFO - Scan time: 22.7763\n", + "2024-12-19 13:16:09,039 - optimization.inference - INFO - Scan time: 21.5598\n", + "2024-12-19 13:16:09,040 - optimization.inference - INFO - Number of candidates by RT in frame 1604: 283\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,040 - optimization.inference - INFO - Number of candidates by RT in frame 1533: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,057 - optimization.inference - INFO - Scan time: 22.8625\n", + "2024-12-19 13:16:09,057 - optimization.inference - INFO - Scan time: 21.6464\n", + "2024-12-19 13:16:09,058 - optimization.inference - INFO - Number of candidates by RT in frame 1609: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,058 - optimization.inference - INFO - Number of candidates by RT in frame 1538: 300\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,075 - optimization.inference - INFO - Scan time: 22.949\n", + "2024-12-19 13:16:09,076 - optimization.inference - INFO - Number of candidates by RT in frame 1614: 290\n", + "2024-12-19 13:16:09,076 - optimization.inference - INFO - Scan time: 21.7313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,077 - optimization.inference - INFO - Number of candidates by RT in frame 1543: 320\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,094 - optimization.inference - INFO - Scan time: 23.0348\n", + "2024-12-19 13:16:09,095 - optimization.inference - INFO - Number of candidates by RT in frame 1619: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,097 - optimization.inference - INFO - Scan time: 21.817\n", + "2024-12-19 13:16:09,098 - optimization.inference - INFO - Number of candidates by RT in frame 1548: 326\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,110 - optimization.inference - INFO - Scan time: 23.1204\n", + "2024-12-19 13:16:09,111 - optimization.inference - INFO - Number of candidates by RT in frame 1624: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,119 - optimization.inference - INFO - Scan time: 21.9031\n", + "2024-12-19 13:16:09,120 - optimization.inference - INFO - Number of candidates by RT in frame 1553: 327\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,129 - optimization.inference - INFO - Scan time: 23.2066\n", + "2024-12-19 13:16:09,130 - optimization.inference - INFO - Number of candidates by RT in frame 1629: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,140 - optimization.inference - INFO - Scan time: 21.989\n", + "2024-12-19 13:16:09,141 - optimization.inference - INFO - Number of candidates by RT in frame 1558: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,148 - optimization.inference - INFO - Scan time: 23.2915\n", + "2024-12-19 13:16:09,149 - optimization.inference - INFO - Number of candidates by RT in frame 1634: 292\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,165 - optimization.inference - INFO - Scan time: 22.075\n", + "2024-12-19 13:16:09,167 - optimization.inference - INFO - Number of candidates by RT in frame 1563: 314\n", + "2024-12-19 13:16:09,167 - optimization.inference - INFO - Scan time: 23.3777\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,168 - optimization.inference - INFO - Number of candidates by RT in frame 1639: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,188 - optimization.inference - INFO - Scan time: 22.1606\n", + "2024-12-19 13:16:09,188 - optimization.inference - INFO - Scan time: 23.4631\n", + "2024-12-19 13:16:09,189 - optimization.inference - INFO - Number of candidates by RT in frame 1568: 299\n", + "2024-12-19 13:16:09,189 - optimization.inference - INFO - Number of candidates by RT in frame 1644: 295\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,208 - optimization.inference - INFO - Scan time: 23.5481\n", + "2024-12-19 13:16:09,209 - optimization.inference - INFO - Number of candidates by RT in frame 1649: 284\n", + "2024-12-19 13:16:09,209 - optimization.inference - INFO - Scan time: 22.2456\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,210 - optimization.inference - INFO - Number of candidates by RT in frame 1573: 307\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,227 - optimization.inference - INFO - Scan time: 23.6339\n", + "2024-12-19 13:16:09,228 - optimization.inference - INFO - Number of candidates by RT in frame 1654: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,230 - optimization.inference - INFO - Scan time: 22.3308\n", + "2024-12-19 13:16:09,231 - optimization.inference - INFO - Number of candidates by RT in frame 1578: 310\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,246 - optimization.inference - INFO - Scan time: 23.7194\n", + "2024-12-19 13:16:09,248 - optimization.inference - INFO - Number of candidates by RT in frame 1659: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,257 - optimization.inference - INFO - Scan time: 22.4165\n", + "2024-12-19 13:16:09,258 - optimization.inference - INFO - Number of candidates by RT in frame 1583: 311\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,263 - optimization.inference - INFO - Scan time: 23.8052\n", + "2024-12-19 13:16:09,264 - optimization.inference - INFO - Number of candidates by RT in frame 1664: 257\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,281 - optimization.inference - INFO - Scan time: 23.8917\n", + "2024-12-19 13:16:09,282 - optimization.inference - INFO - Number of candidates by RT in frame 1669: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,284 - optimization.inference - INFO - Scan time: 22.5029\n", + "2024-12-19 13:16:09,285 - optimization.inference - INFO - Number of candidates by RT in frame 1588: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,299 - optimization.inference - INFO - Scan time: 23.9763\n", + "2024-12-19 13:16:09,300 - optimization.inference - INFO - Number of candidates by RT in frame 1674: 256\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,308 - optimization.inference - INFO - Scan time: 22.5885\n", + "2024-12-19 13:16:09,309 - optimization.inference - INFO - Number of candidates by RT in frame 1593: 284\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,311 - optimization.inference - INFO - Scan time: 24.0626\n", + "2024-12-19 13:16:09,312 - optimization.inference - INFO - Number of candidates by RT in frame 1679: 243\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,328 - optimization.inference - INFO - Scan time: 24.1478\n", + "2024-12-19 13:16:09,329 - optimization.inference - INFO - Number of candidates by RT in frame 1684: 253\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,345 - optimization.inference - INFO - Scan time: 22.6733\n", + "2024-12-19 13:16:09,346 - optimization.inference - INFO - Number of candidates by RT in frame 1598: 269\n", + "2024-12-19 13:16:09,347 - optimization.inference - INFO - Scan time: 24.2338\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,348 - optimization.inference - INFO - Number of candidates by RT in frame 1689: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,365 - optimization.inference - INFO - Scan time: 22.759\n", + "2024-12-19 13:16:09,366 - optimization.inference - INFO - Number of candidates by RT in frame 1603: 281\n", + "2024-12-19 13:16:09,366 - optimization.inference - INFO - Scan time: 24.3195\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,367 - optimization.inference - INFO - Number of candidates by RT in frame 1694: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,383 - optimization.inference - INFO - Scan time: 22.8451\n", + "2024-12-19 13:16:09,384 - optimization.inference - INFO - Number of candidates by RT in frame 1608: 276\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,387 - optimization.inference - INFO - Scan time: 24.405\n", + "2024-12-19 13:16:09,388 - optimization.inference - INFO - Number of candidates by RT in frame 1699: 251\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,399 - optimization.inference - INFO - Scan time: 22.9318\n", + "2024-12-19 13:16:09,400 - optimization.inference - INFO - Number of candidates by RT in frame 1613: 283\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,403 - optimization.inference - INFO - Scan time: 24.491\n", + "2024-12-19 13:16:09,404 - optimization.inference - INFO - Number of candidates by RT in frame 1704: 255\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,418 - optimization.inference - INFO - Scan time: 23.0179\n", + "2024-12-19 13:16:09,419 - optimization.inference - INFO - Number of candidates by RT in frame 1618: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,421 - optimization.inference - INFO - Scan time: 24.5777\n", + "2024-12-19 13:16:09,422 - optimization.inference - INFO - Number of candidates by RT in frame 1709: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,436 - optimization.inference - INFO - Scan time: 23.1031\n", + "2024-12-19 13:16:09,437 - optimization.inference - INFO - Number of candidates by RT in frame 1623: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,439 - optimization.inference - INFO - Scan time: 24.6636\n", + "2024-12-19 13:16:09,440 - optimization.inference - INFO - Number of candidates by RT in frame 1714: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,454 - optimization.inference - INFO - Scan time: 23.1892\n", + "2024-12-19 13:16:09,455 - optimization.inference - INFO - Number of candidates by RT in frame 1628: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,458 - optimization.inference - INFO - Scan time: 24.7497\n", + "2024-12-19 13:16:09,459 - optimization.inference - INFO - Number of candidates by RT in frame 1719: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,472 - optimization.inference - INFO - Scan time: 23.2747\n", + "2024-12-19 13:16:09,473 - optimization.inference - INFO - Number of candidates by RT in frame 1633: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,479 - optimization.inference - INFO - Scan time: 24.8347\n", + "2024-12-19 13:16:09,480 - optimization.inference - INFO - Number of candidates by RT in frame 1724: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,492 - optimization.inference - INFO - Scan time: 23.3606\n", + "2024-12-19 13:16:09,493 - optimization.inference - INFO - Number of candidates by RT in frame 1638: 290\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,500 - optimization.inference - INFO - Scan time: 24.9193\n", + "2024-12-19 13:16:09,501 - optimization.inference - INFO - Number of candidates by RT in frame 1729: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,514 - optimization.inference - INFO - Scan time: 23.4461\n", + "2024-12-19 13:16:09,515 - optimization.inference - INFO - Number of candidates by RT in frame 1643: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,518 - optimization.inference - INFO - Scan time: 25.0046\n", + "2024-12-19 13:16:09,519 - optimization.inference - INFO - Number of candidates by RT in frame 1734: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,534 - optimization.inference - INFO - Scan time: 25.0898\n", + "2024-12-19 13:16:09,535 - optimization.inference - INFO - Number of candidates by RT in frame 1739: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,536 - optimization.inference - INFO - Scan time: 23.5308\n", + "2024-12-19 13:16:09,537 - optimization.inference - INFO - Number of candidates by RT in frame 1648: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,554 - optimization.inference - INFO - Scan time: 23.6163\n", + "2024-12-19 13:16:09,555 - optimization.inference - INFO - Scan time: 25.1758\n", + "2024-12-19 13:16:09,555 - optimization.inference - INFO - Number of candidates by RT in frame 1653: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,556 - optimization.inference - INFO - Number of candidates by RT in frame 1744: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,575 - optimization.inference - INFO - Scan time: 23.7024\n", + "2024-12-19 13:16:09,575 - optimization.inference - INFO - Scan time: 25.2623\n", + "2024-12-19 13:16:09,576 - optimization.inference - INFO - Number of candidates by RT in frame 1658: 269\n", + "2024-12-19 13:16:09,576 - optimization.inference - INFO - Number of candidates by RT in frame 1749: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,592 - optimization.inference - INFO - Scan time: 23.7877\n", + "2024-12-19 13:16:09,593 - optimization.inference - INFO - Number of candidates by RT in frame 1663: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,595 - optimization.inference - INFO - Scan time: 25.3486\n", + "2024-12-19 13:16:09,596 - optimization.inference - INFO - Number of candidates by RT in frame 1754: 283\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,611 - optimization.inference - INFO - Scan time: 23.8747\n", + "2024-12-19 13:16:09,612 - optimization.inference - INFO - Number of candidates by RT in frame 1668: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,615 - optimization.inference - INFO - Scan time: 25.4343\n", + "2024-12-19 13:16:09,616 - optimization.inference - INFO - Number of candidates by RT in frame 1759: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,629 - optimization.inference - INFO - Scan time: 23.9593\n", + "2024-12-19 13:16:09,630 - optimization.inference - INFO - Number of candidates by RT in frame 1673: 256\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,633 - optimization.inference - INFO - Scan time: 25.5194\n", + "2024-12-19 13:16:09,635 - optimization.inference - INFO - Number of candidates by RT in frame 1764: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,642 - optimization.inference - INFO - Scan time: 24.0453\n", + "2024-12-19 13:16:09,643 - optimization.inference - INFO - Number of candidates by RT in frame 1678: 252\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,649 - optimization.inference - INFO - Scan time: 25.6052\n", + "2024-12-19 13:16:09,650 - optimization.inference - INFO - Number of candidates by RT in frame 1769: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,660 - optimization.inference - INFO - Scan time: 24.1311\n", + "2024-12-19 13:16:09,661 - optimization.inference - INFO - Number of candidates by RT in frame 1683: 248\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,672 - optimization.inference - INFO - Scan time: 25.6911\n", + "2024-12-19 13:16:09,673 - optimization.inference - INFO - Number of candidates by RT in frame 1774: 293\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,678 - optimization.inference - INFO - Scan time: 24.2167\n", + "2024-12-19 13:16:09,679 - optimization.inference - INFO - Number of candidates by RT in frame 1688: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,693 - optimization.inference - INFO - Scan time: 25.7776\n", + "2024-12-19 13:16:09,694 - optimization.inference - INFO - Number of candidates by RT in frame 1779: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,698 - optimization.inference - INFO - Scan time: 24.3026\n", + "2024-12-19 13:16:09,699 - optimization.inference - INFO - Number of candidates by RT in frame 1693: 259\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,711 - optimization.inference - INFO - Scan time: 25.8637\n", + "2024-12-19 13:16:09,712 - optimization.inference - INFO - Number of candidates by RT in frame 1784: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,719 - optimization.inference - INFO - Scan time: 24.3878\n", + "2024-12-19 13:16:09,720 - optimization.inference - INFO - Number of candidates by RT in frame 1698: 255\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,729 - optimization.inference - INFO - Scan time: 25.9498\n", + "2024-12-19 13:16:09,730 - optimization.inference - INFO - Number of candidates by RT in frame 1789: 281\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,736 - optimization.inference - INFO - Scan time: 24.4741\n", + "2024-12-19 13:16:09,737 - optimization.inference - INFO - Number of candidates by RT in frame 1703: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,746 - optimization.inference - INFO - Scan time: 26.0359\n", + "2024-12-19 13:16:09,747 - optimization.inference - INFO - Number of candidates by RT in frame 1794: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,754 - optimization.inference - INFO - Scan time: 24.5601\n", + "2024-12-19 13:16:09,755 - optimization.inference - INFO - Number of candidates by RT in frame 1708: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,768 - optimization.inference - INFO - Scan time: 26.1218\n", + "2024-12-19 13:16:09,769 - optimization.inference - INFO - Number of candidates by RT in frame 1799: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,773 - optimization.inference - INFO - Scan time: 24.6463\n", + "2024-12-19 13:16:09,774 - optimization.inference - INFO - Number of candidates by RT in frame 1713: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,788 - optimization.inference - INFO - Scan time: 26.2082\n", + "2024-12-19 13:16:09,789 - optimization.inference - INFO - Number of candidates by RT in frame 1804: 291\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,792 - optimization.inference - INFO - Scan time: 24.7322\n", + "2024-12-19 13:16:09,793 - optimization.inference - INFO - Number of candidates by RT in frame 1718: 278\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,810 - optimization.inference - INFO - Scan time: 26.2944\n", + "2024-12-19 13:16:09,811 - optimization.inference - INFO - Scan time: 24.8174\n", + "2024-12-19 13:16:09,811 - optimization.inference - INFO - Number of candidates by RT in frame 1809: 303\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,812 - optimization.inference - INFO - Number of candidates by RT in frame 1723: 275\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,832 - optimization.inference - INFO - Scan time: 24.9023\n", + "2024-12-19 13:16:09,833 - optimization.inference - INFO - Number of candidates by RT in frame 1728: 274\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,834 - optimization.inference - INFO - Scan time: 26.3808\n", + "2024-12-19 13:16:09,835 - optimization.inference - INFO - Number of candidates by RT in frame 1814: 313\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,856 - optimization.inference - INFO - Scan time: 26.4661\n", + "2024-12-19 13:16:09,857 - optimization.inference - INFO - Scan time: 24.9877\n", + "2024-12-19 13:16:09,857 - optimization.inference - INFO - Number of candidates by RT in frame 1819: 305\n", + "2024-12-19 13:16:09,858 - optimization.inference - INFO - Number of candidates by RT in frame 1733: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,872 - optimization.inference - INFO - Scan time: 25.0724\n", + "2024-12-19 13:16:09,874 - optimization.inference - INFO - Number of candidates by RT in frame 1738: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,879 - optimization.inference - INFO - Scan time: 26.551\n", + "2024-12-19 13:16:09,880 - optimization.inference - INFO - Number of candidates by RT in frame 1824: 298\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,893 - optimization.inference - INFO - Scan time: 25.1587\n", + "2024-12-19 13:16:09,894 - optimization.inference - INFO - Number of candidates by RT in frame 1743: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,900 - optimization.inference - INFO - Scan time: 26.637\n", + "2024-12-19 13:16:09,901 - optimization.inference - INFO - Number of candidates by RT in frame 1829: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,912 - optimization.inference - INFO - Scan time: 25.2448\n", + "2024-12-19 13:16:09,914 - optimization.inference - INFO - Number of candidates by RT in frame 1748: 296\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,920 - optimization.inference - INFO - Scan time: 26.724\n", + "2024-12-19 13:16:09,921 - optimization.inference - INFO - Number of candidates by RT in frame 1834: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,934 - optimization.inference - INFO - Scan time: 25.3313\n", + "2024-12-19 13:16:09,935 - optimization.inference - INFO - Number of candidates by RT in frame 1753: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,938 - optimization.inference - INFO - Scan time: 26.809\n", + "2024-12-19 13:16:09,939 - optimization.inference - INFO - Number of candidates by RT in frame 1839: 279\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,955 - optimization.inference - INFO - Scan time: 25.417\n", + "2024-12-19 13:16:09,955 - optimization.inference - INFO - Scan time: 26.895\n", + "2024-12-19 13:16:09,956 - optimization.inference - INFO - Number of candidates by RT in frame 1844: 261\n", + "2024-12-19 13:16:09,956 - optimization.inference - INFO - Number of candidates by RT in frame 1758: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,973 - optimization.inference - INFO - Scan time: 26.981\n", + "2024-12-19 13:16:09,974 - optimization.inference - INFO - Number of candidates by RT in frame 1849: 276\n", + "2024-12-19 13:16:09,975 - optimization.inference - INFO - Scan time: 25.5028\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,976 - optimization.inference - INFO - Number of candidates by RT in frame 1763: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,992 - optimization.inference - INFO - Scan time: 27.0669\n", + "2024-12-19 13:16:09,993 - optimization.inference - INFO - Scan time: 25.5884\n", + "2024-12-19 13:16:09,994 - optimization.inference - INFO - Number of candidates by RT in frame 1854: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:09,994 - optimization.inference - INFO - Number of candidates by RT in frame 1768: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,016 - optimization.inference - INFO - Scan time: 27.1522\n", + "2024-12-19 13:16:10,017 - optimization.inference - INFO - Number of candidates by RT in frame 1859: 285\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,019 - optimization.inference - INFO - Scan time: 25.6739\n", + "2024-12-19 13:16:10,020 - optimization.inference - INFO - Number of candidates by RT in frame 1773: 286\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,034 - optimization.inference - INFO - Scan time: 27.2378\n", + "2024-12-19 13:16:10,035 - optimization.inference - INFO - Number of candidates by RT in frame 1864: 273\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,040 - optimization.inference - INFO - Scan time: 25.7602\n", + "2024-12-19 13:16:10,041 - optimization.inference - INFO - Number of candidates by RT in frame 1778: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,055 - optimization.inference - INFO - Scan time: 27.3231\n", + "2024-12-19 13:16:10,056 - optimization.inference - INFO - Number of candidates by RT in frame 1869: 271\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,061 - optimization.inference - INFO - Scan time: 25.8462\n", + "2024-12-19 13:16:10,062 - optimization.inference - INFO - Number of candidates by RT in frame 1783: 268\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,075 - optimization.inference - INFO - Scan time: 27.4083\n", + "2024-12-19 13:16:10,076 - optimization.inference - INFO - Number of candidates by RT in frame 1874: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,079 - optimization.inference - INFO - Scan time: 25.9325\n", + "2024-12-19 13:16:10,080 - optimization.inference - INFO - Number of candidates by RT in frame 1788: 284\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,091 - optimization.inference - INFO - Scan time: 27.4963\n", + "2024-12-19 13:16:10,092 - optimization.inference - INFO - Number of candidates by RT in frame 1879: 261\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,097 - optimization.inference - INFO - Scan time: 26.0183\n", + "2024-12-19 13:16:10,098 - optimization.inference - INFO - Number of candidates by RT in frame 1793: 262\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,107 - optimization.inference - INFO - Scan time: 27.5819\n", + "2024-12-19 13:16:10,108 - optimization.inference - INFO - Number of candidates by RT in frame 1884: 249\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,119 - optimization.inference - INFO - Scan time: 26.1046\n", + "2024-12-19 13:16:10,120 - optimization.inference - INFO - Number of candidates by RT in frame 1798: 289\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,126 - optimization.inference - INFO - Scan time: 27.6687\n", + "2024-12-19 13:16:10,127 - optimization.inference - INFO - Number of candidates by RT in frame 1889: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,139 - optimization.inference - INFO - Scan time: 26.1908\n", + "2024-12-19 13:16:10,140 - optimization.inference - INFO - Number of candidates by RT in frame 1803: 288\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,146 - optimization.inference - INFO - Scan time: 27.7552\n", + "2024-12-19 13:16:10,147 - optimization.inference - INFO - Number of candidates by RT in frame 1894: 270\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,160 - optimization.inference - INFO - Scan time: 26.2773\n", + "2024-12-19 13:16:10,162 - optimization.inference - INFO - Number of candidates by RT in frame 1808: 301\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,167 - optimization.inference - INFO - Scan time: 27.8411\n", + "2024-12-19 13:16:10,168 - optimization.inference - INFO - Number of candidates by RT in frame 1899: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,185 - optimization.inference - INFO - Scan time: 26.3639\n", + "2024-12-19 13:16:10,186 - optimization.inference - INFO - Number of candidates by RT in frame 1813: 309\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,187 - optimization.inference - INFO - Scan time: 27.9266\n", + "2024-12-19 13:16:10,188 - optimization.inference - INFO - Number of candidates by RT in frame 1904: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,207 - optimization.inference - INFO - Scan time: 28.0117\n", + "2024-12-19 13:16:10,208 - optimization.inference - INFO - Scan time: 26.4489\n", + "2024-12-19 13:16:10,208 - optimization.inference - INFO - Number of candidates by RT in frame 1909: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,209 - optimization.inference - INFO - Number of candidates by RT in frame 1818: 305\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,227 - optimization.inference - INFO - Scan time: 28.0974\n", + "2024-12-19 13:16:10,228 - optimization.inference - INFO - Number of candidates by RT in frame 1914: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,231 - optimization.inference - INFO - Scan time: 26.534\n", + "2024-12-19 13:16:10,232 - optimization.inference - INFO - Number of candidates by RT in frame 1823: 302\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,247 - optimization.inference - INFO - Scan time: 28.1829\n", + "2024-12-19 13:16:10,248 - optimization.inference - INFO - Number of candidates by RT in frame 1919: 239\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,252 - optimization.inference - INFO - Scan time: 26.6201\n", + "2024-12-19 13:16:10,253 - optimization.inference - INFO - Number of candidates by RT in frame 1828: 272\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,266 - optimization.inference - INFO - Scan time: 28.2683\n", + "2024-12-19 13:16:10,268 - optimization.inference - INFO - Number of candidates by RT in frame 1924: 242\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,272 - optimization.inference - INFO - Scan time: 26.7065\n", + "2024-12-19 13:16:10,273 - optimization.inference - INFO - Number of candidates by RT in frame 1833: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,282 - optimization.inference - INFO - Scan time: 28.3535\n", + "2024-12-19 13:16:10,283 - optimization.inference - INFO - Number of candidates by RT in frame 1929: 243\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,291 - optimization.inference - INFO - Scan time: 26.7919\n", + "2024-12-19 13:16:10,293 - optimization.inference - INFO - Number of candidates by RT in frame 1838: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,299 - optimization.inference - INFO - Scan time: 28.4386\n", + "2024-12-19 13:16:10,300 - optimization.inference - INFO - Number of candidates by RT in frame 1934: 228\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,308 - optimization.inference - INFO - Scan time: 26.8776\n", + "2024-12-19 13:16:10,309 - optimization.inference - INFO - Number of candidates by RT in frame 1843: 260\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,317 - optimization.inference - INFO - Scan time: 28.5245\n", + "2024-12-19 13:16:10,318 - optimization.inference - INFO - Number of candidates by RT in frame 1939: 235\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,326 - optimization.inference - INFO - Scan time: 26.9636\n", + "2024-12-19 13:16:10,327 - optimization.inference - INFO - Number of candidates by RT in frame 1848: 282\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,335 - optimization.inference - INFO - Scan time: 28.6097\n", + "2024-12-19 13:16:10,336 - optimization.inference - INFO - Number of candidates by RT in frame 1944: 239\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,345 - optimization.inference - INFO - Scan time: 27.05\n", + "2024-12-19 13:16:10,346 - optimization.inference - INFO - Number of candidates by RT in frame 1853: 280\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,352 - optimization.inference - INFO - Scan time: 28.695\n", + "2024-12-19 13:16:10,353 - optimization.inference - INFO - Number of candidates by RT in frame 1949: 217\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,367 - optimization.inference - INFO - Scan time: 27.1353\n", + "2024-12-19 13:16:10,368 - optimization.inference - INFO - Number of candidates by RT in frame 1858: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,369 - optimization.inference - INFO - Scan time: 28.7802\n", + "2024-12-19 13:16:10,370 - optimization.inference - INFO - Number of candidates by RT in frame 1954: 206\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,387 - optimization.inference - INFO - Scan time: 27.2206\n", + "2024-12-19 13:16:10,387 - optimization.inference - INFO - Scan time: 28.8659\n", + "2024-12-19 13:16:10,388 - optimization.inference - INFO - Number of candidates by RT in frame 1959: 205\n", + "2024-12-19 13:16:10,388 - optimization.inference - INFO - Number of candidates by RT in frame 1863: 287\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,402 - optimization.inference - INFO - Scan time: 28.952\n", + "2024-12-19 13:16:10,403 - optimization.inference - INFO - Number of candidates by RT in frame 1964: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,410 - optimization.inference - INFO - Scan time: 27.3064\n", + "2024-12-19 13:16:10,411 - optimization.inference - INFO - Number of candidates by RT in frame 1868: 269\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,418 - optimization.inference - INFO - Scan time: 29.0381\n", + "2024-12-19 13:16:10,419 - optimization.inference - INFO - Number of candidates by RT in frame 1969: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,429 - optimization.inference - INFO - Scan time: 27.3915\n", + "2024-12-19 13:16:10,430 - optimization.inference - INFO - Number of candidates by RT in frame 1873: 267\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,436 - optimization.inference - INFO - Scan time: 29.124\n", + "2024-12-19 13:16:10,437 - optimization.inference - INFO - Number of candidates by RT in frame 1974: 217\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,446 - optimization.inference - INFO - Scan time: 27.479\n", + "2024-12-19 13:16:10,447 - optimization.inference - INFO - Number of candidates by RT in frame 1878: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,450 - optimization.inference - INFO - Scan time: 29.2087\n", + "2024-12-19 13:16:10,451 - optimization.inference - INFO - Number of candidates by RT in frame 1979: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,465 - optimization.inference - INFO - Scan time: 27.5647\n", + "2024-12-19 13:16:10,466 - optimization.inference - INFO - Number of candidates by RT in frame 1883: 243\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,467 - optimization.inference - INFO - Scan time: 29.2944\n", + "2024-12-19 13:16:10,468 - optimization.inference - INFO - Number of candidates by RT in frame 1984: 214\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,484 - optimization.inference - INFO - Scan time: 27.6516\n", + "2024-12-19 13:16:10,485 - optimization.inference - INFO - Scan time: 29.3795\n", + "2024-12-19 13:16:10,485 - optimization.inference - INFO - Number of candidates by RT in frame 1888: 259\n", + "2024-12-19 13:16:10,486 - optimization.inference - INFO - Number of candidates by RT in frame 1989: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,501 - optimization.inference - INFO - Scan time: 29.4659\n", + "2024-12-19 13:16:10,502 - optimization.inference - INFO - Number of candidates by RT in frame 1994: 205\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,507 - optimization.inference - INFO - Scan time: 27.7378\n", + "2024-12-19 13:16:10,508 - optimization.inference - INFO - Number of candidates by RT in frame 1893: 277\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,519 - optimization.inference - INFO - Scan time: 29.5519\n", + "2024-12-19 13:16:10,520 - optimization.inference - INFO - Number of candidates by RT in frame 1999: 211\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,528 - optimization.inference - INFO - Scan time: 27.8237\n", + "2024-12-19 13:16:10,529 - optimization.inference - INFO - Number of candidates by RT in frame 1898: 266\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,534 - optimization.inference - INFO - Scan time: 29.6374\n", + "2024-12-19 13:16:10,535 - optimization.inference - INFO - Number of candidates by RT in frame 2004: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,547 - optimization.inference - INFO - Scan time: 27.9094\n", + "2024-12-19 13:16:10,548 - optimization.inference - INFO - Number of candidates by RT in frame 1903: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,551 - optimization.inference - INFO - Scan time: 29.7233\n", + "2024-12-19 13:16:10,552 - optimization.inference - INFO - Number of candidates by RT in frame 2009: 193\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,566 - optimization.inference - INFO - Scan time: 29.8088\n", + "2024-12-19 13:16:10,567 - optimization.inference - INFO - Number of candidates by RT in frame 2014: 203\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,570 - optimization.inference - INFO - Scan time: 27.9948\n", + "2024-12-19 13:16:10,575 - optimization.inference - INFO - Number of candidates by RT in frame 1908: 264\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,583 - optimization.inference - INFO - Scan time: 29.8947\n", + "2024-12-19 13:16:10,584 - optimization.inference - INFO - Number of candidates by RT in frame 2019: 207\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,596 - optimization.inference - INFO - Scan time: 29.9807\n", + "2024-12-19 13:16:10,597 - optimization.inference - INFO - Number of candidates by RT in frame 2024: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,599 - optimization.inference - INFO - Scan time: 28.0802\n", + "2024-12-19 13:16:10,600 - optimization.inference - INFO - Number of candidates by RT in frame 1913: 265\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,613 - optimization.inference - INFO - Scan time: 30.067\n", + "2024-12-19 13:16:10,614 - optimization.inference - INFO - Number of candidates by RT in frame 2029: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,620 - optimization.inference - INFO - Scan time: 28.166\n", + "2024-12-19 13:16:10,621 - optimization.inference - INFO - Number of candidates by RT in frame 1918: 247\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,630 - optimization.inference - INFO - Scan time: 30.1528\n", + "2024-12-19 13:16:10,631 - optimization.inference - INFO - Number of candidates by RT in frame 2034: 181\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,640 - optimization.inference - INFO - Scan time: 28.251\n", + "2024-12-19 13:16:10,641 - optimization.inference - INFO - Number of candidates by RT in frame 1923: 246\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,644 - optimization.inference - INFO - Scan time: 30.2384\n", + "2024-12-19 13:16:10,645 - optimization.inference - INFO - Number of candidates by RT in frame 2039: 171\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,658 - optimization.inference - INFO - Scan time: 30.3245\n", + "2024-12-19 13:16:10,658 - optimization.inference - INFO - Scan time: 28.3367\n", + "2024-12-19 13:16:10,659 - optimization.inference - INFO - Number of candidates by RT in frame 2044: 180\n", + "2024-12-19 13:16:10,659 - optimization.inference - INFO - Number of candidates by RT in frame 1928: 250\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,672 - optimization.inference - INFO - Scan time: 30.4105\n", + "2024-12-19 13:16:10,673 - optimization.inference - INFO - Number of candidates by RT in frame 2049: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,674 - optimization.inference - INFO - Scan time: 28.4218\n", + "2024-12-19 13:16:10,675 - optimization.inference - INFO - Number of candidates by RT in frame 1933: 230\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,688 - optimization.inference - INFO - Scan time: 30.4967\n", + "2024-12-19 13:16:10,689 - optimization.inference - INFO - Number of candidates by RT in frame 2054: 213\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,690 - optimization.inference - INFO - Scan time: 28.5075\n", + "2024-12-19 13:16:10,691 - optimization.inference - INFO - Number of candidates by RT in frame 1938: 236\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,703 - optimization.inference - INFO - Scan time: 30.5827\n", + "2024-12-19 13:16:10,704 - optimization.inference - INFO - Number of candidates by RT in frame 2059: 220\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,712 - optimization.inference - INFO - Scan time: 28.5929\n", + "2024-12-19 13:16:10,713 - optimization.inference - INFO - Number of candidates by RT in frame 1943: 238\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,718 - optimization.inference - INFO - Scan time: 30.6679\n", + "2024-12-19 13:16:10,719 - optimization.inference - INFO - Number of candidates by RT in frame 2064: 221\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,730 - optimization.inference - INFO - Scan time: 28.6781\n", + "2024-12-19 13:16:10,731 - optimization.inference - INFO - Number of candidates by RT in frame 1948: 210\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,736 - optimization.inference - INFO - Scan time: 30.7528\n", + "2024-12-19 13:16:10,737 - optimization.inference - INFO - Number of candidates by RT in frame 2069: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,748 - optimization.inference - INFO - Scan time: 28.7633\n", + "2024-12-19 13:16:10,749 - optimization.inference - INFO - Number of candidates by RT in frame 1953: 206\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,753 - optimization.inference - INFO - Scan time: 30.8388\n", + "2024-12-19 13:16:10,754 - optimization.inference - INFO - Number of candidates by RT in frame 2074: 192\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,766 - optimization.inference - INFO - Scan time: 28.8488\n", + "2024-12-19 13:16:10,767 - optimization.inference - INFO - Number of candidates by RT in frame 1958: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,771 - optimization.inference - INFO - Scan time: 30.9244\n", + "2024-12-19 13:16:10,772 - optimization.inference - INFO - Number of candidates by RT in frame 2079: 198\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,783 - optimization.inference - INFO - Scan time: 28.9349\n", + "2024-12-19 13:16:10,784 - optimization.inference - INFO - Scan time: 31.01\n", + "2024-12-19 13:16:10,784 - optimization.inference - INFO - Number of candidates by RT in frame 1963: 201\n", + "2024-12-19 13:16:10,785 - optimization.inference - INFO - Number of candidates by RT in frame 2084: 184\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,798 - optimization.inference - INFO - Scan time: 31.0957\n", + "2024-12-19 13:16:10,799 - optimization.inference - INFO - Number of candidates by RT in frame 2089: 215\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,803 - optimization.inference - INFO - Scan time: 29.0207\n", + "2024-12-19 13:16:10,805 - optimization.inference - INFO - Number of candidates by RT in frame 1968: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,814 - optimization.inference - INFO - Scan time: 31.1815\n", + "2024-12-19 13:16:10,815 - optimization.inference - INFO - Number of candidates by RT in frame 2094: 210\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,823 - optimization.inference - INFO - Scan time: 29.1069\n", + "2024-12-19 13:16:10,824 - optimization.inference - INFO - Number of candidates by RT in frame 1973: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,829 - optimization.inference - INFO - Scan time: 31.267\n", + "2024-12-19 13:16:10,830 - optimization.inference - INFO - Number of candidates by RT in frame 2099: 198\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,836 - optimization.inference - INFO - Scan time: 29.1916\n", + "2024-12-19 13:16:10,837 - optimization.inference - INFO - Number of candidates by RT in frame 1978: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,844 - optimization.inference - INFO - Scan time: 31.3528\n", + "2024-12-19 13:16:10,845 - optimization.inference - INFO - Number of candidates by RT in frame 2104: 205\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,852 - optimization.inference - INFO - Scan time: 29.2774\n", + "2024-12-19 13:16:10,853 - optimization.inference - INFO - Number of candidates by RT in frame 1983: 213\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,860 - optimization.inference - INFO - Scan time: 31.4388\n", + "2024-12-19 13:16:10,861 - optimization.inference - INFO - Number of candidates by RT in frame 2109: 196\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,870 - optimization.inference - INFO - Scan time: 29.3623\n", + "2024-12-19 13:16:10,871 - optimization.inference - INFO - Number of candidates by RT in frame 1988: 206\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,878 - optimization.inference - INFO - Scan time: 31.5246\n", + "2024-12-19 13:16:10,879 - optimization.inference - INFO - Number of candidates by RT in frame 2114: 194\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,885 - optimization.inference - INFO - Scan time: 29.4487\n", + "2024-12-19 13:16:10,886 - optimization.inference - INFO - Number of candidates by RT in frame 1993: 201\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,893 - optimization.inference - INFO - Scan time: 31.6104\n", + "2024-12-19 13:16:10,894 - optimization.inference - INFO - Number of candidates by RT in frame 2119: 167\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,903 - optimization.inference - INFO - Scan time: 29.5347\n", + "2024-12-19 13:16:10,904 - optimization.inference - INFO - Number of candidates by RT in frame 1998: 211\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,905 - optimization.inference - INFO - Scan time: 31.6959\n", + "2024-12-19 13:16:10,906 - optimization.inference - INFO - Number of candidates by RT in frame 2124: 149\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,918 - optimization.inference - INFO - Scan time: 29.6199\n", + "2024-12-19 13:16:10,918 - optimization.inference - INFO - Scan time: 31.7815\n", + "2024-12-19 13:16:10,919 - optimization.inference - INFO - Number of candidates by RT in frame 2003: 206\n", + "2024-12-19 13:16:10,919 - optimization.inference - INFO - Number of candidates by RT in frame 2129: 143\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,932 - optimization.inference - INFO - Scan time: 31.8674\n", + "2024-12-19 13:16:10,933 - optimization.inference - INFO - Number of candidates by RT in frame 2134: 111\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,935 - optimization.inference - INFO - Scan time: 29.7062\n", + "2024-12-19 13:16:10,936 - optimization.inference - INFO - Number of candidates by RT in frame 2008: 190\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,944 - optimization.inference - INFO - Scan time: 31.9532\n", + "2024-12-19 13:16:10,945 - optimization.inference - INFO - Number of candidates by RT in frame 2139: 69\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,950 - optimization.inference - INFO - Scan time: 29.7916\n", + "2024-12-19 13:16:10,952 - optimization.inference - INFO - Number of candidates by RT in frame 2013: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,957 - optimization.inference - INFO - Scan time: 32.0398\n", + "2024-12-19 13:16:10,958 - optimization.inference - INFO - Number of candidates by RT in frame 2144: 37\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,968 - optimization.inference - INFO - Scan time: 29.8775\n", + "2024-12-19 13:16:10,969 - optimization.inference - INFO - Number of candidates by RT in frame 2018: 200\n", + "2024-12-19 13:16:10,970 - optimization.inference - INFO - Scan time: 32.1245\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,970 - optimization.inference - INFO - Number of candidates by RT in frame 2149: 20\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,982 - optimization.inference - INFO - Scan time: 32.1722\n", + "2024-12-19 13:16:10,982 - optimization.inference - INFO - Scan time: 29.9635\n", + "2024-12-19 13:16:10,982 - optimization.inference - INFO - Number of candidates by RT in frame 2154: 17\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,983 - optimization.inference - INFO - Number of candidates by RT in frame 2023: 199\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:10,994 - optimization.inference - INFO - Scan time: 32.1959\n", + "2024-12-19 13:16:10,995 - optimization.inference - INFO - Number of candidates by RT in frame 2159: 16\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,001 - optimization.inference - INFO - Scan time: 30.0496\n", + "2024-12-19 13:16:11,002 - optimization.inference - INFO - Number of candidates by RT in frame 2028: 200\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,005 - optimization.inference - INFO - Scan time: 32.2118\n", + "2024-12-19 13:16:11,005 - optimization.inference - INFO - Number of candidates by RT in frame 2164: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,016 - optimization.inference - INFO - Scan time: 32.233\n", + "2024-12-19 13:16:11,017 - optimization.inference - INFO - Number of candidates by RT in frame 2169: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,021 - optimization.inference - INFO - Scan time: 30.1356\n", + "2024-12-19 13:16:11,022 - optimization.inference - INFO - Number of candidates by RT in frame 2033: 179\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,026 - optimization.inference - INFO - Scan time: 32.2572\n", + "2024-12-19 13:16:11,026 - optimization.inference - INFO - Number of candidates by RT in frame 2174: 12\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,034 - optimization.inference - INFO - Scan time: 30.2213\n", + "2024-12-19 13:16:11,035 - optimization.inference - INFO - Number of candidates by RT in frame 2038: 167\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,038 - optimization.inference - INFO - Scan time: 32.2828\n", + "2024-12-19 13:16:11,038 - optimization.inference - INFO - Number of candidates by RT in frame 2179: 12\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,047 - optimization.inference - INFO - Scan time: 30.3071\n", + "2024-12-19 13:16:11,048 - optimization.inference - INFO - Number of candidates by RT in frame 2043: 180\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,049 - optimization.inference - INFO - Scan time: 32.295\n", + "2024-12-19 13:16:11,050 - optimization.inference - INFO - Number of candidates by RT in frame 2184: 11\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,060 - optimization.inference - INFO - Scan time: 32.3086\n", + "2024-12-19 13:16:11,061 - optimization.inference - INFO - Number of candidates by RT in frame 2189: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,062 - optimization.inference - INFO - Scan time: 30.3933\n", + "2024-12-19 13:16:11,063 - optimization.inference - INFO - Number of candidates by RT in frame 2048: 191\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,072 - optimization.inference - INFO - Scan time: 32.3257\n", + "2024-12-19 13:16:11,073 - optimization.inference - INFO - Number of candidates by RT in frame 2194: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,079 - optimization.inference - INFO - Scan time: 30.4795\n", + "2024-12-19 13:16:11,080 - optimization.inference - INFO - Number of candidates by RT in frame 2053: 213\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,083 - optimization.inference - INFO - Scan time: 32.3413\n", + "2024-12-19 13:16:11,084 - optimization.inference - INFO - Number of candidates by RT in frame 2199: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,093 - optimization.inference - INFO - Scan time: 32.3604\n", + "2024-12-19 13:16:11,094 - optimization.inference - INFO - Number of candidates by RT in frame 2204: 10\n", + "2024-12-19 13:16:11,094 - optimization.inference - INFO - Scan time: 30.5654\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,095 - optimization.inference - INFO - Number of candidates by RT in frame 2058: 224\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,104 - optimization.inference - INFO - Scan time: 32.3831\n", + "2024-12-19 13:16:11,105 - optimization.inference - INFO - Number of candidates by RT in frame 2209: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,112 - optimization.inference - INFO - Scan time: 30.651\n", + "2024-12-19 13:16:11,113 - optimization.inference - INFO - Number of candidates by RT in frame 2063: 220\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,114 - optimization.inference - INFO - Scan time: 32.4015\n", + "2024-12-19 13:16:11,115 - optimization.inference - INFO - Number of candidates by RT in frame 2214: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,124 - optimization.inference - INFO - Scan time: 32.4191\n", + "2024-12-19 13:16:11,125 - optimization.inference - INFO - Number of candidates by RT in frame 2219: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,129 - optimization.inference - INFO - Scan time: 30.7358\n", + "2024-12-19 13:16:11,130 - optimization.inference - INFO - Number of candidates by RT in frame 2068: 209\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,135 - optimization.inference - INFO - Scan time: 32.4336\n", + "2024-12-19 13:16:11,135 - optimization.inference - INFO - Number of candidates by RT in frame 2224: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,145 - optimization.inference - INFO - Scan time: 32.4469\n", + "2024-12-19 13:16:11,145 - optimization.inference - INFO - Number of candidates by RT in frame 2229: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,147 - optimization.inference - INFO - Scan time: 30.8213\n", + "2024-12-19 13:16:11,148 - optimization.inference - INFO - Number of candidates by RT in frame 2073: 196\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,153 - optimization.inference - INFO - Scan time: 32.4604\n", + "2024-12-19 13:16:11,153 - optimization.inference - INFO - Number of candidates by RT in frame 2234: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,161 - optimization.inference - INFO - Scan time: 32.4719\n", + "2024-12-19 13:16:11,161 - optimization.inference - INFO - Number of candidates by RT in frame 2239: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,165 - optimization.inference - INFO - Scan time: 30.9075\n", + "2024-12-19 13:16:11,166 - optimization.inference - INFO - Number of candidates by RT in frame 2078: 192\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,171 - optimization.inference - INFO - Scan time: 32.486\n", + "2024-12-19 13:16:11,172 - optimization.inference - INFO - Number of candidates by RT in frame 2244: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,176 - optimization.inference - INFO - Scan time: 30.9927\n", + "2024-12-19 13:16:11,177 - optimization.inference - INFO - Number of candidates by RT in frame 2083: 195\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,181 - optimization.inference - INFO - Scan time: 32.4989\n", + "2024-12-19 13:16:11,182 - optimization.inference - INFO - Number of candidates by RT in frame 2249: 4\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,191 - optimization.inference - INFO - Scan time: 32.5147\n", + "2024-12-19 13:16:11,192 - optimization.inference - INFO - Number of candidates by RT in frame 2254: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,194 - optimization.inference - INFO - Scan time: 31.0786\n", + "2024-12-19 13:16:11,195 - optimization.inference - INFO - Number of candidates by RT in frame 2088: 208\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,199 - optimization.inference - INFO - Scan time: 32.5315\n", + "2024-12-19 13:16:11,200 - optimization.inference - INFO - Number of candidates by RT in frame 2259: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,208 - optimization.inference - INFO - Scan time: 32.5484\n", + "2024-12-19 13:16:11,208 - optimization.inference - INFO - Number of candidates by RT in frame 2264: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,211 - optimization.inference - INFO - Scan time: 31.1643\n", + "2024-12-19 13:16:11,212 - optimization.inference - INFO - Number of candidates by RT in frame 2093: 211\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,216 - optimization.inference - INFO - Scan time: 32.5666\n", + "2024-12-19 13:16:11,217 - optimization.inference - INFO - Number of candidates by RT in frame 2269: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,225 - optimization.inference - INFO - Scan time: 32.5822\n", + "2024-12-19 13:16:11,226 - optimization.inference - INFO - Number of candidates by RT in frame 2274: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,229 - optimization.inference - INFO - Scan time: 31.25\n", + "2024-12-19 13:16:11,230 - optimization.inference - INFO - Number of candidates by RT in frame 2098: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,235 - optimization.inference - INFO - Scan time: 32.595\n", + "2024-12-19 13:16:11,235 - optimization.inference - INFO - Number of candidates by RT in frame 2279: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,242 - optimization.inference - INFO - Scan time: 32.6072\n", + "2024-12-19 13:16:11,243 - optimization.inference - INFO - Number of candidates by RT in frame 2284: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,244 - optimization.inference - INFO - Scan time: 31.3358\n", + "2024-12-19 13:16:11,245 - optimization.inference - INFO - Number of candidates by RT in frame 2103: 202\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,250 - optimization.inference - INFO - Scan time: 32.6236\n", + "2024-12-19 13:16:11,251 - optimization.inference - INFO - Number of candidates by RT in frame 2289: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,258 - optimization.inference - INFO - Scan time: 32.6371\n", + "2024-12-19 13:16:11,259 - optimization.inference - INFO - Number of candidates by RT in frame 2294: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,262 - optimization.inference - INFO - Scan time: 31.4218\n", + "2024-12-19 13:16:11,263 - optimization.inference - INFO - Number of candidates by RT in frame 2108: 197\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,266 - optimization.inference - INFO - Scan time: 32.6539\n", + "2024-12-19 13:16:11,267 - optimization.inference - INFO - Number of candidates by RT in frame 2299: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,274 - optimization.inference - INFO - Scan time: 32.6686\n", + "2024-12-19 13:16:11,274 - optimization.inference - INFO - Number of candidates by RT in frame 2304: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,281 - optimization.inference - INFO - Scan time: 32.6851\n", + "2024-12-19 13:16:11,281 - optimization.inference - INFO - Scan time: 31.5076\n", + "2024-12-19 13:16:11,282 - optimization.inference - INFO - Number of candidates by RT in frame 2309: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,282 - optimization.inference - INFO - Number of candidates by RT in frame 2113: 194\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,288 - optimization.inference - INFO - Scan time: 32.7\n", + "2024-12-19 13:16:11,289 - optimization.inference - INFO - Number of candidates by RT in frame 2314: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,296 - optimization.inference - INFO - Scan time: 32.7135\n", + "2024-12-19 13:16:11,296 - optimization.inference - INFO - Number of candidates by RT in frame 2319: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,298 - optimization.inference - INFO - Scan time: 31.5932\n", + "2024-12-19 13:16:11,299 - optimization.inference - INFO - Number of candidates by RT in frame 2118: 172\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,303 - optimization.inference - INFO - Scan time: 32.7296\n", + "2024-12-19 13:16:11,304 - optimization.inference - INFO - Number of candidates by RT in frame 2324: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,310 - optimization.inference - INFO - Scan time: 32.7431\n", + "2024-12-19 13:16:11,311 - optimization.inference - INFO - Number of candidates by RT in frame 2329: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,316 - optimization.inference - INFO - Scan time: 31.6787\n", + "2024-12-19 13:16:11,316 - optimization.inference - INFO - Number of candidates by RT in frame 2123: 153\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,318 - optimization.inference - INFO - Scan time: 32.7587\n", + "2024-12-19 13:16:11,319 - optimization.inference - INFO - Number of candidates by RT in frame 2334: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,325 - optimization.inference - INFO - Scan time: 32.7792\n", + "2024-12-19 13:16:11,326 - optimization.inference - INFO - Number of candidates by RT in frame 2339: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,328 - optimization.inference - INFO - Scan time: 31.7644\n", + "2024-12-19 13:16:11,329 - optimization.inference - INFO - Number of candidates by RT in frame 2128: 147\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,332 - optimization.inference - INFO - Scan time: 32.794\n", + "2024-12-19 13:16:11,333 - optimization.inference - INFO - Number of candidates by RT in frame 2344: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,338 - optimization.inference - INFO - Scan time: 32.8084\n", + "2024-12-19 13:16:11,339 - optimization.inference - INFO - Number of candidates by RT in frame 2349: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,341 - optimization.inference - INFO - Scan time: 31.8502\n", + "2024-12-19 13:16:11,342 - optimization.inference - INFO - Number of candidates by RT in frame 2133: 117\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,345 - optimization.inference - INFO - Scan time: 32.8238\n", + "2024-12-19 13:16:11,346 - optimization.inference - INFO - Number of candidates by RT in frame 2354: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,352 - optimization.inference - INFO - Scan time: 31.9361\n", + "2024-12-19 13:16:11,353 - optimization.inference - INFO - Scan time: 32.8392\n", + "2024-12-19 13:16:11,353 - optimization.inference - INFO - Number of candidates by RT in frame 2359: 2\n", + "2024-12-19 13:16:11,353 - optimization.inference - INFO - Number of candidates by RT in frame 2138: 83\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,360 - optimization.inference - INFO - Scan time: 32.8542\n", + "2024-12-19 13:16:11,361 - optimization.inference - INFO - Number of candidates by RT in frame 2364: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,367 - optimization.inference - INFO - Scan time: 32.867\n", + "2024-12-19 13:16:11,368 - optimization.inference - INFO - Number of candidates by RT in frame 2369: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,368 - optimization.inference - INFO - Scan time: 32.0223\n", + "2024-12-19 13:16:11,369 - optimization.inference - INFO - Number of candidates by RT in frame 2143: 41\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,374 - optimization.inference - INFO - Scan time: 32.8791\n", + "2024-12-19 13:16:11,375 - optimization.inference - INFO - Number of candidates by RT in frame 2374: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,381 - optimization.inference - INFO - Scan time: 32.894\n", + "2024-12-19 13:16:11,382 - optimization.inference - INFO - Number of candidates by RT in frame 2379: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,383 - optimization.inference - INFO - Scan time: 32.1076\n", + "2024-12-19 13:16:11,384 - optimization.inference - INFO - Number of candidates by RT in frame 2148: 20\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,388 - optimization.inference - INFO - Scan time: 32.9087\n", + "2024-12-19 13:16:11,389 - optimization.inference - INFO - Number of candidates by RT in frame 2384: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,395 - optimization.inference - INFO - Scan time: 32.1657\n", + "2024-12-19 13:16:11,396 - optimization.inference - INFO - Scan time: 32.9209\n", + "2024-12-19 13:16:11,396 - optimization.inference - INFO - Number of candidates by RT in frame 2153: 18\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,396 - optimization.inference - INFO - Number of candidates by RT in frame 2389: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,403 - optimization.inference - INFO - Scan time: 32.9353\n", + "2024-12-19 13:16:11,403 - optimization.inference - INFO - Number of candidates by RT in frame 2394: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,407 - optimization.inference - INFO - Scan time: 32.1936\n", + "2024-12-19 13:16:11,408 - optimization.inference - INFO - Number of candidates by RT in frame 2158: 16\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,409 - optimization.inference - INFO - Scan time: 32.9474\n", + "2024-12-19 13:16:11,410 - optimization.inference - INFO - Number of candidates by RT in frame 2399: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,416 - optimization.inference - INFO - Scan time: 32.959\n", + "2024-12-19 13:16:11,417 - optimization.inference - INFO - Number of candidates by RT in frame 2404: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,418 - optimization.inference - INFO - Scan time: 32.2094\n", + "2024-12-19 13:16:11,419 - optimization.inference - INFO - Number of candidates by RT in frame 2163: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,423 - optimization.inference - INFO - Scan time: 32.9705\n", + "2024-12-19 13:16:11,423 - optimization.inference - INFO - Number of candidates by RT in frame 2409: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,429 - optimization.inference - INFO - Scan time: 32.9888\n", + "2024-12-19 13:16:11,429 - optimization.inference - INFO - Scan time: 32.2307\n", + "2024-12-19 13:16:11,430 - optimization.inference - INFO - Number of candidates by RT in frame 2414: 1\n", + "2024-12-19 13:16:11,430 - optimization.inference - INFO - Number of candidates by RT in frame 2168: 14\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,436 - optimization.inference - INFO - Scan time: 33.0011\n", + "2024-12-19 13:16:11,436 - optimization.inference - INFO - Number of candidates by RT in frame 2419: 1\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,439 - optimization.inference - INFO - Scan time: 32.2527\n", + "2024-12-19 13:16:11,440 - optimization.inference - INFO - Number of candidates by RT in frame 2173: 12\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,442 - optimization.inference - INFO - Shape of COO matrix: (2421, 18939)\n", + "2024-12-19 13:16:11,451 - optimization.inference - INFO - Scan time: 32.2784\n", + "2024-12-19 13:16:11,452 - optimization.inference - INFO - Number of candidates by RT in frame 2178: 12\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,463 - optimization.inference - INFO - Scan time: 32.2927\n", + "2024-12-19 13:16:11,464 - optimization.inference - INFO - Number of candidates by RT in frame 2183: 11\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,475 - optimization.inference - INFO - Scan time: 32.3063\n", + "2024-12-19 13:16:11,475 - optimization.inference - INFO - Number of candidates by RT in frame 2188: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,486 - optimization.inference - INFO - Scan time: 32.322\n", + "2024-12-19 13:16:11,487 - optimization.inference - INFO - Number of candidates by RT in frame 2193: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,497 - optimization.inference - INFO - Scan time: 32.339\n", + "2024-12-19 13:16:11,498 - optimization.inference - INFO - Number of candidates by RT in frame 2198: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,507 - optimization.inference - INFO - Scan time: 32.3568\n", + "2024-12-19 13:16:11,508 - optimization.inference - INFO - Number of candidates by RT in frame 2203: 10\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,517 - optimization.inference - INFO - Scan time: 32.3795\n", + "2024-12-19 13:16:11,518 - optimization.inference - INFO - Number of candidates by RT in frame 2208: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,524 - optimization.inference - INFO - Size of COO matrix in batch 4: 1.614264 Mb\n", + "2024-12-19 13:16:11,529 - optimization.inference - INFO - Scan time: 32.3992\n", + "2024-12-19 13:16:11,530 - optimization.inference - INFO - Number of candidates by RT in frame 2213: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,540 - optimization.inference - INFO - Scan time: 32.4162\n", + "2024-12-19 13:16:11,540 - optimization.inference - INFO - Number of candidates by RT in frame 2218: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,551 - optimization.inference - INFO - Scan time: 32.4313\n", + "2024-12-19 13:16:11,551 - optimization.inference - INFO - Number of candidates by RT in frame 2223: 9\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,561 - optimization.inference - INFO - Scan time: 32.4446\n", + "2024-12-19 13:16:11,562 - optimization.inference - INFO - Number of candidates by RT in frame 2228: 7\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,570 - optimization.inference - INFO - Scan time: 32.4581\n", + "2024-12-19 13:16:11,571 - optimization.inference - INFO - Number of candidates by RT in frame 2233: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,579 - optimization.inference - INFO - Scan time: 32.4696\n", + "2024-12-19 13:16:11,579 - optimization.inference - INFO - Number of candidates by RT in frame 2238: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,589 - optimization.inference - INFO - Scan time: 32.4831\n", + "2024-12-19 13:16:11,590 - optimization.inference - INFO - Number of candidates by RT in frame 2243: 6\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,599 - optimization.inference - INFO - Scan time: 32.4966\n", + "2024-12-19 13:16:11,600 - optimization.inference - INFO - Number of candidates by RT in frame 2248: 4\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,609 - optimization.inference - INFO - Scan time: 32.511\n", + "2024-12-19 13:16:11,610 - optimization.inference - INFO - Number of candidates by RT in frame 2253: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,618 - optimization.inference - INFO - Scan time: 32.5286\n", + "2024-12-19 13:16:11,619 - optimization.inference - INFO - Number of candidates by RT in frame 2258: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,627 - optimization.inference - INFO - Scan time: 32.5461\n", + "2024-12-19 13:16:11,628 - optimization.inference - INFO - Number of candidates by RT in frame 2263: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,636 - optimization.inference - INFO - Scan time: 32.5615\n", + "2024-12-19 13:16:11,636 - optimization.inference - INFO - Number of candidates by RT in frame 2268: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,645 - optimization.inference - INFO - Scan time: 32.5785\n", + "2024-12-19 13:16:11,646 - optimization.inference - INFO - Number of candidates by RT in frame 2273: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,655 - optimization.inference - INFO - Scan time: 32.5914\n", + "2024-12-19 13:16:11,655 - optimization.inference - INFO - Number of candidates by RT in frame 2278: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,664 - optimization.inference - INFO - Scan time: 32.6043\n", + "2024-12-19 13:16:11,665 - optimization.inference - INFO - Number of candidates by RT in frame 2283: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,672 - optimization.inference - INFO - Scan time: 32.6185\n", + "2024-12-19 13:16:11,673 - optimization.inference - INFO - Number of candidates by RT in frame 2288: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,680 - optimization.inference - INFO - Scan time: 32.6328\n", + "2024-12-19 13:16:11,681 - optimization.inference - INFO - Number of candidates by RT in frame 2293: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,688 - optimization.inference - INFO - Scan time: 32.6503\n", + "2024-12-19 13:16:11,689 - optimization.inference - INFO - Number of candidates by RT in frame 2298: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,697 - optimization.inference - INFO - Scan time: 32.6657\n", + "2024-12-19 13:16:11,698 - optimization.inference - INFO - Number of candidates by RT in frame 2303: 3\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,705 - optimization.inference - INFO - Scan time: 32.6822\n", + "2024-12-19 13:16:11,706 - optimization.inference - INFO - Number of candidates by RT in frame 2308: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,713 - optimization.inference - INFO - Scan time: 32.6977\n", + "2024-12-19 13:16:11,714 - optimization.inference - INFO - Number of candidates by RT in frame 2313: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,720 - optimization.inference - INFO - Scan time: 32.7098\n", + "2024-12-19 13:16:11,721 - optimization.inference - INFO - Number of candidates by RT in frame 2318: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,729 - optimization.inference - INFO - Scan time: 32.7252\n", + "2024-12-19 13:16:11,730 - optimization.inference - INFO - Number of candidates by RT in frame 2323: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,737 - optimization.inference - INFO - Scan time: 32.7402\n", + "2024-12-19 13:16:11,738 - optimization.inference - INFO - Number of candidates by RT in frame 2328: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,744 - optimization.inference - INFO - Scan time: 32.7555\n", + "2024-12-19 13:16:11,745 - optimization.inference - INFO - Number of candidates by RT in frame 2333: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,752 - optimization.inference - INFO - Scan time: 32.7769\n", + "2024-12-19 13:16:11,753 - optimization.inference - INFO - Number of candidates by RT in frame 2338: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,759 - optimization.inference - INFO - Scan time: 32.7904\n", + "2024-12-19 13:16:11,760 - optimization.inference - INFO - Number of candidates by RT in frame 2343: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,766 - optimization.inference - INFO - Scan time: 32.8033\n", + "2024-12-19 13:16:11,767 - optimization.inference - INFO - Number of candidates by RT in frame 2348: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,774 - optimization.inference - INFO - Scan time: 32.8202\n", + "2024-12-19 13:16:11,775 - optimization.inference - INFO - Number of candidates by RT in frame 2353: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,782 - optimization.inference - INFO - Scan time: 32.8369\n", + "2024-12-19 13:16:11,782 - optimization.inference - INFO - Number of candidates by RT in frame 2358: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,789 - optimization.inference - INFO - Scan time: 32.8506\n", + "2024-12-19 13:16:11,790 - optimization.inference - INFO - Number of candidates by RT in frame 2363: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,797 - optimization.inference - INFO - Scan time: 32.864\n", + "2024-12-19 13:16:11,797 - optimization.inference - INFO - Number of candidates by RT in frame 2368: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,804 - optimization.inference - INFO - Scan time: 32.8768\n", + "2024-12-19 13:16:11,805 - optimization.inference - INFO - Number of candidates by RT in frame 2373: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,811 - optimization.inference - INFO - Scan time: 32.8897\n", + "2024-12-19 13:16:11,812 - optimization.inference - INFO - Number of candidates by RT in frame 2378: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,818 - optimization.inference - INFO - Scan time: 32.9064\n", + "2024-12-19 13:16:11,819 - optimization.inference - INFO - Number of candidates by RT in frame 2383: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,825 - optimization.inference - INFO - Scan time: 32.9185\n", + "2024-12-19 13:16:11,826 - optimization.inference - INFO - Number of candidates by RT in frame 2388: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,833 - optimization.inference - INFO - Scan time: 32.9324\n", + "2024-12-19 13:16:11,834 - optimization.inference - INFO - Number of candidates by RT in frame 2393: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,840 - optimization.inference - INFO - Scan time: 32.9445\n", + "2024-12-19 13:16:11,841 - optimization.inference - INFO - Number of candidates by RT in frame 2398: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,847 - optimization.inference - INFO - Scan time: 32.9567\n", + "2024-12-19 13:16:11,848 - optimization.inference - INFO - Number of candidates by RT in frame 2403: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,854 - optimization.inference - INFO - Scan time: 32.9682\n", + "2024-12-19 13:16:11,854 - optimization.inference - INFO - Number of candidates by RT in frame 2408: 2\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,860 - optimization.inference - INFO - Scan time: 32.9859\n", + "2024-12-19 13:16:11,861 - optimization.inference - INFO - Number of candidates by RT in frame 2413: 1\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,866 - optimization.inference - INFO - Scan time: 32.998\n", + "2024-12-19 13:16:11,867 - optimization.inference - INFO - Number of candidates by RT in frame 2418: 1\n", + "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:781: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " candidate_precursor_by_rt.sort_values(\n", + "2024-12-19 13:16:11,873 - optimization.inference - INFO - Shape of COO matrix: (2421, 18939)\n", + "2024-12-19 13:16:11,950 - optimization.inference - INFO - Size of COO matrix in batch 3: 1.614864 Mb\n", + "2024-12-19 13:16:12> Process scans - Script execution time: 0m 31s\n", + "2024-12-19 13:16:12> =================Post Processing==================\n", + "2024-12-19 13:16:12> NNZ size of batch 0 act_3d 67438\n", + "2024-12-19 13:16:12> NNZ size of batch 1 act_3d 67464\n", + "2024-12-19 13:16:13> NNZ size of act_3d_all 134902\n", + "2024-12-19 13:16:13> NNZ size of batch 2 act_3d 67543\n", + "2024-12-19 13:16:13> NNZ size of act_3d_all 202445\n", + "2024-12-19 13:16:13> NNZ size of batch 3 act_3d 67286\n", + "2024-12-19 13:16:13> NNZ size of act_3d_all 269731\n", + "2024-12-19 13:16:13> NNZ size of batch 4 act_3d 67261\n", + "2024-12-19 13:16:13> NNZ size of act_3d_all 336992\n", + "2024-12-19 13:16:13> pept_act_sum_all sum (18939,)\n", + "2024-12-19 13:16:13> ==================Result Analaysis==================\n", + "2024-12-19 13:16:13> Drop na values in pept_act_sum, Pept activation sum entries: 18939\n", + "2024-12-19 13:16:13> Filtering the data by the sum of intensity threshold 2, number of entries before filtering 18939\n", + "2024-12-19 13:16:13> Number of entries after filtering 18938\n", + "2024-12-19 13:16:13> No decoy entries in the data, using FDR threshold of dictionary 0.2\n", + "2024-12-19 13:16:13> Number of entries after merging 18938 and columns Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", + " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", + " 'Oxidation (M)', 'Missed cleavages', 'Proteins', 'Leading proteins',\n", + " 'Leading razor protein', 'Gene names', 'Protein names', 'Type',\n", + " 'Raw file', 'Experiment', 'MS/MS m/z', 'Charge', 'm/z', 'Mass',\n", + " 'Resolution', 'Uncalibrated - Calibrated m/z [ppm]',\n", + " 'Uncalibrated - Calibrated m/z [Da]', 'Mass error [ppm]',\n", + " 'Mass error [Da]', 'Uncalibrated mass error [ppm]',\n", + " 'Uncalibrated mass error [Da]', 'Max intensity m/z 0', 'Retention time',\n", + " 'Retention length', 'Calibrated retention time',\n", + " 'Calibrated retention time start', 'Calibrated retention time finish',\n", + " 'Retention time calibration', 'Match time difference',\n", + " 'Match m/z difference', 'Match q-value', 'Match score',\n", + " 'Number of data points', 'Number of scans', 'Number of isotopic peaks',\n", + " 'PIF', 'Fraction of total spectrum', 'Base peak fraction', 'PEP',\n", + " 'MS/MS count', 'MS/MS scan number', 'Score', 'Delta score',\n", + " 'Combinatorics', 'Intensity', 'Reverse', 'Potential contaminant', 'id',\n", + " 'Protein group IDs', 'Peptide ID', 'Mod. peptide ID', 'MS/MS IDs',\n", + " 'Best MS/MS', 'AIF MS/MS IDs', 'Oxidation (M) site IDs', 'source',\n", + " 'Time_minute_center_exp', 'MS1_frame_idx_center_exp',\n", + " 'Time_minute_left_exp', 'MS1_frame_idx_left_exp',\n", + " 'Time_minute_right_exp', 'MS1_frame_idx_right_exp', 'RT_search_left',\n", + " 'RT_search_right', 'RT_search_center', 'Time_minute_center_ref',\n", + " 'MS1_frame_idx_center_ref', 'Time_minute_left_ref',\n", + " 'MS1_frame_idx_left_ref', 'Time_minute_right_ref',\n", + " 'MS1_frame_idx_right_ref', 'IsoMZ', 'IsoAbundance', 'mz_rank', 'mz_bin',\n", + " 'mz_length', 'pept_batch_idx', 'Decoy', 'pept_act_sum',\n", + " 'log_sum_intensity'],\n", + " dtype='object')\n", + "2024-12-19 13:16:13> Data: Intensity_log, pept_act_sum_log, slope = 0.867, intercept = 0.885, Pearson's R = 0.833, Spearman's R = 0.8\n", + "2024-12-19 13:16:20> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/results/evaluation/CorrQuantification_pept_act_sum_log_fdr_0.2_log_int_2.png\n", + "2024-12-19 13:16:22> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/results/evaluation/CorrQuantification_pept_act_sum_log_fdr_0.2_log_int_2.svg\n", + "2024-12-19 13:16:22> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/results/evaluation/VennDiag_precursor_fdr_0.2_log_int_2.png\n", + "2024-12-19 13:16:22> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/results/evaluation/VennDiag_precursor_fdr_0.2_log_int_2.svg\n", + "2024-12-19 13:16:22> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/results/evaluation/VennDiag_peptide_fdr_0.2_log_int_2.png\n", + "2024-12-19 13:16:22> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/results/evaluation/VennDiag_peptide_fdr_0.2_log_int_2.svg\n", + "2024-12-19 13:16:22> Number of proteins in Maxquant 1873\n", + "2024-12-19 13:16:22> Number of proteins in SWAPS 1873\n", + "2024-12-19 13:16:22> Number of proteins in both SWAPS and Maxquant 1873\n", + "2024-12-19 13:16:22> Number of proteins only in SWAPS 0\n", + "2024-12-19 13:16:23> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/results/evaluation/VennDiag_protein_fdr_0.2_log_int_2.png\n", + "2024-12-19 13:16:23> Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_ecoli_20241219_131518_762964/results/evaluation/VennDiag_protein_fdr_0.2_log_int_2.svg\n", + "\u001b[0m\u001b[0m\u001b[0m\u001b[0m\u001b[0m2024-12-19 13:16:24> WARNING: Temp mmap arrays were written to /tmp/temp_mmap_8qil4_2c. Cleanup of this folder is OS dependant, and might need to be triggered manually! Current space: 34,153,234,432\n", + "\u001b[0m" + ] + } + ], + "source": [ + "%autoreload 2\n", + "!python /cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/sbs_runner_ims.py --config_path=/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/utils/exp_configs/config_ayla_test.yaml" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Check peptide activation" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(2987, 1227)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import sparse\n", + "\n", + "pept_act = sparse.load_npz(\n", + " \"/cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_20241219_131745_378483/results/activation/im_rt_pept_act_coo_peptbatch0.npz\"\n", + ")\n", + "# convert to dense\n", + "pept_act_mat = pept_act.todense()\n", + "pept_act_mat.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "pept_act_sum_by_scan = pept_act_mat.sum(axis=1)\n", + "pept_act_sum_by_pept = pept_act_mat.sum(axis=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "pept_act_mat has shape (n_ms1scans + 1, n_candidate + 1). The last row is a place holder so it is alway zero. To map the rows back to actual retention time value, you can use the mzML file. Row idx is the same as mzML scan index.\n", + "\n", + "The first column is a place holder candidate since the candidates are identified by 'mz_rank', there is no rank 0 so column 0 always have zero intensity. You can map back the peptide using the dictionary from the result_path." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", + " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", + " 'Oxidation (M)', 'Missed cleavages', 'Proteins', 'Leading proteins',\n", + " 'Leading razor protein', 'Type', 'Raw file', 'Experiment', 'MS/MS m/z',\n", + " 'Charge', 'm/z', 'Mass', 'Resolution',\n", + " 'Uncalibrated - Calibrated m/z [ppm]',\n", + " 'Uncalibrated - Calibrated m/z [Da]', 'Mass Error [ppm]',\n", + " 'Mass Error [Da]', 'Uncalibrated Mass Error [ppm]',\n", + " 'Uncalibrated Mass Error [Da]', 'Max intensity m/z 0', 'Retention time',\n", + " 'Retention length', 'Calibrated retention time',\n", + " 'Calibrated retention time start', 'Calibrated retention time finish',\n", + " 'Retention time calibration', 'Match time difference',\n", + " 'Match m/z difference', 'Match q-value', 'Match score',\n", + " 'Number of data points', 'Number of scans', 'Number of isotopic peaks',\n", + " 'PIF', 'Fraction of total spectrum', 'Base peak fraction', 'PEP',\n", + " 'MS/MS Count', 'MS/MS Scan Number', 'Score', 'Delta score',\n", + " 'Combinatorics', 'Intensity', 'Reverse', 'Potential contaminant', 'id',\n", + " 'Protein group IDs', 'Peptide ID', 'Mod. peptide ID', 'MS/MS IDs',\n", + " 'Best MS/MS', 'AIF MS/MS IDs', 'Oxidation (M) site IDs', 'source',\n", + " 'Time_minute_center_exp', 'MS1_frame_idx_center_exp',\n", + " 'Time_minute_left_exp', 'MS1_frame_idx_left_exp',\n", + " 'Time_minute_right_exp', 'MS1_frame_idx_right_exp', 'RT_search_left',\n", + " 'RT_search_right', 'RT_search_center', 'Time_minute_center_ref',\n", + " 'MS1_frame_idx_center_ref', 'Time_minute_left_ref',\n", + " 'MS1_frame_idx_left_ref', 'Time_minute_right_ref',\n", + " 'MS1_frame_idx_right_ref', 'IsoMZ', 'IsoAbundance', 'mz_rank', 'mz_bin',\n", + " 'mz_length', 'pept_batch_idx'],\n", + " dtype='object')" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Load dictionary\n", + "maxquant_ref = pd.read_pickle(\n", + " \"/cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla_20241219_131745_378483/maxquant_result_ref.pkl\"\n", + ")\n", + "maxquant_ref.columns\n", + "# mz_rank is the column that can be used for mapping candidate" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Add extra candidates" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " mz rt_start rt_end tolerance tolerance_unit comment\n", + "0 1013.491028 49.734975 50.115053 5 ppm 2\n", + "1 675.996444 49.734975 50.115053 5 ppm 3\n", + "2 507.249152 49.734975 50.115053 5 ppm 4\n", + "3 406.000777 49.734975 50.115053 5 ppm 5\n", + "4 930.464966 52.804498 53.536034 5 ppm 12\n" + ] + } + ], + "source": [ + "# Load dataframe from JSON file\n", + "df_from_json = pd.read_json(\n", + " \"/cmnfs/data/proteomics/origin/ayla_proteometools_subset/01709a_GB1-TUM_first_pool_100_01_01-DDA-1h-R1_mz.json\"\n", + ")\n", + "print(df_from_json.head())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "These extra precursor charge states need to be appended to the MaxQuant Evidence.txt.\n", + "\n", + "Maybe directly copy the identified precursors and modify the following column for different charge state:\n", + "- 'Charge'\n", + "- 'm/z'\n", + "- 'Retention time'\n", + "- 'Retention length'\n", + "- 'Calibrated retention time'\n", + "- 'Calibrated retention time start'\n", + "- 'Calibrated retention time finish'\n", + "- 'id' # simply extend this, in principle not used by SWAPS\n", + "- 'Intensity' # set to zero\n", + "\n", + "\n", + "and leave these columns empty:\n", + "'MS/MS m/z',\n", + "'Uncalibrated - Calibrated m/z [ppm]',\n", + "- 'Uncalibrated - Calibrated m/z [Da]'\n", + "- 'Mass Error [ppm]'\n", + "- 'Mass Error [Da]'\n", + "- 'Uncalibrated Mass Error [ppm]'\n", + "- 'Uncalibrated Mass Error [Da]'\n", + "- 'Max intensity m/z 0'\n", + "- 'Retention time calibration'\n", + "- 'Match time difference'\n", + "- 'Match m/z difference'\n", + "- 'Match q-value'\n", + "- 'Match score'\n", + "- 'Number of data points'\n", + "- 'Number of scans'\n", + "- 'Number of isotopic peaks'\n", + "- 'PIF'\n", + "- 'Fraction of total spectrum'\n", + "- 'Base peak fraction'\n", + "- 'PEP'\n", + "- 'MS/MS Count'\n", + "- 'MS/MS Scan Number'\n", + "- 'Score'\n", + "- 'Delta score'\n", + "- 'Combinatorics'\n", + "- 'MS/MS IDs'\n", + "- 'Best MS/MS'\n", + "- 'AIF MS/MS IDs'\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", + " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", + " 'Oxidation (M)', 'Missed cleavages', 'Proteins', 'Leading proteins',\n", + " 'Leading razor protein', 'Type', 'Raw file', 'Experiment', 'MS/MS m/z',\n", + " 'Charge', 'm/z', 'Mass', 'Resolution',\n", + " 'Uncalibrated - Calibrated m/z [ppm]',\n", + " 'Uncalibrated - Calibrated m/z [Da]', 'Mass Error [ppm]',\n", + " 'Mass Error [Da]', 'Uncalibrated Mass Error [ppm]',\n", + " 'Uncalibrated Mass Error [Da]', 'Max intensity m/z 0', 'Retention time',\n", + " 'Retention length', 'Calibrated retention time',\n", + " 'Calibrated retention time start', 'Calibrated retention time finish',\n", + " 'Retention time calibration', 'Match time difference',\n", + " 'Match m/z difference', 'Match q-value', 'Match score',\n", + " 'Number of data points', 'Number of scans', 'Number of isotopic peaks',\n", + " 'PIF', 'Fraction of total spectrum', 'Base peak fraction', 'PEP',\n", + " 'MS/MS Count', 'MS/MS Scan Number', 'Score', 'Delta score',\n", + " 'Combinatorics', 'Intensity', 'Reverse', 'Potential contaminant', 'id',\n", + " 'Protein group IDs', 'Peptide ID', 'Mod. peptide ID', 'MS/MS IDs',\n", + " 'Best MS/MS', 'AIF MS/MS IDs', 'Oxidation (M) site IDs'],\n", + " dtype='object')" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mq_evidence = pd.read_csv(\n", + " \"/cmnfs/data/proteomics/origin/ayla_proteometools_subset/TUM_first_pool_100_01_01_DDA-1h-R1-tryptic/evidence.txt\",\n", + " sep=\"\\t\",\n", + ")\n", + "mq_evidence.columns" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "sbs", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/exp_ana_00_ms2.ipynb b/notebooks/exp_ana_00_ms2.ipynb deleted file mode 100644 index aaf1c9c..0000000 --- a/notebooks/exp_ana_00_ms2.ipynb +++ /dev/null @@ -1,871 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from IPython.core.interactiveshell import InteractiveShell\n", - "InteractiveShell.ast_node_interactivity = \"all\"\n", - "import logging\n", - "logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')\n", - "%load_ext autoreload" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-29 11:18:39,762 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", - "2024-02-29 11:18:39,765 - numexpr.utils - INFO - NumExpr defaulting to 8 threads.\n", - "2024-02-29 11:18:42,582 - matplotlib - DEBUG - matplotlib data path: /cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data\n", - "2024-02-29 11:18:42,600 - matplotlib - DEBUG - CONFIGDIR=/cmnfs/home/z.xiao/.config/matplotlib\n", - "2024-02-29 11:18:42,605 - matplotlib - DEBUG - interactive is False\n", - "2024-02-29 11:18:42,606 - matplotlib - DEBUG - platform is linux\n", - "2024-02-29 11:18:42,783 - matplotlib - DEBUG - CACHEDIR=/cmnfs/home/z.xiao/.cache/matplotlib\n", - "2024-02-29 11:18:42,836 - matplotlib.font_manager - DEBUG - Using fontManager instance from /cmnfs/home/z.xiao/.cache/matplotlib/fontlist-v330.json\n" - ] - } - ], - "source": [ - "import pandas as pd\n", - "import os\n", - "import sys\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "module_path = os.path.abspath(os.path.join(\"..\"))\n", - "if module_path not in sys.path:\n", - " sys.path.append(module_path)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Load data" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_90934/42633509.py:2: DtypeWarning: Columns (50) have mixed types. Specify dtype option on import or set low_memory=False.\n", - " msms_df = pd.read_csv(os.path.join(txt_path, \"msms.txt\"), sep=\"\\t\")\n" - ] - } - ], - "source": [ - "txt_path = \"/cmnfs/proj/ORIGINS/data/ecoli/ss/DDA/MQ/combined/txt/\"\n", - "msms_df = pd.read_csv(os.path.join(txt_path, \"msms.txt\"), sep=\"\\t\")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Raw fileScan numberScan indexSequenceLengthMissed cleavagesModificationsModified sequenceOxidation (M) ProbabilitiesOxidation (M) Score Diffs...ReverseAll scoresAll sequencesAll modified sequencesidProtein group IDsPeptide IDMod. peptide IDEvidence IDOxidation (M) site IDs
0BBM_647_P241_02_07_ssDDA_MIA_00484617768AAAAEIAVK90Unmodified_AAAAEIAVK_NaNNaN...NaN69.8246066869863;35.2952538007438;28.174025403...AAAAEIAVK;NDAILVAK;AAIAAEVAK_AAAAEIAVK_;_NDAILVAK_;_AAIAAEVAK_0384000NaN
1BBM_647_P241_02_07_ssDDA_MIA_00584717770AAAAEIAVK90Unmodified_AAAAEIAVK_NaNNaN...NaN73.6646353084277;43.8078020897056;36.395170339887AAAAEIAVK;NDAILVAK;AAIAAEVAK_AAAAEIAVK_;_NDAILVAK_;_AAIAAEVAK_1384001NaN
2BBM_647_P241_02_07_ssDDA_MIA_00193748634AAADEWDER90Unmodified_AAADEWDER_NaNNaN...NaN145.648489875395;3.3921643866591AAADEWDER;DDEEYHVR_AAADEWDER_;_DDEEYHVR_21208112NaN
3BBM_647_P241_02_07_ssDDA_MIA_00293418594AAADEWDER90Unmodified_AAADEWDER_NaNNaN...NaN163.202594227336;4.35631285626958AAADEWDER;DDEEYHVR_AAADEWDER_;_DDEEYHVR_31208113NaN
4BBM_647_P241_02_07_ssDDA_MIA_00393318582AAADEWDER90Unmodified_AAADEWDER_NaNNaN...NaN151.495376157055;4.35631285626958AAADEWDER;DDEEYHVR_AAADEWDER_;_DDEEYHVR_41208114NaN
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5 rows × 60 columns

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" - ], - "text/plain": [ - " Raw file Scan number Scan index Sequence \\\n", - "0 BBM_647_P241_02_07_ssDDA_MIA_004 8461 7768 AAAAEIAVK \n", - "1 BBM_647_P241_02_07_ssDDA_MIA_005 8471 7770 AAAAEIAVK \n", - "2 BBM_647_P241_02_07_ssDDA_MIA_001 9374 8634 AAADEWDER \n", - "3 BBM_647_P241_02_07_ssDDA_MIA_002 9341 8594 AAADEWDER \n", - "4 BBM_647_P241_02_07_ssDDA_MIA_003 9331 8582 AAADEWDER \n", - "\n", - " Length Missed cleavages Modifications Modified sequence \\\n", - "0 9 0 Unmodified _AAAAEIAVK_ \n", - "1 9 0 Unmodified _AAAAEIAVK_ \n", - "2 9 0 Unmodified _AAADEWDER_ \n", - "3 9 0 Unmodified _AAADEWDER_ \n", - "4 9 0 Unmodified _AAADEWDER_ \n", - "\n", - " Oxidation (M) Probabilities Oxidation (M) Score Diffs ... Reverse \\\n", - "0 NaN NaN ... NaN \n", - "1 NaN NaN ... NaN \n", - "2 NaN NaN ... NaN \n", - "3 NaN NaN ... NaN \n", - "4 NaN NaN ... NaN \n", - "\n", - " All scores \\\n", - "0 69.8246066869863;35.2952538007438;28.174025403... \n", - "1 73.6646353084277;43.8078020897056;36.395170339887 \n", - "2 145.648489875395;3.3921643866591 \n", - "3 163.202594227336;4.35631285626958 \n", - "4 151.495376157055;4.35631285626958 \n", - "\n", - " All sequences All modified sequences id \\\n", - "0 AAAAEIAVK;NDAILVAK;AAIAAEVAK _AAAAEIAVK_;_NDAILVAK_;_AAIAAEVAK_ 0 \n", - "1 AAAAEIAVK;NDAILVAK;AAIAAEVAK _AAAAEIAVK_;_NDAILVAK_;_AAIAAEVAK_ 1 \n", - "2 AAADEWDER;DDEEYHVR _AAADEWDER_;_DDEEYHVR_ 2 \n", - "3 AAADEWDER;DDEEYHVR _AAADEWDER_;_DDEEYHVR_ 3 \n", - "4 AAADEWDER;DDEEYHVR _AAADEWDER_;_DDEEYHVR_ 4 \n", - "\n", - " Protein group IDs Peptide ID Mod. peptide ID Evidence ID \\\n", - "0 384 0 0 0 \n", - "1 384 0 0 1 \n", - "2 1208 1 1 2 \n", - "3 1208 1 1 3 \n", - "4 1208 1 1 4 \n", - "\n", - " Oxidation (M) site IDs \n", - "0 NaN \n", - "1 NaN \n", - "2 NaN \n", - "3 NaN \n", - "4 NaN \n", - "\n", - "[5 rows x 60 columns]" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "msms_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "msms_exp1_df = msms_df[msms_df[\"Raw file\"] == \"BBM_647_P241_02_07_ssDDA_MIA_001\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "ms1_scans_df = pd.read_csv(os.path.join(txt_path, \"msScans.txt\"), sep=\"\\t\")\n", - "ms2_scans_df = pd.read_csv(os.path.join(txt_path, \"msmsScans.txt\"), sep=\"\\t\")" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Raw fileScan numberScan indexRetention timeCycle timeIon injection timeBase peak intensityTotal ion currentMS/MS countMass calibration...Multiplets / sIdentified multiplets / sMultiplet identification rate [%]MS/MS / sIdentified MS/MS / sMS/MS identification rate [%]Intens Comp FactorCTCD CompRawOvFtTAGC Fill
0BBM_647_P241_02_07_ssDDA_MIA_001100.0028180.138362.230411027763000.0-2.2526...8.0031.41817.7212.662.25217.79NaNNaN20807.61.00
1BBM_647_P241_02_07_ssDDA_MIA_001210.0051240.138342.227779031073000.0-2.2526...8.0021.41717.7112.652.25117.79NaNNaN19506.31.00
2BBM_647_P241_02_07_ssDDA_MIA_001320.0074300.1383850.016475030815000.0-2.2526...8.0001.41717.7112.642.25017.79NaNNaN326321.30.11
3BBM_647_P241_02_07_ssDDA_MIA_001430.0097360.1393950.016412030273000.0-2.2526...7.9981.41617.7012.642.24917.80NaNNaN321359.60.72
4BBM_647_P241_02_07_ssDDA_MIA_001540.0120590.1383550.015816029983000.0-2.2526...7.9961.41517.6912.632.24817.80NaNNaN317618.30.78
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5 rows × 28 columns

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" - ], - "text/plain": [ - " Raw file Scan number Scan index Retention time \\\n", - "0 BBM_647_P241_02_07_ssDDA_MIA_001 1 0 0.002818 \n", - "1 BBM_647_P241_02_07_ssDDA_MIA_001 2 1 0.005124 \n", - "2 BBM_647_P241_02_07_ssDDA_MIA_001 3 2 0.007430 \n", - "3 BBM_647_P241_02_07_ssDDA_MIA_001 4 3 0.009736 \n", - "4 BBM_647_P241_02_07_ssDDA_MIA_001 5 4 0.012059 \n", - "\n", - " Cycle time Ion injection time Base peak intensity Total ion current \\\n", - "0 0.13836 2.2 304110 2776300 \n", - "1 0.13834 2.2 277790 3107300 \n", - "2 0.13838 50.0 164750 3081500 \n", - "3 0.13939 50.0 164120 3027300 \n", - "4 0.13835 50.0 158160 2998300 \n", - "\n", - " MS/MS count Mass calibration ... Multiplets / s \\\n", - "0 0.0 -2.2526 ... 8.003 \n", - "1 0.0 -2.2526 ... 8.002 \n", - "2 0.0 -2.2526 ... 8.000 \n", - "3 0.0 -2.2526 ... 7.998 \n", - "4 0.0 -2.2526 ... 7.996 \n", - "\n", - " Identified multiplets / s Multiplet identification rate [%] MS/MS / s \\\n", - "0 1.418 17.72 12.66 \n", - "1 1.417 17.71 12.65 \n", - "2 1.417 17.71 12.64 \n", - "3 1.416 17.70 12.64 \n", - "4 1.415 17.69 12.63 \n", - "\n", - " Identified MS/MS / s MS/MS identification rate [%] Intens Comp Factor \\\n", - "0 2.252 17.79 NaN \n", - "1 2.251 17.79 NaN \n", - "2 2.250 17.79 NaN \n", - "3 2.249 17.80 NaN \n", - "4 2.248 17.80 NaN \n", - "\n", - " CTCD Comp RawOvFtT AGC Fill \n", - "0 NaN 20807.6 1.00 \n", - "1 NaN 19506.3 1.00 \n", - "2 NaN 326321.3 0.11 \n", - "3 NaN 321359.6 0.72 \n", - "4 NaN 317618.3 0.78 \n", - "\n", - "[5 rows x 28 columns]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ms1_scans_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Raw fileScan numberRetention timeIon injection timeTotal ion currentCollision energySummationsBase peak intensityElapsed timeIdentified...ProteinsScoreExperimentIntens Comp FactorCTCD CompRawOvFtTAGC FillScan indexMS scan indexMS scan number
0BBM_647_P241_02_07_ssDDA_MIA_001390.09089532.0333000280179260.0NaN-...NaN1NaNNaN10556.30.0103738
1BBM_647_P241_02_07_ssDDA_MIA_001400.09167132.0414790280106230.0NaN-...NaN1NaNNaN14693.40.0113738
2BBM_647_P241_02_07_ssDDA_MIA_001410.09239632.013144028027357.0NaN-...NaN1NaNNaN6674.90.0123738
3BBM_647_P241_02_07_ssDDA_MIA_001420.09312032.011499028041049.0NaN-...NaN1NaNNaN5185.00.0133738
4BBM_647_P241_02_07_ssDDA_MIA_001430.09384432.015755028081491.0NaN-...NaN1NaNNaN8048.80.0143738
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5 rows × 41 columns

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" - ], - "text/plain": [ - " Raw file Scan number Retention time \\\n", - "0 BBM_647_P241_02_07_ssDDA_MIA_001 39 0.090895 \n", - "1 BBM_647_P241_02_07_ssDDA_MIA_001 40 0.091671 \n", - "2 BBM_647_P241_02_07_ssDDA_MIA_001 41 0.092396 \n", - "3 BBM_647_P241_02_07_ssDDA_MIA_001 42 0.093120 \n", - "4 BBM_647_P241_02_07_ssDDA_MIA_001 43 0.093844 \n", - "\n", - " Ion injection time Total ion current Collision energy Summations \\\n", - "0 32.0 333000 28 0 \n", - "1 32.0 414790 28 0 \n", - "2 32.0 131440 28 0 \n", - "3 32.0 114990 28 0 \n", - "4 32.0 157550 28 0 \n", - "\n", - " Base peak intensity Elapsed time Identified ... Proteins Score \\\n", - "0 179260.0 NaN - ... NaN \n", - "1 106230.0 NaN - ... NaN \n", - "2 27357.0 NaN - ... NaN \n", - "3 41049.0 NaN - ... NaN \n", - "4 81491.0 NaN - ... NaN \n", - "\n", - " Experiment Intens Comp Factor CTCD Comp RawOvFtT AGC Fill Scan index \\\n", - "0 1 NaN NaN 10556.3 0.01 0 \n", - "1 1 NaN NaN 14693.4 0.01 1 \n", - "2 1 NaN NaN 6674.9 0.01 2 \n", - "3 1 NaN NaN 5185.0 0.01 3 \n", - "4 1 NaN NaN 8048.8 0.01 4 \n", - "\n", - " MS scan index MS scan number \n", - "0 37 38 \n", - "1 37 38 \n", - "2 37 38 \n", - "3 37 38 \n", - "4 37 38 \n", - "\n", - "[5 rows x 41 columns]" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ms2_scans_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "ms1_scans_exp1_df = ms1_scans_df[\n", - " ms1_scans_df[\"Raw file\"] == \"BBM_647_P241_02_07_ssDDA_MIA_001\"\n", - "]\n", - "ms2_scans_exp1_df = ms2_scans_df[\n", - " ms2_scans_df[\"Raw file\"] == \"BBM_647_P241_02_07_ssDDA_MIA_001\"\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "([,\n", - " ],\n", - " [Text(1.080403427608183, 0.20670857169573256, 'Number of MS1 scans'),\n", - " Text(-1.0804034348657274, -0.20670853376273113, 'Number of MS2 scans')],\n", - " [Text(0.5893109605135544, 0.11275013001585411, '6.0%\\n(2420)'),\n", - " Text(-0.5893109644722149, -0.11275010932512605, '94.0%\\n(37797)')])" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "plt.rc(\"font\", size=14)\n", - "fig, ax = plt.subplots()\n", - "\n", - "\n", - "def func(pct, allvals):\n", - " absolute = int(np.round(pct / 100.0 * np.sum(allvals)))\n", - " return f\"{pct:.1f}%\\n({absolute:d})\"\n", - "\n", - "\n", - "data = [2420, 37797]\n", - "\n", - "ax.pie(\n", - " data,\n", - " labels=[\"Number of MS1 scans\", \"Number of MS2 scans\"],\n", - " autopct=lambda pct: func(pct, data),\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "sbs", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/paper_01_exp_figure1.ipynb b/notebooks/paper_01_exp_figure1.ipynb deleted file mode 100644 index 9621a3b..0000000 --- a/notebooks/paper_01_exp_figure1.ipynb +++ /dev/null @@ -1,721658 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from importlib import reload\n", - "from IPython.core.interactiveshell import InteractiveShell\n", - "%load_ext autoreload\n", - "InteractiveShell.ast_node_interactivity = \"all\"\n", - "import logging\n", - "logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 15:31:00,393 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", - "2024-10-29 15:31:00,430 - numexpr.utils - INFO - NumExpr defaulting to 8 threads.\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", - " from pandas.core import (\n" - ] - } - ], - "source": [ - "import pandas as pd\n", - "import numpy as np\n", - "import os\n", - "import sys\n", - "\n", - "module_path = os.path.abspath(os.path.join(\"..\"))\n", - "if module_path not in sys.path:\n", - " sys.path.append(module_path)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Load Data" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from utils.config import get_cfg_defaults\n", - "from utils.singleton_swaps_optimization import swaps_optimization_cfg\n", - "import sparse\n", - "\n", - "config_path = \"/cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_30min_exp_library_no_decoy_20241002_170450_580562/config_20241002_170450_580562.yaml\"\n", - "cfg = get_cfg_defaults(swaps_optimization_cfg)\n", - "cfg.merge_from_file(config_path)\n", - "maxquant_result_ref = pd.read_pickle(cfg.DICT_PICKLE_PATH)\n", - "\n", - "mobility_values_df = pd.read_csv(os.path.join(cfg.RESULT_PATH, \"mobility_values.csv\"))\n", - "ms1scans = pd.read_csv(os.path.join(cfg.RESULT_PATH, \"ms1scans.csv\"))\n", - "act_dir = os.path.join(cfg.RESULT_PATH, \"results\", \"activation\")\n", - "\n", - "eval_dir = \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig1_exp_dict/\"\n", - "os.makedirs(eval_dir, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Result Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 15:32:08,843 - matplotlib - DEBUG - matplotlib data path: /cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data\n", - "2024-10-29 15:32:08,853 - matplotlib - DEBUG - CONFIGDIR=/cmnfs/home/z.xiao/.config/matplotlib\n", - "2024-10-29 15:32:08,856 - matplotlib - DEBUG - interactive is False\n", - "2024-10-29 15:32:08,857 - matplotlib - DEBUG - platform is linux\n", - "2024-10-29 15:32:09,011 - matplotlib - DEBUG - CACHEDIR=/cmnfs/home/z.xiao/.cache/matplotlib\n", - "2024-10-29 15:32:09,018 - matplotlib.font_manager - DEBUG - Using fontManager instance from /cmnfs/home/z.xiao/.cache/matplotlib/fontlist-v330.json\n", - "2024-10-29 15:32:10,360 - h5py._conv - DEBUG - Creating converter from 7 to 5\n", - "2024-10-29 15:32:10,361 - h5py._conv - DEBUG - Creating converter from 5 to 7\n", - "2024-10-29 15:32:10,362 - h5py._conv - DEBUG - Creating converter from 7 to 5\n", - "2024-10-29 15:32:10,363 - h5py._conv - DEBUG - Creating converter from 5 to 7\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n", - "2024-10-29 15:32:15,120 - result_analysis.result_analysis - INFO - Drop na values in pept_act_sum_filter_by_im, Pept activation sum entries: 51800\n", - "2024-10-29 15:32:15,121 - result_analysis.result_analysis - INFO - Filtering the data by the sum of intensity threshold 2, number of entries before filtering 51800\n", - "2024-10-29 15:32:15,123 - result_analysis.result_analysis - INFO - Number of entries after filtering 51799\n", - "2024-10-29 15:32:15,123 - result_analysis.result_analysis - INFO - No decoy entries in the data, using FDR threshold of dictionary 0.2\n", - "2024-10-29 15:32:15,264 - result_analysis.result_analysis - INFO - Number of entries after merging 51799 and columns Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'MS1_frame_idx_right_ref', 'IsoMZ', 'IsoAbundance', 'mz_rank', 'mz_bin',\n", - " 'mz_length', 'pept_batch_idx', 'Decoy', 'pept_act_sum_filter_by_im',\n", - " 'log_sum_intensity'],\n", - " dtype='object', length=109)\n", - "2024-10-29 15:32:15,363 - utils.plot - INFO - Data: Intensity_log, pept_act_sum_filter_by_im_log, slope = 1.036, intercept = -0.696, Pearson's R = 0.942, Spearman's R = 0.931\n", - "2024-10-29 15:32:57,878 - matplotlib.pyplot - DEBUG - Loaded backend module://matplotlib_inline.backend_inline version unknown.\n", - "2024-10-29 15:32:57,885 - matplotlib.pyplot - DEBUG - Loaded backend module://matplotlib_inline.backend_inline version unknown.\n", - "2024-10-29 15:32:57,893 - matplotlib.font_manager - DEBUG - findfont: Matching sans\\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=20.0.\n", - "2024-10-29 15:32:57,895 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996\n", - "2024-10-29 15:32:57,898 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,898 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,899 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,899 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,900 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,900 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,901 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,901 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,901 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,902 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05\n", - "2024-10-29 15:32:57,902 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,903 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,903 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,904 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,904 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,905 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,905 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,906 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,906 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,907 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,907 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,908 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,908 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,909 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,909 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,910 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,910 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,910 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,911 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335\n", - "2024-10-29 15:32:57,911 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,912 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,912 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05\n", - "2024-10-29 15:32:57,913 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,913 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,914 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,914 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,915 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,915 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-Bold.otf', name='Nimbus Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,916 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-malayalam/Lohit-Malayalam.ttf', name='Lohit Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,916 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramondSC08-Regular.ttf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,917 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Medium.ttf', name='Rasa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:57,917 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05\n", - "2024-10-29 15:32:57,918 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstTitleL.ttf', name='KacstTitleL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,918 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhojki-Regular.ttf', name='Noto Sans Khojki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,919 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode-BoldItalic.ttf', name='Junicode', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:57,919 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThaana-Bold.ttf', name='Noto Sans Thaana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,919 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-bold.otf', name='TeX Gyre Pagella', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,920 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGurmukhi-Regular.ttf', name='Noto Sans Gurmukhi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,920 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-Bold.otf', name='C059', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,921 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansShavian-Regular.ttf', name='Noto Sans Shavian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,921 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-BoldOblique.otf', name='Norasi', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,922 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-SemiboldItalic.ttf', name='Lato', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:57,922 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Black.ttf', name='Roboto', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525\n", - "2024-10-29 15:32:57,923 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa-Bold.ttf', name='Purisa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,923 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-B.ttf', name='Ubuntu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,924 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMultani-Regular.ttf', name='Noto Sans Multani', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,924 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBengali-Regular.ttf', name='Noto Sans Bengali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,925 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi.otf', name='Norasi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,925 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-Italic.ttf', name='Cousine', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,926 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-tamil/Lohit-Tamil.ttf', name='Lohit Tamil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,926 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-Demi.otf', name='URW Bookman', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:57,927 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-regular.otf', name='TeX Gyre Termes', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,927 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-Regular.otf', name='Accanthis ADF Std', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,927 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono.otf', name='Tlwg Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,928 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-Regular.ttf', name='Tinos', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,928 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCaucasianAlbanian-Regular.ttf', name='Noto Sans Caucasian Albanian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,929 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baskerville/GFSBaskerville.otf', name='GFS Baskerville', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,929 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-MediumItalic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=500, stretch='condensed', size='scalable')) = 11.344999999999999\n", - "2024-10-29 15:32:57,930 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDogra-Regular.ttf', name='Noto Serif Dogra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,930 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-Italic.otf', name='Accanthis ADF Std', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,931 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-bold.otf', name='TeX Gyre Heros', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,931 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Regular.ttf', name='Liberation Sans Narrow', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:32:57,932 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-BoldItalic.ttf', name='Caladea', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,932 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-BoldOblique.ttf', name='Umpush', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,933 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono12-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,933 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSans.otf', name='FreeSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,934 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansManichaean-Regular.ttf', name='Noto Sans Manichaean', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,934 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-Oblique.otf', name='Umpush', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,935 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,935 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman8-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,936 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNushu-Regular.ttf', name='Noto Sans Nushu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,936 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/Muktibold.ttf', name='Mukti', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,937 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-BoldItalic.otf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,937 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/Gentium-I.ttf', name='Gentium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,937 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist-BoldOblique.otf', name='Tlwg Typist', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,938 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree.ttf', name='Waree', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,938 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHanifiRohingya-Regular.ttf', name='Noto Sans Hanifi Rohingya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,939 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono-BoldOblique.otf', name='Tlwg Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,939 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-BoldItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,940 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/mallanna.ttf', name='Mallanna', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,940 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMandaic-Regular.ttf', name='Noto Sans Mandaic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,941 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-telugu/Lohit-Telugu.ttf', name='Lohit Telugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,941 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa-Oblique.ttf', name='Purisa', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,942 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans17-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,942 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsSm-Regular.otf', name='STIXIntegralsSm', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,943 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-Bold.otf', name='Nimbus Sans Narrow', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:32:57,943 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMonoOblique.ttf', name='FreeMono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,944 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-bolditalic.otf', name='TeX Gyre Schola', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,944 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-italic.otf', name='TeX Gyre Termes', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,944 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda-Oblique.otf', name='Garuda', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,945 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Gurajada.ttf', name='Gurajada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,946 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhmer-Bold.ttf', name='Noto Sans Khmer', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,946 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCuneiform-Regular.ttf', name='Noto Sans Cuneiform', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,947 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsD-Regular.otf', name='STIXIntegralsD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,947 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-Italic.otf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,947 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-Bold.otf', name='Accanthis ADF Std', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,948 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipaexfont-mincho/ipaexm.ttf', name='IPAexMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,948 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidot.otf', name='GFS Didot', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,949 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono-Oblique.otf', name='Tlwg Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,949 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Bold.ttf', name='Liberation Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,950 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-Regular.ttf', name='Liberation Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,950 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBuhid-Regular.ttf', name='Noto Sans Buhid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,951 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThaana-Regular.ttf', name='Noto Sans Thaana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,951 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-BoldItalic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,952 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedThai-Regular.ttf', name='Noto Looped Thai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,952 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSans.ttf', name='FreeSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,953 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-Oblique.ttf', name='Umpush', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,953 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-regular.otf', name='Latin Modern Mono Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,954 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-LightItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:57,954 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/StandardSymbolsPS.otf', name='Standard Symbols PS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,955 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/ramabhadra.ttf', name='Ramabhadra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,955 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05\n", - "2024-10-29 15:32:57,955 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-BoldCondIt.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:32:57,956 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/D050000L.otf', name='D050000L', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,956 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAir-Regular.ttf', name='Noto Sans Tifinagh Air', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,957 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMahajani-Regular.ttf', name='Noto Sans Mahajani', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,957 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-Regular.ttf', name='Carlito', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,958 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansEthiopic-Bold.ttf', name='Noto Sans Ethiopic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,958 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-Regular.otf', name='Nimbus Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,959 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-guru-extra/Saab.ttf', name='Saab', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,959 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,960 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/suranna.ttf', name='Suranna', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,960 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandemi10-oblique.otf', name='Latin Modern Roman Demi', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:57,961 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifThai-Bold.ttf', name='Noto Serif Thai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,961 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa-Oblique.otf', name='Purisa', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,975 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGujarati-Regular.ttf', name='Noto Sans Gujarati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,975 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Manjari-Bold.otf', name='Manjari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,976 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOlChiki-Regular.ttf', name='Noto Sans Ol Chiki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,976 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-CondItalic.otf', name='Gillius ADF', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:32:57,977 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-deva-extra/chandas1-2.ttf', name='Chandas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,978 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Bold-Italic.ttf', name='Go', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:57,978 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-Roman.otf', name='C059', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,979 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_RI.otf', name='Linux Biolinum O', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,979 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-BoldCond.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:32:57,980 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono8-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,981 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansdemicond10-oblique.otf', name='Latin Modern Sans Demi Cond', style='oblique', variant='normal', weight=600, stretch='condensed', size='scalable')) = 11.44\n", - "2024-10-29 15:32:57,981 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoDotum.ttf', name='UnJamoDotum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,982 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstLetter.ttf', name='KacstLetter', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:57,982 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-Book.otf', name='URW Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,983 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-boldoblique.otf', name='Latin Modern Mono Light', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,984 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTagalog-Regular.ttf', name='Noto Sans Tagalog', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,984 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifArmenian-Bold.ttf', name='Noto Serif Armenian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,985 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-deva-extra/samanata.ttf', name='Samanata', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,985 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMonoBold.otf', name='FreeMono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,986 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstPen.ttf', name='KacstPen', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:57,986 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Regular.ttf', name='Roboto', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,987 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans12-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,987 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-Italic.otf', name='Accanthis ADF Std No3', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,988 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSundanese-Bold.ttf', name='Noto Sans Sundanese', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,988 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-MI.ttf', name='Ubuntu', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:57,989 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBassaVah-Regular.ttf', name='Noto Sans Bassa Vah', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,989 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-Italic.otf', name='C059', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,990 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoTraditionalNushu-Regular.ttf', name='Noto Traditional Nushu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,990 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:32:57,991 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-LightItalic.otf', name='URW Bookman', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:57,991 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-LightOblique.otf', name='Umpush', style='oblique', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:57,992 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-Italic.otf', name='Berenis ADF Pro', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,992 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasI.ttf', name='Gentium Basic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:57,993 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari.ttf', name='Kinnari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,993 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArabic-Regular.ttf', name='Noto Sans Arabic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,994 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHebrew-Regular.ttf', name='Noto Sans Hebrew', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,994 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-Bold.ttf', name='Gentium Book Plus', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:32:57,995 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant10-bold.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,995 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-Bold.otf', name='Berenis ADF Pro', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,996 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree.otf', name='Waree', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,996 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-Bold.ttf', name='Tinos', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,997 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-C.ttf', name='Ubuntu Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:32:57,997 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,998 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans9-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:57,998 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-BoldOblique.ttf', name='Kinnari', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:57,999 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman5-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:57,999 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoKufiArabic-Bold.ttf', name='Noto Kufi Arabic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,000 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-Regular.ttf', name='Charis SIL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,000 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlam-Regular.ttf', name='Noto Sans Adlam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,001 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Semibold.ttf', name='Lato', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,001 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansModi-Regular.ttf', name='Noto Sans Modi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,002 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-Italic.otf', name='Nimbus Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,002 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond-Initials.ttf', name='EB Garamond Initials', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,003 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/gulim.ttf', name='Baekmuk Gulim', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,003 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Regular.ttf', name='Go', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,004 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXVariants-Regular.otf', name='STIXVariants', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,004 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoBatang.ttf', name='UnJamoBatang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,005 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTagbanwa-Regular.ttf', name='Noto Sans Tagbanwa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,005 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-SemiBoldItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,006 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-gothic/ipag.ttf', name='IPAGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,006 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-tamil-classical/Lohit-Tamil-Classical.ttf', name='Lohit Tamil Classical', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,007 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeThreeSym-Regular.otf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,007 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeFiveSym-Regular.otf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,008 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSansBoldOblique.ttf', name='FreeSans', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,009 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSylotiNagri-Regular.ttf', name='Noto Sans Syloti Nagri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,009 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramondSC08-Regular.otf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,010 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamilSlanted-Bold.ttf', name='Noto Serif Tamil Slanted', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,010 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Black.ttf', name='Lato', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525\n", - "2024-10-29 15:32:58,011 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAPT-Regular.ttf', name='Noto Sans Tifinagh APT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,011 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond08-Regular.ttf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,012 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisia.otf', name='GFS Artemisia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,012 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee.ttf', name='Sawasdee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,013 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXVariants-Bold.otf', name='STIXVariants', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,013 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLycian-Regular.ttf', name='Noto Sans Lycian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,014 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-LI.ttf', name='Ubuntu', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,014 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman-Italic.ttf', name='Laksaman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,015 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOlChiki-Bold.ttf', name='Noto Sans Ol Chiki', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,015 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-Bold.ttf', name='Caladea', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,016 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Rachana-Regular.ttf', name='Rachana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,016 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Gidugu.ttf', name='Gidugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,017 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoRashiHebrew-Regular.ttf', name='Noto Rashi Hebrew', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,017 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansEgyptianHieroglyphs-Regular.ttf', name='Noto Sans Egyptian Hieroglyphs', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,018 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant8-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,018 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCherokee-Bold.ttf', name='Noto Sans Cherokee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,019 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhmer-Regular.ttf', name='Noto Serif Khmer', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,019 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_DR.otf', name='Linux Libertine Display O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,020 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/bodoni-classic/GFSBodoniClassic.otf', name='GFS BodoniClassic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,020 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-Bold.ttf', name='Umpush', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,021 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 0.25\n", - "2024-10-29 15:32:58,021 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-bold.otf', name='TeX Gyre Termes', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,022 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono10-italic.otf', name='Latin Modern Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,022 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa-Bold.otf', name='Purisa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,023 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman-BoldItalic.otf', name='Laksaman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,023 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Regular.ttf', name='Rasa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,024 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThai-Bold.ttf', name='Noto Sans Thai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,024 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-BoldItalic.otf', name='Nimbus Mono PS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,025 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Semibold.ttf', name='Open Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,025 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Italic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,026 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/LakkiReddy.ttf', name='LakkiReddy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,026 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldPersian-Regular.ttf', name='Noto Sans Old Persian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,027 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-BoldItalic.ttf', name='Noto Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,027 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansElymaic-Regular.ttf', name='Noto Sans Elymaic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,028 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifBalinese-Regular.ttf', name='Noto Serif Balinese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,028 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBrahmi-Regular.ttf', name='Noto Sans Brahmi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,029 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/pagul/Pagul.ttf', name='Pagul', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,029 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/porson/GFSPorson.otf', name='GFS Porson', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,030 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-BoldItalic.otf', name='Cabin', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,030 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKannada-Bold.ttf', name='Noto Sans Kannada', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,031 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-Regular.otf', name='Nimbus Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,031 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMeroitic-Regular.ttf', name='Noto Sans Meroitic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,032 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMalayalam-Regular.ttf', name='Noto Sans Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,032 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansRejang-Regular.ttf', name='Noto Sans Rejang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,033 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansInscriptionalParthian-Regular.ttf', name='Noto Sans Inscriptional Parthian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,033 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Regular.ttf', name='Lato', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,034 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa-BoldOblique.ttf', name='Purisa', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,034 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-BoldOblique.ttf', name='Norasi', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,035 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifYezidi-Bold.ttf', name='Noto Serif Yezidi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,035 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-orya-extra/utkal.ttf', name='ori1Uni', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,036 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-regular.otf', name='TeX Gyre Bonum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,036 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-Bold.otf', name='Lobster Two', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,037 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996\n", - "2024-10-29 15:32:58,037 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKannada-Regular.ttf', name='Noto Sans Kannada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,038 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm-math/latinmodern-math.otf', name='Latin Modern Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,038 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/SyamalaRamana.ttf', name='Syamala Ramana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,039 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Bold.ttf', name='Lato', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,039 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono-Oblique.ttf', name='Tlwg Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,040 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Regular.ttf', name='Liberation Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,040 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-bold.otf', name='Latin Modern Mono Prop Light', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,041 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter-BoldOblique.otf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,041 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist.otf', name='Tlwg Typist', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,042 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-BoldItalic.otf', name='Nimbus Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,042 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-Italic.ttf', name='Norasi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,043 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKayahLi-Bold.ttf', name='Noto Sans Kayah Li', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,043 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-Italic.ttf', name='Arimo', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,044 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLepcha-Regular.ttf', name='Noto Sans Lepcha', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,044 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Medium.ttf', name='Yrsa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,045 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidotBold.otf', name='GFS Didot', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,045 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-BoldItalic.ttf', name='Arimo', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,046 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-BoldItalic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,046 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree-Bold.otf', name='Waree', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,047 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoprop10-regular.otf', name='Latin Modern Mono Prop', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,047 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-italic.otf', name='TeX Gyre Adventor', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,048 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSansOblique.ttf', name='FreeSans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,048 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedLao-Bold.ttf', name='Noto Looped Lao', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,049 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Italic.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,049 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman-Italic.otf', name='Laksaman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,050 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,050 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Medium.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=500, stretch='condensed', size='scalable')) = 10.344999999999999\n", - "2024-10-29 15:32:58,051 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-BoldItalic.otf', name='Norasi', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,051 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Ponnala.ttf', name='Ponnala', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,052 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-bold.otf', name='TeX Gyre Cursor', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,053 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Suravaram.ttf', name='Suravaram', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,053 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-BoldItalic.otf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,054 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree-Bold.ttf', name='Waree', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,054 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-Italic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,055 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_R.otf', name='Linux Biolinum O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,055 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/Z003-MediumItalic.otf', name='Z003', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,056 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Thin.ttf', name='Lato', style='normal', variant='normal', weight=200, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,056 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-Regular.otf', name='Accanthis ADF Std No2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,057 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/glyphicons/glyphicons-halflings-regular.ttf', name='GLYPHICONS Halflings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,057 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee-Bold.otf', name='Sawasdee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,058 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansdemicond10-regular.otf', name='Latin Modern Sans Demi Cond', style='normal', variant='normal', weight=600, stretch='condensed', size='scalable')) = 10.44\n", - "2024-10-29 15:32:58,058 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTibetan-Bold.ttf', name='Noto Serif Tibetan', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,059 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-Bold.ttf', name='Kinnari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,059 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMono.otf', name='FreeMono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,060 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-BI.ttf', name='Ubuntu', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,060 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPalmyrene-Regular.ttf', name='Noto Sans Palmyrene', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,061 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-Oblique.ttf', name='Kinnari', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,061 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/theokritos/GFSTheokritos.otf', name='GFS Theokritos', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,062 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLao-Regular.ttf', name='Noto Sans Lao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,062 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCham-Regular.ttf', name='Noto Sans Cham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,063 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGurmukhi-Bold.ttf', name='Noto Serif Gurmukhi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,063 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTangut-Regular.ttf', name='Noto Serif Tangut', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,064 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Smallcaps-Italic.ttf', name='Go Smallcaps', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,064 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSymbols2-Regular.ttf', name='Noto Sans Symbols2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,065 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Heavy.ttf', name='Lato', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:32:58,065 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond-InitialsF2.ttf', name='EB Garamond Initials Fill2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,066 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-bolditalic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,066 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-Oblique.otf', name='Kinnari', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,067 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifHebrew-Regular.ttf', name='Noto Serif Hebrew', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,067 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans12-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,068 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Italic.ttf', name='Liberation Sans Narrow', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:32:58,068 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMeeteiMayek-Regular.ttf', name='Noto Sans Meetei Mayek', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,084 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMono-Regular.ttf', name='Noto Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,085 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifNyiakengPuachueHmong-Bold.ttf', name='Noto Serif Hmong Nyiakeng', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,085 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lao/Phetsarath_OT.ttf', name='Phetsarath OT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,086 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-Bold.otf', name='Nimbus Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,086 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldNorthArabian-Regular.ttf', name='Noto Sans Old North Arabian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,087 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-regular.otf', name='Latin Modern Sans Quotation', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,087 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifThai-Regular.ttf', name='Noto Serif Thai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,088 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGujarati-Regular.ttf', name='Noto Serif Gujarati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,088 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoKufiArabic-Regular.ttf', name='Noto Kufi Arabic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,089 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-Italic.otf', name='Nimbus Mono PS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,089 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ttf-khmeros-core/KhmerOSsys.ttf', name='Khmer OS System', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,090 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-Regular.otf', name='Lobster Two', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,091 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnPilgiBold.ttf', name='UnPilgi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,091 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMendeKikakui-Regular.ttf', name='Noto Sans Mende Kikakui', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,092 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Cond.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:32:58,092 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMro-Regular.ttf', name='Noto Sans Mro', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,093 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKannada-Bold.ttf', name='Noto Serif Kannada', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,093 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-M.ttf', name='Ubuntu', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,094 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoltcond10-regular.otf', name='Latin Modern Mono Light Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:32:58,094 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-Bold.otf', name='Kinnari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,095 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-Italic.otf', name='Nimbus Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,095 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Italic.ttf', name='Go', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,096 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus-compact/GentiumPlusCompact-I.ttf', name='Gentium Plus Compact', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,096 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-Light.otf', name='URW Bookman', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,097 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNaskhArabic-Bold.ttf', name='Noto Naskh Arabic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,098 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansElbasan-Regular.ttf', name='Noto Sans Elbasan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,098 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramondSC12-Regular.otf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,098 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Light.ttf', name='Rasa', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,099 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-BoldItalic.ttf', name='Noto Sans Display', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,099 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-Italic.ttf', name='Noto Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,100 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMono.ttf', name='FreeMono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,100 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Regular.ttf', name='Quicksand', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,101 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/comfortaa/Comfortaa-Bold.ttf', name='Comfortaa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,101 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,102 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-Regular.otf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,102 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-Bold.otf', name='P052', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,103 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/PadaukBook-Regular.ttf', name='Padauk Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,103 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromancaps10-regular.otf', name='Latin Modern Roman Caps', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,104 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak-fonts/Samyak-Tamil.ttf', name='Samyak Tamil', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,104 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-ExtraBold.otf', name='Cantarell', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:32:58,105 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma-Bold.ttf', name='Loma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,105 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman17-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,106 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond-InitialsF2.otf', name='EB Garamond Initials Fill2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,106 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-BoldOblique.otf', name='Kinnari', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,107 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-BoldItalic.ttf', name='Lato', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,107 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOriya-Bold.ttf', name='Noto Sans Oriya', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,108 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-Italic.otf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,108 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCypriot-Regular.ttf', name='Noto Sans Cypriot', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,109 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCherokee-Regular.ttf', name='Noto Sans Cherokee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,109 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-Light.ttf', name='Umpush', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,110 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeTwoSym-Bold.otf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,110 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-BlackItalic.ttf', name='Roboto', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525\n", - "2024-10-29 15:32:58,111 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma.ttf', name='Loma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,111 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMedefaidrin-Bold.ttf', name='Noto Sans Medefaidrin', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,112 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnGraphicBold.ttf', name='UnGraphic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,112 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-BoldCondItalic.otf', name='Gillius ADF', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:32:58,113 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSansBold.otf', name='FreeSans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,113 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnYetgul.ttf', name='UnYetgul', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,114 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-regular.otf', name='TeX Gyre Pagella', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,114 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,115 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-BoldItalic.otf', name='Kinnari', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,116 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCanadianAboriginal-Bold.ttf', name='Noto Sans Canadian Aboriginal', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,116 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSaurashtra-Regular.ttf', name='Noto Sans Saurashtra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,117 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArmenian-Regular.ttf', name='Noto Sans Armenian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,117 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/complutum/GFSPolyglot.otf', name='GFS Complutum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,118 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhudawadi-Regular.ttf', name='Noto Sans Khudawadi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,126 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSansOblique.otf', name='FreeSans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,127 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGurmukhi-Bold.ttf', name='Noto Sans Gurmukhi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,127 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-bold.otf', name='TeX Gyre Bonum', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,128 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldSogdian-Regular.ttf', name='Noto Sans Old Sogdian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,129 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoMono-Regular.ttf', name='Noto Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,129 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/olga/GFSOlga.otf', name='GFS Olga', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,130 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,130 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-ExtraLight.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=200, stretch='normal', size='scalable')) = 0.24\n", - "2024-10-29 15:32:58,131 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-ThinItalic.ttf', name='Lato', style='italic', variant='normal', weight=200, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,132 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/Mukti.ttf', name='Mukti', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,133 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-Bold.ttf', name='Charis SIL', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,134 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-punjabi/Lohit-Gurmukhi.ttf', name='Lohit Gurmukhi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,134 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda-Bold.otf', name='Garuda', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,135 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDinaru.ttf', name='UnDinaru', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,135 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman8-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,136 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifEthiopic-Regular.ttf', name='Noto Serif Ethiopic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,137 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono9-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,138 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Medium.ttf', name='Go Medium', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,138 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Regular.ttf', name='Yrsa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,139 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-R.ttf', name='Ubuntu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,140 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/NATS.ttf', name='NATS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,140 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Bold.ttf', name='Open Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,141 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-Oblique.otf', name='Norasi', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,141 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDevanagari-Regular.ttf', name='Noto Sans Devanagari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,142 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoltcond10-oblique.otf', name='Latin Modern Mono Light Cond', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:32:58,144 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-Regular.ttf', name='Noto Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,144 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Medium.ttf', name='Lato', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,145 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-BoldItalic.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,145 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTelugu-Regular.ttf', name='Noto Serif Telugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,146 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMalayalam-Bold.ttf', name='Noto Sans Malayalam', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,146 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Italic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,147 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-BoldOblique.otf', name='Nimbus Sans Narrow', style='oblique', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:32:58,147 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_K.otf', name='Linux Biolinum Keyboard O', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,148 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-bsmi00lp/bsmi00lp.ttf', name='AR PL Mingti2L Big5', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,150 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDevanagari-Bold.ttf', name='Noto Sans Devanagari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,150 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSansBoldOblique.otf', name='FreeSans', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,151 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNaskhArabic-Regular.ttf', name='Noto Naskh Arabic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,151 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMonoBold.ttf', name='FreeMono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,152 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstArt.ttf', name='KacstArt', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,152 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansVai-Regular.ttf', name='Noto Sans Vai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,153 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-italic.otf', name='TeX Gyre Pagella', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,153 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman9-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,154 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghHawad-Regular.ttf', name='Noto Sans Tifinagh Hawad', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,156 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/padmaa-Medium-0.5.ttf', name='padmaa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,156 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-HairlineItalic.ttf', name='Lato', style='italic', variant='normal', weight=100, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,157 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBalinese-Regular.ttf', name='Noto Sans Balinese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,158 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/gazis/GFSGazis.otf', name='GFS Gazis', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,158 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-Bold.otf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,159 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-bold.otf', name='TeX Gyre Schola', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,159 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansYi-Regular.ttf', name='Noto Sans Yi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,160 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpSm-Bold.otf', name='STIXIntegralsUpSm', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,160 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Bold.ttf', name='Go', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,161 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/Gentium-R.ttf', name='Gentium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,161 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman6-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,162 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMasaramGondi-Regular.ttf', name='Noto Sans Masaram Gondi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,162 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='condensed', size='scalable')) = 1.535\n", - "2024-10-29 15:32:58,163 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Gayathri-Thin.otf', name='Gayathri', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,164 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-Oblique.otf', name='Nimbus Sans Narrow', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:32:58,166 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Italic.ttf', name='Lato', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,167 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisiaIt.otf', name='GFS Artemisia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,167 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGeorgian-Bold.ttf', name='Noto Sans Georgian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,168 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda-BoldOblique.ttf', name='Garuda', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,169 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-Regular.ttf', name='Noto Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,170 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPauCinHau-Regular.ttf', name='Noto Sans Pau Cin Hau', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,170 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSiddham-Regular.ttf', name='Noto Sans Siddham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,171 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-kalapi/Kalapi.ttf', name='Kalapi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,172 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-L.ttf', name='Ubuntu', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,172 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedLao-Regular.ttf', name='Noto Looped Lao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,173 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/batang.ttf', name='Baekmuk Batang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,173 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-Bold.ttf', name='Liberation Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,174 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Suruma.ttf', name='Suruma', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,175 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/comfortaa/Comfortaa-Regular.ttf', name='Comfortaa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,176 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-oblique.otf', name='Latin Modern Mono Light', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,177 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman7-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,178 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUp-Bold.otf', name='STIXIntegralsUp', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,178 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-Bold.otf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,179 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSundanese-Regular.ttf', name='Noto Sans Sundanese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,180 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSoyombo-Regular.ttf', name='Noto Sans Soyombo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,180 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasBI.ttf', name='Gentium Basic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,181 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman-Bold.ttf', name='Laksaman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,181 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-bold.otf', name='TeX Gyre Heros Cn', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,182 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMonoBoldOblique.ttf', name='FreeMono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,183 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-Bold.ttf', name='Noto Serif Display', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,184 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode-Italic.ttf', name='Junicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,184 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono-Bold.ttf', name='Tlwg Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,185 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnBatangBold.ttf', name='UnBatang', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,186 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-bolditalic.otf', name='TeX Gyre Heros Cn', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,187 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Manjari-Regular.otf', name='Manjari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,187 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGujarati-Bold.ttf', name='Noto Sans Gujarati', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,188 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-BoldItalic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,189 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman7-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,190 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-CondItalic.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:32:58,190 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMarchen-Regular.ttf', name='Noto Sans Marchen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,191 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghRhissaIxa-Regular.ttf', name='Noto Sans Tifinagh Rhissa Ixa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,192 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman9-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,193 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSoraSompeng-Regular.ttf', name='Noto Sans Sora Sompeng', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,193 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDevanagari-Regular.ttf', name='Noto Serif Devanagari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,194 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/padmaa.ttf', name='padmaa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,195 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,196 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono.ttf', name='Go Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,196 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-bolditalic.otf', name='TeX Gyre Termes', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,197 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond-Initials.otf', name='EB Garamond Initials', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,198 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-BoldItalic.ttf', name='Roboto', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,198 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-Regular.otf', name='STIX', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,199 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist-Oblique.otf', name='Tlwg Typist', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,199 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-Bold.ttf', name='Gentium Plus', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,200 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Bold.ttf', name='Roboto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,200 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/FoulisGreek.ttf', name='FoulisGreek', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,202 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Italic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,202 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Smallcaps.ttf', name='Go Smallcaps', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,203 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGeorgian-Bold.ttf', name='Noto Serif Georgian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,204 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo-Bold.otf', name='Tlwg Typo', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,204 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Italic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:32:58,205 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKaithi-Regular.ttf', name='Noto Sans Kaithi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,205 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Dyuthi-Regular.ttf', name='Dyuthi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,206 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda-Oblique.ttf', name='Garuda', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,206 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-SemiBold.otf', name='Cabin', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,208 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-mincho/ipamp.ttf', name='IPAPMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,209 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Regular.otf', name='Gillius ADF', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,209 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Regular.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:32:58,210 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThai-Regular.ttf', name='Noto Sans Thai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,210 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLydian-Regular.ttf', name='Noto Sans Lydian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,211 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Light.ttf', name='Open Sans', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,211 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyretermes-math.otf', name='TeX Gyre Termes Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,212 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenicBoldIt.otf', name='GFS Neohellenic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,212 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Regular.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,213 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa.ttf', name='Purisa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,213 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBatak-Regular.ttf', name='Noto Sans Batak', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,214 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipaexfont-gothic/ipaexg.ttf', name='IPAexGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,216 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGrantha-Regular.ttf', name='Noto Serif Grantha', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,217 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Bold.ttf', name='Rasa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,217 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-BoldItalic.ttf', name='Norasi', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,218 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree-Oblique.ttf', name='Waree', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,219 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldItalic-Regular.ttf', name='Noto Sans Old Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,220 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDotum.ttf', name='UnDotum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,220 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOsmanya-Regular.ttf', name='Noto Sans Osmanya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,221 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-B.ttf', name='Ubuntu Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,222 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnPilgi.ttf', name='UnPilgi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,222 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RB.otf', name='Linux Libertine O', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,223 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Medium.ttf', name='Quicksand Medium', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,224 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoSora.ttf', name='UnJamoSora', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,224 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Manjari-Thin.otf', name='Manjari', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,225 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifSinhala-Regular.ttf', name='Noto Serif Sinhala', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,225 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifHebrew-Bold.ttf', name='Noto Serif Hebrew', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,226 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDinaruBold.ttf', name='UnDinaru', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,226 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArmenian-Bold.ttf', name='Noto Sans Armenian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,227 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Regular.ttf', name='Liberation Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,227 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee-Bold.ttf', name='Sawasdee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,228 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-SemiBold.ttf', name='Rasa', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,228 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-Regular.ttf', name='Amiri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,229 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-Italic.ttf', name='Charis SIL', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,229 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBhaiksuki-Regular.ttf', name='Noto Sans Bhaiksuki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,230 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma-BoldOblique.ttf', name='Loma', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,231 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSymbols-Bold.ttf', name='Noto Sans Symbols', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,231 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter.otf', name='Tlwg Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,232 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-BoldCond.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:32:58,232 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyreschola-math.otf', name='TeX Gyre Schola Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,233 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-CondItalic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:32:58,233 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree-BoldOblique.ttf', name='Waree', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,234 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSogdian-Regular.ttf', name='Noto Sans Sogdian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,234 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans8-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,235 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee-Oblique.ttf', name='Sawasdee', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,235 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak/Samyak-Devanagari.ttf', name='Samyak Devanagari', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,236 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Italic.otf', name='Gillius ADF', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,236 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAgrawImazighen-Regular.ttf', name='Noto Sans Tifinagh Agraw Imazighen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,241 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-Bold.ttf', name='EB Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,241 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-RI.ttf', name='Ubuntu Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,242 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-italic.otf', name='TeX Gyre Schola', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,243 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/PadaukBook-Bold.ttf', name='Padauk Book', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,243 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNabataean-Regular.ttf', name='Noto Sans Nabataean', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,244 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush.otf', name='Umpush', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,244 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/dhurjati.ttf', name='Dhurjati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,245 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGlagolitic-Regular.ttf', name='Noto Sans Glagolitic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,246 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGothic-Regular.ttf', name='Noto Sans Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,247 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-Italic.ttf', name='Kinnari', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,248 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree-Oblique.otf', name='Waree', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,249 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnPenheulim.ttf', name='UnPenheulim', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,249 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMyanmar-Regular.ttf', name='Noto Serif Myanmar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,250 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-Regular.ttf', name='Noto Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,250 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasI.ttf', name='Gentium Book Basic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,251 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerifBoldItalic.ttf', name='FreeSerif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,251 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanunsl10-regular.otf', name='Latin Modern Roman Unslanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,252 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-BoldItalic.ttf', name='Noto Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,252 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-ThinItalic.ttf', name='Roboto', style='italic', variant='normal', weight=250, stretch='normal', size='scalable')) = 11.1925\n", - "2024-10-29 15:32:58,253 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifLao-Regular.ttf', name='Noto Serif Lao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,253 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-telu-extra/Pothana2000.ttf', name='Pothana2000', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,254 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-Bold.otf', name='Umpush', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,254 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Sarai/Sarai.ttf', name='Sarai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,255 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-SemiboldItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,255 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldHungarian-Regular.ttf', name='Noto Sans Old Hungarian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,256 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMyanmar-Regular.ttf', name='Noto Sans Myanmar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,259 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-gbsn00lp/gbsn00lp.ttf', name='AR PL SungtiL GB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,259 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldPermic-Regular.ttf', name='Noto Sans Old Permic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,260 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Bold.ttf', name='Liberation Sans Narrow', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:32:58,261 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldSouthArabian-Regular.ttf', name='Noto Sans Old South Arabian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,261 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnGraphic.ttf', name='UnGraphic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,262 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandemi10-regular.otf', name='Latin Modern Roman Demi', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,263 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Bold.otf', name='Cantarell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,263 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-BoldCond.otf', name='Gillius ADF', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:32:58,264 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuMathTeXGyre.ttf', name='DejaVu Math TeX Gyre', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,265 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman7-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,266 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOriya-Regular.ttf', name='Noto Sans Oriya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,266 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSyriac-Regular.ttf', name='Noto Sans Syriac', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,267 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLisu-Regular.ttf', name='Noto Sans Lisu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,268 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-BoldItalic.ttf', name='Noto Serif Display', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,268 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAhaggar-Regular.ttf', name='Noto Sans Tifinagh Ahaggar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,269 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RI.otf', name='Linux Libertine O', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,270 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMeeteiMayek-Bold.ttf', name='Noto Sans Meetei Mayek', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,271 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansRunic-Regular.ttf', name='Noto Sans Runic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,271 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-gothic/ipagp.ttf', name='IPAPGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,272 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBengali-Bold.ttf', name='Noto Sans Bengali', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,272 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic/uming.ttc', name='AR PL UMing CN', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,273 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-BoldOblique.otf', name='Umpush', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,274 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-italic.otf', name='TeX Gyre Bonum', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,274 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasB.ttf', name='Gentium Basic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,275 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPahawhHmong-Regular.ttf', name='Noto Sans Pahawh Hmong', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,275 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-Italic.ttf', name='Caladea', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,276 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAzawagh-Regular.ttf', name='Noto Sans Tifinagh Azawagh', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,276 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Regular.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,277 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/NTR.ttf', name='NTR', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,278 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiTham-Bold.ttf', name='Noto Sans Tai Tham', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,278 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstNaskh.ttf', name='KacstNaskh', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,279 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant10-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,279 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Ramaraja-Regular.ttf', name='Ramaraja', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,281 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo-BoldOblique.ttf', name='Tlwg Typo', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,282 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-BoldItalic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,283 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond08-Regular.otf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,283 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiLe-Regular.ttf', name='Noto Sans Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,284 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-BoldItalic.otf', name='Nimbus Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,285 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-LightOblique.ttf', name='Umpush', style='oblique', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,285 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Regular.otf', name='Cantarell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,286 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonocaps10-oblique.otf', name='Latin Modern Mono Caps', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,287 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman12-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,287 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Cond.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:32:58,288 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-Th.ttf', name='Ubuntu', style='normal', variant='normal', weight=250, stretch='normal', size='scalable')) = 10.1925\n", - "2024-10-29 15:32:58,288 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-BlackItalic.ttf', name='Lato', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525\n", - "2024-10-29 15:32:58,289 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/libreoffice/opens___.ttf', name='OpenSymbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,291 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 1.25\n", - "2024-10-29 15:32:58,291 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Light.ttf', name='Lato', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,292 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstOffice.ttf', name='KacstOffice', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,293 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Medium-Italic.ttf', name='Go Medium', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,293 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTirhuta-Regular.ttf', name='Noto Sans Tirhuta', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,294 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa.otf', name='Purisa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,295 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeFourSym-Regular.otf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,296 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Thin.otf', name='Cantarell', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,296 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-Bold.otf', name='Accanthis ADF Std No3', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,297 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono-Bold-Italic.ttf', name='Go Mono', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,297 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,298 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Sahadeva/sahadeva.ttf', name='Sahadeva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,299 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-Regular.otf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,299 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/asana-math/Asana-Math.otf', name='Asana Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,300 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Bold.otf', name='Gillius ADF', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,300 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNewTaiLue-Regular.ttf', name='Noto Sans New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,302 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerif.otf', name='FreeSerif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,303 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghSIL-Regular.ttf', name='Noto Sans Tifinagh SIL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,303 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-CondLight.ttf', name='Open Sans', style='normal', variant='normal', weight=300, stretch='condensed', size='scalable')) = 10.344999999999999\n", - "2024-10-29 15:32:58,304 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-LightItalic.ttf', name='Lato', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,304 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidotItalic.otf', name='GFS Didot', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,305 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-ExtraBoldItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=800, stretch='normal', size='scalable')) = 11.43\n", - "2024-10-29 15:32:58,306 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-BoldSlanted.ttf', name='Amiri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,306 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDeseret-Regular.ttf', name='Noto Sans Deseret', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,307 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-telu-extra/vemana2000.ttf', name='Vemana2000', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,307 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPsalterPahlavi-Regular.ttf', name='Noto Sans Psalter Pahlavi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,309 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiTham-Regular.ttf', name='Noto Sans Tai Tham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,310 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandunh10-regular.otf', name='Latin Modern Roman Dunhill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,310 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstBook.ttf', name='KacstBook', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,311 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBamum-Bold.ttf', name='Noto Sans Bamum', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,311 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMedefaidrin-Regular.ttf', name='Noto Sans Medefaidrin', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,312 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee-Oblique.otf', name='Sawasdee', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,312 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-oriya/Lohit-Odia.ttf', name='Lohit Odia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,313 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMyanmar-Bold.ttf', name='Noto Sans Myanmar', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,313 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-Regular.otf', name='Berenis ADF Pro', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,314 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/GentiumAlt-I.ttf', name='GentiumAlt', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,315 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee.otf', name='Sawasdee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,315 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramondSC12-Regular.ttf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,316 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-Italic.ttf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,316 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-Regular.ttf', name='Gentium Plus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,317 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-regular.otf', name='TeX Gyre Heros', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,317 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Rachana-Bold.ttf', name='Rachana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,320 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/Padauk-Bold.ttf', name='Padauk', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,320 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-BI.ttf', name='Ubuntu Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,321 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeTwoSym-Regular.otf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,322 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter-Oblique.otf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,322 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist-Bold.ttf', name='Tlwg Typist', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,323 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstPoster.ttf', name='KacstPoster', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,324 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma-Oblique.ttf', name='Loma', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,324 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisiaBoldIt.otf', name='GFS Didot', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,325 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlamUnjoined-Bold.ttf', name='Noto Sans Adlam Unjoined', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,326 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant17-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,327 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPhagsPa-Regular.ttf', name='Noto Sans PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,327 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-BoldItalic.otf', name='Berenis ADF Pro', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,328 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Bold.ttf', name='Quicksand', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,328 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-Regular.ttf', name='Arimo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,329 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Navilu/Navilu.ttf', name='Navilu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,329 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Italic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,330 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldTurkic-Regular.ttf', name='Noto Sans Old Turkic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,331 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-Bold.ttf', name='Liberation Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,331 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDotumBold.ttf', name='UnDotum', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,332 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHebrew-Bold.ttf', name='Noto Sans Hebrew', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,332 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUp-Regular.otf', name='STIXIntegralsUp', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,333 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-ExtraBold.ttf', name='Open Sans', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:32:58,333 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-Regular.ttf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,334 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonocaps10-regular.otf', name='Latin Modern Mono Caps', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,334 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/dotum.ttf', name='Baekmuk Dotum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,337 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_I.otf', name='Linux Libertine Initials O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,338 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-BoldItalic.otf', name='Accanthis ADF Std No3', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,338 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-Italic.ttf', name='Carlito', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,339 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-bolditalic.otf', name='TeX Gyre Cursor', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,340 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tibetan-machine/TibetanMachineUni.ttf', name='Tibetan Machine Uni', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,340 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-CondLightItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=300, stretch='condensed', size='scalable')) = 11.344999999999999\n", - "2024-10-29 15:32:58,341 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobster/lobster.otf', name='Lobster Two', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,341 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-MediumItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,342 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/droid/DroidSansFallbackFull.ttf', name='Droid Sans Fallback', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,342 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-BoldItalic.ttf', name='Gentium Plus', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,344 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-HeavyItalic.ttf', name='Lato', style='italic', variant='normal', weight=800, stretch='normal', size='scalable')) = 11.43\n", - "2024-10-29 15:32:58,345 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/Ani.ttf', name='Ani', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,345 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAvestan-Regular.ttf', name='Noto Sans Avestan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,346 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Peddana-Regular.ttf', name='Peddana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,346 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,348 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMalayalam-Regular.ttf', name='Noto Serif Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,348 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono.ttf', name='Tlwg Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,349 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyredejavu-math.otf', name='TeX Gyre DejaVu Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,350 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-BoldItalic.otf', name='Lobster Two', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,350 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLinearB-Regular.ttf', name='Noto Sans Linear B', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,351 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-Regular.otf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,352 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-bolditalic.otf', name='TeX Gyre Heros', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,352 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo.otf', name='Tlwg Typo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,353 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335\n", - "2024-10-29 15:32:58,354 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/Padauk-Regular.ttf', name='Padauk', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,355 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst-one/KacstOne-Bold.ttf', name='KacstOne', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,355 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansJavanese-Bold.ttf', name='Noto Sans Javanese', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,356 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman12-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,356 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBuginese-Regular.ttf', name='Noto Sans Buginese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,357 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-Regular.otf', name='Nimbus Mono PS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,357 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-Regular.ttf', name='Noto Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,358 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-boldoblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,359 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Bold.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,360 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant9-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,361 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnPen.ttf', name='UnPen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,361 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSinhala-Regular.ttf', name='Noto Sans Sinhala', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,362 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-Bold.otf', name='EB Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,363 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTelugu-Bold.ttf', name='Noto Sans Telugu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,364 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHanunoo-Regular.ttf', name='Noto Sans Hanunoo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,364 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ttf-khmeros-core/KhmerOS.ttf', name='Khmer OS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,365 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMono-Bold.ttf', name='Noto Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,366 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnShinmun.ttf', name='UnShinmun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,366 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-BoldItalic.otf', name='Accanthis ADF Std No2', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,367 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLisu-Bold.ttf', name='Noto Sans Lisu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,368 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasB.ttf', name='Gentium Book Basic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,369 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus-compact/GentiumPlusCompact-R.ttf', name='Gentium Plus Compact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,369 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/JamrulNormal.ttf', name='Jamrul', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,370 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari.otf', name='Kinnari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,370 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-BoldItalic.otf', name='STIX', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,371 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman8-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,372 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-Roman.otf', name='P052', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,373 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromancaps10-oblique.otf', name='Latin Modern Roman Caps', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,374 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo.ttf', name='Tlwg Typo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,374 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-Italic.otf', name='Kinnari', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,375 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist-Bold.otf', name='Tlwg Typist', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,375 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansImperialAramaic-Regular.ttf', name='Noto Sans Imperial Aramaic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,376 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArabic-Bold.ttf', name='Noto Sans Arabic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,377 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyrepagella-math.otf', name='TeX Gyre Pagella Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,377 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrechorus-mediumitalic.otf', name='TeX Gyre Chorus', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,378 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMiao-Regular.ttf', name='Noto Sans Miao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,378 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDinaruLight.ttf', name='UnDinaru', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,379 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/sinhala/lklug.ttf', name='LKLUG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,381 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHanifiRohingya-Bold.ttf', name='Noto Sans Hanifi Rohingya', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,381 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Uroob-Regular.ttf', name='Uroob', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,382 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansInscriptionalPahlavi-Regular.ttf', name='Noto Sans Inscriptional Pahlavi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,382 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-MediumItalic.otf', name='Cabin', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,383 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode-Bold.ttf', name='Junicode', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,383 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifAhom-Regular.ttf', name='Noto Serif Ahom', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,384 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-Italic.ttf', name='Noto Sans Display', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,385 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnVada.ttf', name='UnVada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,386 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoslant10-regular.otf', name='Latin Modern Mono Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,387 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSymbols-Regular.ttf', name='Noto Sans Symbols', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,387 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans9-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,388 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi.ttf', name='Norasi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,388 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-Bold.ttf', name='Carlito', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,389 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenic.otf', name='GFS Neohellenic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,390 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOgham-Regular.ttf', name='Noto Sans Ogham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,391 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGrantha-Regular.ttf', name='Noto Sans Grantha', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,391 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerifItalic.otf', name='FreeSerif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,392 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-bolditalic.otf', name='TeX Gyre Pagella', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,393 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Light.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=300, stretch='condensed', size='scalable')) = 10.344999999999999\n", - "2024-10-29 15:32:58,394 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Karumbi-Regular.ttf', name='Karumbi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,394 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansIndicSiyaqNumbers-Regular.ttf', name='Noto Sans Indic Siyaq Numbers', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,395 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter.ttf', name='Tlwg Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,396 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-Italic.otf', name='P052', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,396 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo-BoldOblique.otf', name='Tlwg Typo', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,397 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsSm-Bold.otf', name='STIXIntegralsSm', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,398 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGujarati-Bold.ttf', name='Noto Serif Gujarati', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,398 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-BoldItalic.ttf', name='Liberation Sans Narrow', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:32:58,399 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansZanabazarSquare-Regular.ttf', name='Noto Sans Zanabazar Square', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,399 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoMusic-Regular.ttf', name='Noto Music', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,400 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-Bold.otf', name='Norasi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,400 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda.ttf', name='Garuda', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,401 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Gubbi/Gubbi.ttf', name='Gubbi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,402 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Bold.ttf', name='Liberation Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,402 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMalayalam-Bold.ttf', name='Noto Serif Malayalam', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,403 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifArmenian-Regular.ttf', name='Noto Serif Armenian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,403 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-AllSC.otf', name='EB Garamond 12 All SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,404 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:32:58,405 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-bkai00mp/bkai00mp.ttf', name='AR PL KaitiM Big5', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,405 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma-BoldOblique.otf', name='Loma', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,406 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyrebonum-math.otf', name='TeX Gyre Bonum Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,406 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-oblique.otf', name='Latin Modern Mono Prop Light', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,407 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman-BoldItalic.ttf', name='Laksaman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,407 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoRashiHebrew-Bold.ttf', name='Noto Rashi Hebrew', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,408 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Italic.ttf', name='Open Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,409 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-Italic.otf', name='Accanthis ADF Std No2', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,412 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMayanNumerals-Regular.ttf', name='Noto Sans Mayan Numerals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,412 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda.otf', name='Garuda', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,413 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBalinese-Bold.ttf', name='Noto Sans Balinese', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,414 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlam-Bold.ttf', name='Noto Sans Adlam', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,415 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnGungseo.ttf', name='UnGungseo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,415 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstDecorative.ttf', name='KacstDecorative', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,416 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstTitle.ttf', name='KacstTitle', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,416 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTibetan-Regular.ttf', name='Noto Serif Tibetan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,417 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-bold.otf', name='TeX Gyre Adventor', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,418 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant12-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,419 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-regular.otf', name='TeX Gyre Schola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,419 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono-Bold.otf', name='Tlwg Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,420 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-regular.otf', name='TeX Gyre Cursor', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,420 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-boldoblique.otf', name='Latin Modern Mono Prop Light', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,421 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoNovel.ttf', name='UnJamoNovel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,421 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-MediumItalic.ttf', name='Roboto', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,422 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-Light.otf', name='Umpush', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,423 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerifBold.otf', name='FreeSerif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,423 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Italic.otf', name='Cabin', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,424 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak-fonts/Samyak-Malayalam.ttf', name='Samyak Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,424 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/TimmanaRegular.ttf', name='Timmana', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525\n", - "2024-10-29 15:32:58,425 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Meera-Regular.ttf', name='Meera', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,425 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPhoenician-Regular.ttf', name='Noto Sans Phoenician', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,426 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_RB.otf', name='Linux Biolinum O', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,427 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-SemiBoldItalic.otf', name='Cabin', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,427 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Light.otf', name='Cantarell', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,428 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-BoldItalic.ttf', name='Gentium Book Plus', style='italic', variant='normal', weight=800, stretch='normal', size='scalable')) = 11.43\n", - "2024-10-29 15:32:58,430 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee-BoldOblique.otf', name='Sawasdee', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,431 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc', name='Noto Sans CJK JP', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,432 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinagh-Regular.ttf', name='Noto Sans Tifinagh', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,433 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-Italic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,433 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidotBoldItalic.otf', name='GFS Didot', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,434 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/GentiumAlt-R.ttf', name='GentiumAlt', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,435 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansEthiopic-Regular.ttf', name='Noto Sans Ethiopic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,435 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Medium.ttf', name='Roboto', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,436 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono-Bold.ttf', name='Go Mono', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,437 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLinearA-Regular.ttf', name='Noto Sans Linear A', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,437 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasBI.ttf', name='Gentium Book Basic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,438 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode.ttf', name='Junicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,438 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/TenaliRamakrishna-Regular.ttf', name='TenaliRamakrishna', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,440 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-regular.otf', name='Latin Modern Mono Prop Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,440 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/mry_KacstQurn.ttf', name='mry_KacstQurn', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,441 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/SreeKrushnadevaraya.ttf', name='Sree Krushnadevaraya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,442 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifBengali-Regular.ttf', name='Noto Serif Bengali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,442 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMath-Regular.ttf', name='Noto Sans Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,443 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansUgaritic-Regular.ttf', name='Noto Sans Ugaritic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,443 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerif.ttf', name='FreeSerif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,445 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-Bold.ttf', name='Arimo', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,445 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasR.ttf', name='Gentium Book Basic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,446 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerifBold.ttf', name='FreeSerif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,447 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-Bold.otf', name='Nimbus Mono PS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,447 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter-BoldOblique.ttf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,448 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-BdIta.otf', name='C059', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,449 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-japanese-gothic.ttf', name='IPAexGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,450 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-Regular.ttf', name='Cousine', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,450 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman12-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,451 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 0.5349999999999999\n", - "2024-10-29 15:32:58,451 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-bold.otf', name='Latin Modern Mono Light', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,452 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-Bold.ttf', name='Liberation Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,452 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-Italic.otf', name='Lobster Two', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,453 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Italic.ttf', name='Roboto', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,454 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-BoldItalic.otf', name='Gillius ADF', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,454 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDuployan-Regular.ttf', name='Noto Sans Duployan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,455 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFProMath-Regular.otf', name='Berenis ADF Pro Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,455 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGeorgian-Regular.ttf', name='Noto Serif Georgian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,456 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,456 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-gkai00mp/gkai00mp.ttf', name='AR PL KaitiM GB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,457 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/MitraMono.ttf', name='Mitra ', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,457 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeOneSym-Regular.otf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,458 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNastaliqUrdu-Bold.ttf', name='Noto Nastaliq Urdu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,461 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-BoldItalic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,461 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono-Italic.ttf', name='Go Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,462 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-BoldItalic.otf', name='Accanthis ADF Std', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,462 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-Bold.ttf', name='Cousine', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,463 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/Rekha.ttf', name='Rekha', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,464 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstDigital.ttf', name='KacstDigital', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,465 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-bold.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,465 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHatran-Regular.ttf', name='Noto Sans Hatran', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,466 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-bolditalic.otf', name='TeX Gyre Adventor', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,467 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnBatang.ttf', name='UnBatang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,467 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansWancho-Regular.ttf', name='Noto Sans Wancho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,468 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-BoldItalic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:32:58,469 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKharoshthi-Regular.ttf', name='Noto Sans Kharoshthi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,470 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAdrar-Regular.ttf', name='Noto Sans Tifinagh Adrar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,470 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpD-Regular.otf', name='STIXIntegralsUpD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,471 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Light.ttf', name='Quicksand Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,471 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-kannada/Lohit-Kannada.ttf', name='Lohit Kannada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,472 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Regular.otf', name='Cabin', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,473 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/solomos/GFSSolomos.otf', name='GFS Solomos', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,473 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Hairline.ttf', name='Lato', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,474 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAnatolianHieroglyphs-Regular.ttf', name='Noto Sans Anatolian Hieroglyphs', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,474 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-BookOblique.otf', name='URW Gothic', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,475 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-bold.otf', name='Latin Modern Sans Quotation', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,476 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Nakula/nakula.ttf', name='Nakula', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,476 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RBI.otf', name='Linux Libertine O', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,477 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNastaliqUrdu-Regular.ttf', name='Noto Nastaliq Urdu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,479 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-Italic.ttf', name='Noto Serif Display', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,479 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-Italic.otf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,480 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTamil-Bold.ttf', name='Noto Sans Tamil', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,481 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghTawellemmet-Regular.ttf', name='Noto Sans Tifinagh Tawellemmet', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,481 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGeorgian-Regular.ttf', name='Noto Sans Georgian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,482 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlamUnjoined-Regular.ttf', name='Noto Sans Adlam Unjoined', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,483 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/hline.ttf', name='Baekmuk Headline', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,484 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree-BoldOblique.otf', name='Waree', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,484 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMonoOblique.otf', name='FreeMono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,485 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-regular.otf', name='TeX Gyre Adventor', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,485 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa-BoldOblique.otf', name='Purisa', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,487 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCham-Bold.ttf', name='Noto Sans Cham', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,487 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee-BoldOblique.ttf', name='Sawasdee', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,488 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-BoldItalic.ttf', name='Tinos', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,489 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-italic.otf', name='TeX Gyre Heros', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,489 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-Bold.ttf', name='Noto Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,490 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-DemiItalic.otf', name='URW Bookman', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,491 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhmer-Bold.ttf', name='Noto Serif Khmer', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,492 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/AmiriQuran.ttf', name='Amiri Quran', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,492 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpSm-Regular.otf', name='STIXIntegralsUpSm', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,493 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTamilSupplement-Regular.ttf', name='Noto Sans Tamil Supplement', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,493 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman-Bold.otf', name='Laksaman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,494 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-italic.otf', name='TeX Gyre Heros Cn', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,495 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenicIt.otf', name='GFS Neohellenic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,495 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSoraSompeng-Bold.ttf', name='Noto Sans Sora Sompeng', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,496 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans17-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,496 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSerifCJK-Regular.ttc', name='Noto Serif CJK JP', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,497 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCoptic-Regular.ttf', name='Noto Sans Coptic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,498 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Thin.ttf', name='Roboto', style='normal', variant='normal', weight=250, stretch='normal', size='scalable')) = 10.1925\n", - "2024-10-29 15:32:58,498 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo-Oblique.otf', name='Tlwg Typo', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,499 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghGhat-Regular.ttf', name='Noto Sans Tifinagh Ghat', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,499 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak-fonts/Samyak-Gujarati.ttf', name='Samyak Gujarati', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,500 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RZI.otf', name='Linux Libertine O', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,502 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo-Oblique.ttf', name='Tlwg Typo', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,503 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-Regular.ttf', name='Liberation Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,503 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamil-Bold.ttf', name='Noto Serif Tamil', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,504 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-Bold.ttf', name='Noto Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,505 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSamaritan-Regular.ttf', name='Noto Sans Samaritan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,506 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond-InitialsF1.otf', name='EB Garamond Initials Fill1', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,506 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter-Oblique.ttf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,507 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/RaghuMalayalamSans-Regular.ttf', name='RaghuMalayalamSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,508 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandunh10-oblique.otf', name='Latin Modern Roman Dunhill', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,508 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush.ttf', name='Umpush', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,509 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,509 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Keraleeyam-Regular.ttf', name='Keraleeyam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,510 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-BoldItalic.otf', name='P052', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,511 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma-Oblique.otf', name='Loma', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,511 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifSinhala-Bold.ttf', name='Noto Serif Sinhala', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,512 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_M.otf', name='Linux Libertine Mono O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,512 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:32:58,514 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-Bold.otf', name='Accanthis ADF Std No2', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,515 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeThreeSym-Bold.otf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,515 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-SemiBold.ttf', name='Yrsa', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,516 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifBengali-Bold.ttf', name='Noto Serif Bengali', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,517 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-R.ttf', name='Ubuntu Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,518 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerifBoldItalic.otf', name='FreeSerif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,518 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda-BoldOblique.otf', name='Garuda', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,519 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman5-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,520 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter-Bold.ttf', name='Tlwg Typewriter', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,521 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-BoldItalic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,521 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-BoldCondItalic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:32:58,522 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhojki-Regular.ttf', name='Noto Serif Khojki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,523 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansJavanese-Regular.ttf', name='Noto Sans Javanese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,523 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Bold.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,524 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma.otf', name='Loma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,524 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBamum-Regular.ttf', name='Noto Sans Bamum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,525 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond-InitialsF1.ttf', name='EB Garamond Initials Fill1', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,525 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/font-awesome/fontawesome-webfont.ttf', name='FontAwesome', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,526 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-bengali/Lohit-Bengali.ttf', name='Lohit Bengali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,526 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstScreen.ttf', name='KacstScreen', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,527 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTelugu-Regular.ttf', name='Noto Sans Telugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,528 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Light.ttf', name='Roboto', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,528 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-boldoblique.otf', name='Latin Modern Sans Quotation', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,529 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhmer-Regular.ttf', name='Noto Sans Khmer', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,529 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Mandali-Regular.ttf', name='Mandali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,530 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Chilanka-Regular.otf', name='Chilanka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,530 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIXMath-Regular.otf', name='STIX Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,531 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-Regular.ttf', name='Liberation Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,531 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Regular.ttf', name='Open Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,532 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-Demi.otf', name='URW Gothic', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,533 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman9-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,533 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf', name='Liberation Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,534 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/comfortaa/Comfortaa-Light.ttf', name='Comfortaa', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,537 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMonoBoldOblique.otf', name='FreeMono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,537 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono-BoldOblique.ttf', name='Tlwg Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,538 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-Oblique.ttf', name='Norasi', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,538 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-DemiOblique.otf', name='URW Gothic', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:32:58,539 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans8-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,539 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman.ttf', name='Laksaman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,540 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/RaviPrakash.ttf', name='RaviPrakash', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,541 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist-Oblique.ttf', name='Tlwg Typist', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,542 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-Italic.otf', name='Norasi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,542 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Regular.ttf', name='Liberation Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,543 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Bold.ttf', name='Yrsa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,543 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-Bold.ttf', name='Amiri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,544 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter-Bold.otf', name='Tlwg Typewriter', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,545 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-Italic.otf', name='STIX', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,545 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,546 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-BoldItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,546 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerifItalic.ttf', name='FreeSerif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,547 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-italic.otf', name='TeX Gyre Cursor', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,547 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsD-Bold.otf', name='STIXIntegralsD', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,548 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Light.ttf', name='Yrsa', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,548 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-Regular.ttf', name='Caladea', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,549 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNewa-Regular.ttf', name='Noto Sans Newa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,550 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-Italic.ttf', name='Tinos', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,550 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnPilgia.ttf', name='UnPilgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,553 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond08-Italic.otf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,553 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSharada-Regular.ttf', name='Noto Sans Sharada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,554 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMyanmar-Bold.ttf', name='Noto Serif Myanmar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,554 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma-Bold.otf', name='Loma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,555 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-deva-extra/kalimati.ttf', name='Kalimati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,555 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/PottiSreeramulu.ttf', name='Potti Sreeramulu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,556 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstFarsi.ttf', name='KacstFarsi', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,557 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeFourSym-Bold.otf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,558 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_R.otf', name='Linux Libertine O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,558 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman.otf', name='Laksaman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,559 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifYezidi-Regular.ttf', name='Noto Serif Yezidi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,560 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/aakar-medium.ttf', name='aakar', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,561 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-Italic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,561 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTelugu-Bold.ttf', name='Noto Serif Telugu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,562 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/AnjaliOldLipi-Regular.ttf', name='AnjaliOldLipi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,563 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-BoldItalic.ttf', name='Charis SIL', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,563 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman6-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,564 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-regular.otf', name='TeX Gyre Heros Cn', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,565 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstQurn.ttf', name='KacstQurn', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,565 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-BoldItalic.ttf', name='Kinnari', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,566 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSinhala-Bold.ttf', name='Noto Sans Sinhala', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,566 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Gayathri-Regular.otf', name='Gayathri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,567 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeOneSym-Bold.otf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,567 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:32:58,568 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono10-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,569 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Cond.otf', name='Gillius ADF', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:32:58,569 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSignWriting-Regular.ttf', name='Noto Sans SignWriting', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,570 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-LightItalic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=300, stretch='condensed', size='scalable')) = 11.344999999999999\n", - "2024-10-29 15:32:58,572 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Gayathri-Bold.otf', name='Gayathri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,572 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCarian-Regular.ttf', name='Noto Sans Carian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,573 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist-BoldOblique.ttf', name='Tlwg Typist', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,573 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-LightItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,574 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGunjalaGondi-Regular.ttf', name='Noto Sans Gunjala Gondi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,574 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-assamese/Lohit-Assamese.ttf', name='Lohit Assamese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,575 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-Italic.ttf', name='Gentium Plus', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,576 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Bold.otf', name='Cabin', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,576 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGurmukhi-Regular.ttf', name='Noto Serif Gurmukhi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,577 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/abyssinica/AbyssinicaSIL-Regular.ttf', name='Abyssinica SIL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,577 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst-one/KacstOne.ttf', name='KacstOne', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,578 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedThai-Bold.ttf', name='Noto Looped Thai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,578 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-oblique.otf', name='Latin Modern Sans Quotation', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,579 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/padmaa-Bold.1.1.ttf', name='padmaa-Bold.1.1', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,581 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoprop10-oblique.otf', name='Latin Modern Mono Prop', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,581 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansChakma-Regular.ttf', name='Noto Sans Chakma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,582 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc', name='Noto Sans CJK JP', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,583 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond08-Italic.ttf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,583 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLimbu-Regular.ttf', name='Noto Sans Limbu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,584 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamil-Regular.ttf', name='Noto Serif Tamil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,584 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-devanagari/Lohit-Devanagari.ttf', name='Lohit Devanagari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,585 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSansBold.ttf', name='FreeSans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,586 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-AllSC.ttf', name='EB Garamond 12 All SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,586 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-mincho/ipam.ttf', name='IPAMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,587 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLao-Bold.ttf', name='Noto Sans Lao', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,587 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiViet-Regular.ttf', name='Noto Sans Tai Viet', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,588 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/font-awesome/FontAwesome.otf', name='FontAwesome', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,588 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMongolian-Regular.ttf', name='Noto Sans Mongolian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,589 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifEthiopic-Bold.ttf', name='Noto Serif Ethiopic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,589 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/LikhanNormal.ttf', name='Likhan', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,590 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSerifCJK-Bold.ttc', name='Noto Serif CJK JP', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,591 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-Bold.otf', name='STIX', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,591 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifNyiakengPuachueHmong-Regular.ttf', name='Noto Serif Hmong Nyiakeng', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,592 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOsage-Regular.ttf', name='Noto Sans Osage', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,592 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-gujarati/Lohit-Gujarati.ttf', name='Lohit Gujarati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,595 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCanadianAboriginal-Regular.ttf', name='Noto Sans Canadian Aboriginal', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,596 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDevanagari-Bold.ttf', name='Noto Serif Devanagari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,596 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-bolditalic.otf', name='TeX Gyre Bonum', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,597 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhojki-Bold.ttf', name='Noto Serif Khojki', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,597 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Gargi/Gargi.ttf', name='Gargi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,598 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/AmiriQuranColored.ttf', name='Amiri Quran Colored', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,599 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot-classic/GFSDidotClassic.otf', name='GFS Didot Classic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,599 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-Regular.otf', name='Accanthis ADF Std No3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,600 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-Bold.ttf', name='Norasi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,600 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-CondBold.ttf', name='Open Sans Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:32:58,601 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-BoldItalic.ttf', name='Cousine', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,601 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda-Bold.ttf', name='Garuda', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,602 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-Italic.ttf', name='Noto Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,603 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKannada-Regular.ttf', name='Noto Serif Kannada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,603 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-Regular.otf', name='Nimbus Sans Narrow', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:32:58,604 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamilSlanted-Regular.ttf', name='Noto Serif Tamil Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,604 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist.ttf', name='Tlwg Typist', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,607 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-Slanted.ttf', name='Amiri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,607 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-RI.ttf', name='Ubuntu', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,608 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo-Bold.ttf', name='Tlwg Typo', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,608 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNKo-Regular.ttf', name='Noto Sans NKo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,609 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnTaza.ttf', name='UnTaza', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,609 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisiaBold.otf', name='GFS Artemisia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,610 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Medium.otf', name='Cabin', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,611 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Italic.ttf', name='Yrsa', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:32:58,611 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-japanese-mincho.ttf', name='IPAexMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,612 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RZ.otf', name='Linux Libertine O', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:32:58,612 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-Bold.ttf', name='Noto Sans Display', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,613 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTamil-Regular.ttf', name='Noto Sans Tamil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,613 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpD-Bold.otf', name='STIXIntegralsUpD', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,614 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenicBold.otf', name='GFS Neohellenic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,615 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTakri-Regular.ttf', name='Noto Sans Takri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,617 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-MediumItalic.ttf', name='Lato', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,617 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifLao-Bold.ttf', name='Noto Serif Lao', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:32:58,618 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-LightItalic.ttf', name='Roboto', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,619 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-BoldItalic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,619 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-Italic.ttf', name='Gentium Book Plus', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:32:58,620 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKayahLi-Regular.ttf', name='Noto Sans Kayah Li', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,621 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-BoldItalic.ttf', name='Carlito', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:32:58,622 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Bold.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:32:58,622 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansWarangCiti-Regular.ttf', name='Noto Sans Warang Citi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,623 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasR.ttf', name='Gentium Basic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:32:58,624 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-Regular.ttf', name='Gentium Book Plus', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:32:58,624 - matplotlib.font_manager - DEBUG - findfont: Matching sans\\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=20.0 to DejaVu Sans ('/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000.\n", - "2024-10-29 15:33:02,009 - matplotlib.font_manager - DEBUG - findfont: Matching sans\\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=18.0.\n", - "2024-10-29 15:33:02,011 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996\n", - "2024-10-29 15:33:02,012 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,013 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,014 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,014 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,015 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,016 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,016 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,017 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,018 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,019 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05\n", - "2024-10-29 15:33:02,020 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,021 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,021 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,022 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,022 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,023 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,024 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,024 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,025 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,026 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,026 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,027 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,027 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,028 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,029 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,029 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,030 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,031 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,033 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335\n", - "2024-10-29 15:33:02,034 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,034 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,035 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05\n", - "2024-10-29 15:33:02,036 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,036 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,037 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,038 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,038 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,039 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-Bold.otf', name='Nimbus Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,039 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-malayalam/Lohit-Malayalam.ttf', name='Lohit Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,040 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramondSC08-Regular.ttf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,041 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Medium.ttf', name='Rasa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,041 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05\n", - "2024-10-29 15:33:02,042 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstTitleL.ttf', name='KacstTitleL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,042 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhojki-Regular.ttf', name='Noto Sans Khojki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,043 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode-BoldItalic.ttf', name='Junicode', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,044 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThaana-Bold.ttf', name='Noto Sans Thaana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,044 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-bold.otf', name='TeX Gyre Pagella', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,045 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGurmukhi-Regular.ttf', name='Noto Sans Gurmukhi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,046 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-Bold.otf', name='C059', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,046 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansShavian-Regular.ttf', name='Noto Sans Shavian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,047 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-BoldOblique.otf', name='Norasi', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,047 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-SemiboldItalic.ttf', name='Lato', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,048 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Black.ttf', name='Roboto', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525\n", - "2024-10-29 15:33:02,049 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa-Bold.ttf', name='Purisa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,049 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-B.ttf', name='Ubuntu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,050 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMultani-Regular.ttf', name='Noto Sans Multani', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,051 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBengali-Regular.ttf', name='Noto Sans Bengali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,051 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi.otf', name='Norasi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,052 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-Italic.ttf', name='Cousine', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,052 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-tamil/Lohit-Tamil.ttf', name='Lohit Tamil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,053 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-Demi.otf', name='URW Bookman', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,054 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-regular.otf', name='TeX Gyre Termes', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,054 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-Regular.otf', name='Accanthis ADF Std', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,055 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono.otf', name='Tlwg Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,056 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-Regular.ttf', name='Tinos', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,056 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCaucasianAlbanian-Regular.ttf', name='Noto Sans Caucasian Albanian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,057 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baskerville/GFSBaskerville.otf', name='GFS Baskerville', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,058 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-MediumItalic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=500, stretch='condensed', size='scalable')) = 11.344999999999999\n", - "2024-10-29 15:33:02,058 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDogra-Regular.ttf', name='Noto Serif Dogra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,059 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-Italic.otf', name='Accanthis ADF Std', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,059 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-bold.otf', name='TeX Gyre Heros', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,060 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Regular.ttf', name='Liberation Sans Narrow', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:02,061 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-BoldItalic.ttf', name='Caladea', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,061 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-BoldOblique.ttf', name='Umpush', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,062 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono12-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,063 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSans.otf', name='FreeSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,063 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansManichaean-Regular.ttf', name='Noto Sans Manichaean', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,064 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-Oblique.otf', name='Umpush', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,064 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,065 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman8-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,066 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNushu-Regular.ttf', name='Noto Sans Nushu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,067 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/Muktibold.ttf', name='Mukti', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,067 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-BoldItalic.otf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,068 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/Gentium-I.ttf', name='Gentium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,069 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist-BoldOblique.otf', name='Tlwg Typist', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,069 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree.ttf', name='Waree', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,070 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHanifiRohingya-Regular.ttf', name='Noto Sans Hanifi Rohingya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,071 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono-BoldOblique.otf', name='Tlwg Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,072 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-BoldItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,072 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/mallanna.ttf', name='Mallanna', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,073 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMandaic-Regular.ttf', name='Noto Sans Mandaic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,073 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-telugu/Lohit-Telugu.ttf', name='Lohit Telugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,074 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa-Oblique.ttf', name='Purisa', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,075 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans17-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,075 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsSm-Regular.otf', name='STIXIntegralsSm', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,076 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-Bold.otf', name='Nimbus Sans Narrow', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:02,077 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMonoOblique.ttf', name='FreeMono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,077 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-bolditalic.otf', name='TeX Gyre Schola', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,078 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-italic.otf', name='TeX Gyre Termes', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,078 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda-Oblique.otf', name='Garuda', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,079 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Gurajada.ttf', name='Gurajada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,080 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhmer-Bold.ttf', name='Noto Sans Khmer', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,080 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCuneiform-Regular.ttf', name='Noto Sans Cuneiform', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,081 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsD-Regular.otf', name='STIXIntegralsD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,082 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-Italic.otf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,082 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-Bold.otf', name='Accanthis ADF Std', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,083 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipaexfont-mincho/ipaexm.ttf', name='IPAexMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,083 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidot.otf', name='GFS Didot', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,084 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono-Oblique.otf', name='Tlwg Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,085 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Bold.ttf', name='Liberation Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,085 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-Regular.ttf', name='Liberation Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,086 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBuhid-Regular.ttf', name='Noto Sans Buhid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,087 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThaana-Regular.ttf', name='Noto Sans Thaana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,088 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-BoldItalic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,089 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedThai-Regular.ttf', name='Noto Looped Thai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,089 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSans.ttf', name='FreeSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,090 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-Oblique.ttf', name='Umpush', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,091 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-regular.otf', name='Latin Modern Mono Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,091 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-LightItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,100 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/StandardSymbolsPS.otf', name='Standard Symbols PS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,101 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/ramabhadra.ttf', name='Ramabhadra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,101 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05\n", - "2024-10-29 15:33:02,102 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-BoldCondIt.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:02,103 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/D050000L.otf', name='D050000L', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,103 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAir-Regular.ttf', name='Noto Sans Tifinagh Air', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,104 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMahajani-Regular.ttf', name='Noto Sans Mahajani', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,104 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-Regular.ttf', name='Carlito', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,105 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansEthiopic-Bold.ttf', name='Noto Sans Ethiopic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,106 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-Regular.otf', name='Nimbus Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,106 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-guru-extra/Saab.ttf', name='Saab', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,107 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,107 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/suranna.ttf', name='Suranna', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,108 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandemi10-oblique.otf', name='Latin Modern Roman Demi', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,108 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifThai-Bold.ttf', name='Noto Serif Thai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,109 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa-Oblique.otf', name='Purisa', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,109 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGujarati-Regular.ttf', name='Noto Sans Gujarati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,110 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Manjari-Bold.otf', name='Manjari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,110 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOlChiki-Regular.ttf', name='Noto Sans Ol Chiki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,111 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-CondItalic.otf', name='Gillius ADF', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:02,111 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-deva-extra/chandas1-2.ttf', name='Chandas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,112 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Bold-Italic.ttf', name='Go', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,113 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-Roman.otf', name='C059', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,113 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_RI.otf', name='Linux Biolinum O', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,114 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-BoldCond.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:02,114 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono8-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,115 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansdemicond10-oblique.otf', name='Latin Modern Sans Demi Cond', style='oblique', variant='normal', weight=600, stretch='condensed', size='scalable')) = 11.44\n", - "2024-10-29 15:33:02,115 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoDotum.ttf', name='UnJamoDotum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,116 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstLetter.ttf', name='KacstLetter', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,116 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-Book.otf', name='URW Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,117 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-boldoblique.otf', name='Latin Modern Mono Light', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,117 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTagalog-Regular.ttf', name='Noto Sans Tagalog', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,118 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifArmenian-Bold.ttf', name='Noto Serif Armenian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,118 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-deva-extra/samanata.ttf', name='Samanata', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,119 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMonoBold.otf', name='FreeMono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,119 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstPen.ttf', name='KacstPen', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,120 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Regular.ttf', name='Roboto', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,120 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans12-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,121 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-Italic.otf', name='Accanthis ADF Std No3', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,122 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSundanese-Bold.ttf', name='Noto Sans Sundanese', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,122 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-MI.ttf', name='Ubuntu', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,123 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBassaVah-Regular.ttf', name='Noto Sans Bassa Vah', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,123 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-Italic.otf', name='C059', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,124 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoTraditionalNushu-Regular.ttf', name='Noto Traditional Nushu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,124 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:02,126 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-LightItalic.otf', name='URW Bookman', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,126 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-LightOblique.otf', name='Umpush', style='oblique', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,127 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-Italic.otf', name='Berenis ADF Pro', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,127 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasI.ttf', name='Gentium Basic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,128 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari.ttf', name='Kinnari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,129 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArabic-Regular.ttf', name='Noto Sans Arabic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,129 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHebrew-Regular.ttf', name='Noto Sans Hebrew', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,130 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-Bold.ttf', name='Gentium Book Plus', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:33:02,130 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant10-bold.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,131 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-Bold.otf', name='Berenis ADF Pro', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,135 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree.otf', name='Waree', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,136 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-Bold.ttf', name='Tinos', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,136 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-C.ttf', name='Ubuntu Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:02,137 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,138 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans9-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,138 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-BoldOblique.ttf', name='Kinnari', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,139 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman5-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,140 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoKufiArabic-Bold.ttf', name='Noto Kufi Arabic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,140 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-Regular.ttf', name='Charis SIL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,141 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlam-Regular.ttf', name='Noto Sans Adlam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,141 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Semibold.ttf', name='Lato', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,142 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansModi-Regular.ttf', name='Noto Sans Modi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,143 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-Italic.otf', name='Nimbus Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,143 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond-Initials.ttf', name='EB Garamond Initials', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,144 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/gulim.ttf', name='Baekmuk Gulim', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,144 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Regular.ttf', name='Go', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,145 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXVariants-Regular.otf', name='STIXVariants', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,145 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoBatang.ttf', name='UnJamoBatang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,146 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTagbanwa-Regular.ttf', name='Noto Sans Tagbanwa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,146 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-SemiBoldItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,147 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-gothic/ipag.ttf', name='IPAGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,149 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-tamil-classical/Lohit-Tamil-Classical.ttf', name='Lohit Tamil Classical', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,149 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeThreeSym-Regular.otf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,150 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeFiveSym-Regular.otf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,150 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSansBoldOblique.ttf', name='FreeSans', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,151 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSylotiNagri-Regular.ttf', name='Noto Sans Syloti Nagri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,152 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramondSC08-Regular.otf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,152 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamilSlanted-Bold.ttf', name='Noto Serif Tamil Slanted', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,153 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Black.ttf', name='Lato', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525\n", - "2024-10-29 15:33:02,153 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAPT-Regular.ttf', name='Noto Sans Tifinagh APT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,154 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond08-Regular.ttf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,154 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisia.otf', name='GFS Artemisia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,155 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee.ttf', name='Sawasdee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,157 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXVariants-Bold.otf', name='STIXVariants', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,157 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLycian-Regular.ttf', name='Noto Sans Lycian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,158 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-LI.ttf', name='Ubuntu', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,158 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman-Italic.ttf', name='Laksaman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,159 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOlChiki-Bold.ttf', name='Noto Sans Ol Chiki', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,159 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-Bold.ttf', name='Caladea', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,160 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Rachana-Regular.ttf', name='Rachana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,160 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Gidugu.ttf', name='Gidugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,161 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoRashiHebrew-Regular.ttf', name='Noto Rashi Hebrew', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,161 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansEgyptianHieroglyphs-Regular.ttf', name='Noto Sans Egyptian Hieroglyphs', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,162 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant8-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,162 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCherokee-Bold.ttf', name='Noto Sans Cherokee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,163 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhmer-Regular.ttf', name='Noto Serif Khmer', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,163 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_DR.otf', name='Linux Libertine Display O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,164 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/bodoni-classic/GFSBodoniClassic.otf', name='GFS BodoniClassic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,165 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-Bold.ttf', name='Umpush', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,165 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 0.25\n", - "2024-10-29 15:33:02,166 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-bold.otf', name='TeX Gyre Termes', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,166 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono10-italic.otf', name='Latin Modern Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,167 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa-Bold.otf', name='Purisa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,167 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman-BoldItalic.otf', name='Laksaman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,168 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Regular.ttf', name='Rasa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,168 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThai-Bold.ttf', name='Noto Sans Thai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,169 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-BoldItalic.otf', name='Nimbus Mono PS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,172 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Semibold.ttf', name='Open Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,172 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Italic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,173 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/LakkiReddy.ttf', name='LakkiReddy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,173 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldPersian-Regular.ttf', name='Noto Sans Old Persian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,174 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-BoldItalic.ttf', name='Noto Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,174 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansElymaic-Regular.ttf', name='Noto Sans Elymaic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,176 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifBalinese-Regular.ttf', name='Noto Serif Balinese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,176 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBrahmi-Regular.ttf', name='Noto Sans Brahmi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,177 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/pagul/Pagul.ttf', name='Pagul', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,177 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/porson/GFSPorson.otf', name='GFS Porson', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,178 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-BoldItalic.otf', name='Cabin', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,178 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKannada-Bold.ttf', name='Noto Sans Kannada', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,179 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-Regular.otf', name='Nimbus Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,179 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMeroitic-Regular.ttf', name='Noto Sans Meroitic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,180 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMalayalam-Regular.ttf', name='Noto Sans Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,181 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansRejang-Regular.ttf', name='Noto Sans Rejang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,181 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansInscriptionalParthian-Regular.ttf', name='Noto Sans Inscriptional Parthian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,182 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Regular.ttf', name='Lato', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,182 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa-BoldOblique.ttf', name='Purisa', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,183 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-BoldOblique.ttf', name='Norasi', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,183 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifYezidi-Bold.ttf', name='Noto Serif Yezidi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,185 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-orya-extra/utkal.ttf', name='ori1Uni', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,186 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-regular.otf', name='TeX Gyre Bonum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,186 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-Bold.otf', name='Lobster Two', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,187 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996\n", - "2024-10-29 15:33:02,187 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKannada-Regular.ttf', name='Noto Sans Kannada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,188 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm-math/latinmodern-math.otf', name='Latin Modern Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,188 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/SyamalaRamana.ttf', name='Syamala Ramana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,189 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Bold.ttf', name='Lato', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,189 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono-Oblique.ttf', name='Tlwg Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,190 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Regular.ttf', name='Liberation Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,190 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-bold.otf', name='Latin Modern Mono Prop Light', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,191 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter-BoldOblique.otf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,192 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist.otf', name='Tlwg Typist', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,192 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-BoldItalic.otf', name='Nimbus Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,193 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-Italic.ttf', name='Norasi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,193 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKayahLi-Bold.ttf', name='Noto Sans Kayah Li', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,194 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-Italic.ttf', name='Arimo', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,194 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLepcha-Regular.ttf', name='Noto Sans Lepcha', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,195 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Medium.ttf', name='Yrsa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,195 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidotBold.otf', name='GFS Didot', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,196 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-BoldItalic.ttf', name='Arimo', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,197 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-BoldItalic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,197 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree-Bold.otf', name='Waree', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,200 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoprop10-regular.otf', name='Latin Modern Mono Prop', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,201 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-italic.otf', name='TeX Gyre Adventor', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,201 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSansOblique.ttf', name='FreeSans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,202 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedLao-Bold.ttf', name='Noto Looped Lao', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,203 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Italic.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,203 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman-Italic.otf', name='Laksaman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,204 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,204 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Medium.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=500, stretch='condensed', size='scalable')) = 10.344999999999999\n", - "2024-10-29 15:33:02,205 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-BoldItalic.otf', name='Norasi', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,206 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Ponnala.ttf', name='Ponnala', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,206 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-bold.otf', name='TeX Gyre Cursor', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,207 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Suravaram.ttf', name='Suravaram', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,207 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-BoldItalic.otf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,208 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree-Bold.ttf', name='Waree', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,208 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-Italic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,210 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_R.otf', name='Linux Biolinum O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,210 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/Z003-MediumItalic.otf', name='Z003', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,211 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Thin.ttf', name='Lato', style='normal', variant='normal', weight=200, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,211 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-Regular.otf', name='Accanthis ADF Std No2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,212 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/glyphicons/glyphicons-halflings-regular.ttf', name='GLYPHICONS Halflings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,212 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee-Bold.otf', name='Sawasdee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,213 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansdemicond10-regular.otf', name='Latin Modern Sans Demi Cond', style='normal', variant='normal', weight=600, stretch='condensed', size='scalable')) = 10.44\n", - "2024-10-29 15:33:02,213 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTibetan-Bold.ttf', name='Noto Serif Tibetan', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,214 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-Bold.ttf', name='Kinnari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,215 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMono.otf', name='FreeMono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,215 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-BI.ttf', name='Ubuntu', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,216 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPalmyrene-Regular.ttf', name='Noto Sans Palmyrene', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,216 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-Oblique.ttf', name='Kinnari', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,217 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/theokritos/GFSTheokritos.otf', name='GFS Theokritos', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,217 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLao-Regular.ttf', name='Noto Sans Lao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,218 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCham-Regular.ttf', name='Noto Sans Cham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,221 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGurmukhi-Bold.ttf', name='Noto Serif Gurmukhi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,222 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTangut-Regular.ttf', name='Noto Serif Tangut', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,222 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Smallcaps-Italic.ttf', name='Go Smallcaps', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,223 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSymbols2-Regular.ttf', name='Noto Sans Symbols2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,223 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Heavy.ttf', name='Lato', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:33:02,224 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond-InitialsF2.ttf', name='EB Garamond Initials Fill2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,225 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-bolditalic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,225 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-Oblique.otf', name='Kinnari', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,226 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifHebrew-Regular.ttf', name='Noto Serif Hebrew', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,226 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans12-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,227 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Italic.ttf', name='Liberation Sans Narrow', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:02,227 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMeeteiMayek-Regular.ttf', name='Noto Sans Meetei Mayek', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,228 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMono-Regular.ttf', name='Noto Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,228 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifNyiakengPuachueHmong-Bold.ttf', name='Noto Serif Hmong Nyiakeng', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,229 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lao/Phetsarath_OT.ttf', name='Phetsarath OT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,230 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-Bold.otf', name='Nimbus Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,234 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldNorthArabian-Regular.ttf', name='Noto Sans Old North Arabian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,234 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-regular.otf', name='Latin Modern Sans Quotation', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,235 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifThai-Regular.ttf', name='Noto Serif Thai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,235 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGujarati-Regular.ttf', name='Noto Serif Gujarati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,236 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoKufiArabic-Regular.ttf', name='Noto Kufi Arabic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,237 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-Italic.otf', name='Nimbus Mono PS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,238 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ttf-khmeros-core/KhmerOSsys.ttf', name='Khmer OS System', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,238 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-Regular.otf', name='Lobster Two', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,239 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnPilgiBold.ttf', name='UnPilgi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,239 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMendeKikakui-Regular.ttf', name='Noto Sans Mende Kikakui', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,240 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Cond.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:02,240 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMro-Regular.ttf', name='Noto Sans Mro', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,241 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKannada-Bold.ttf', name='Noto Serif Kannada', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,242 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-M.ttf', name='Ubuntu', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,243 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoltcond10-regular.otf', name='Latin Modern Mono Light Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:02,243 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-Bold.otf', name='Kinnari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,244 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-Italic.otf', name='Nimbus Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,245 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Italic.ttf', name='Go', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,246 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus-compact/GentiumPlusCompact-I.ttf', name='Gentium Plus Compact', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,246 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-Light.otf', name='URW Bookman', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,247 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNaskhArabic-Bold.ttf', name='Noto Naskh Arabic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,247 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansElbasan-Regular.ttf', name='Noto Sans Elbasan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,248 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramondSC12-Regular.otf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,248 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Light.ttf', name='Rasa', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,249 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-BoldItalic.ttf', name='Noto Sans Display', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,250 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-Italic.ttf', name='Noto Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,251 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMono.ttf', name='FreeMono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,251 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Regular.ttf', name='Quicksand', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,252 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/comfortaa/Comfortaa-Bold.ttf', name='Comfortaa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,252 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,254 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-Regular.otf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,254 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-Bold.otf', name='P052', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,255 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/PadaukBook-Regular.ttf', name='Padauk Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,255 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromancaps10-regular.otf', name='Latin Modern Roman Caps', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,256 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak-fonts/Samyak-Tamil.ttf', name='Samyak Tamil', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,256 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-ExtraBold.otf', name='Cantarell', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:33:02,258 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma-Bold.ttf', name='Loma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,258 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman17-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,259 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond-InitialsF2.otf', name='EB Garamond Initials Fill2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,259 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-BoldOblique.otf', name='Kinnari', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,260 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-BoldItalic.ttf', name='Lato', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,261 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOriya-Bold.ttf', name='Noto Sans Oriya', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,262 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-Italic.otf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,262 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCypriot-Regular.ttf', name='Noto Sans Cypriot', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,263 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCherokee-Regular.ttf', name='Noto Sans Cherokee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,263 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-Light.ttf', name='Umpush', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,264 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeTwoSym-Bold.otf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,265 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-BlackItalic.ttf', name='Roboto', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525\n", - "2024-10-29 15:33:02,265 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma.ttf', name='Loma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,266 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMedefaidrin-Bold.ttf', name='Noto Sans Medefaidrin', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,266 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnGraphicBold.ttf', name='UnGraphic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,268 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-BoldCondItalic.otf', name='Gillius ADF', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:02,269 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSansBold.otf', name='FreeSans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,269 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnYetgul.ttf', name='UnYetgul', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,270 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-regular.otf', name='TeX Gyre Pagella', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,270 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,271 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-BoldItalic.otf', name='Kinnari', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,272 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCanadianAboriginal-Bold.ttf', name='Noto Sans Canadian Aboriginal', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,272 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSaurashtra-Regular.ttf', name='Noto Sans Saurashtra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,273 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArmenian-Regular.ttf', name='Noto Sans Armenian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,273 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/complutum/GFSPolyglot.otf', name='GFS Complutum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,274 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhudawadi-Regular.ttf', name='Noto Sans Khudawadi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,275 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSansOblique.otf', name='FreeSans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,275 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGurmukhi-Bold.ttf', name='Noto Sans Gurmukhi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,276 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-bold.otf', name='TeX Gyre Bonum', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,276 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldSogdian-Regular.ttf', name='Noto Sans Old Sogdian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,277 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoMono-Regular.ttf', name='Noto Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,279 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/olga/GFSOlga.otf', name='GFS Olga', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,280 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,280 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-ExtraLight.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=200, stretch='normal', size='scalable')) = 0.24\n", - "2024-10-29 15:33:02,281 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-ThinItalic.ttf', name='Lato', style='italic', variant='normal', weight=200, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,282 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/Mukti.ttf', name='Mukti', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,283 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-Bold.ttf', name='Charis SIL', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,284 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-punjabi/Lohit-Gurmukhi.ttf', name='Lohit Gurmukhi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,284 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda-Bold.otf', name='Garuda', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,285 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDinaru.ttf', name='UnDinaru', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,285 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman8-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,287 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifEthiopic-Regular.ttf', name='Noto Serif Ethiopic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,287 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono9-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,288 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Medium.ttf', name='Go Medium', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,288 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Regular.ttf', name='Yrsa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,289 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-R.ttf', name='Ubuntu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,290 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/NATS.ttf', name='NATS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,290 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Bold.ttf', name='Open Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,291 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-Oblique.otf', name='Norasi', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,291 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDevanagari-Regular.ttf', name='Noto Sans Devanagari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,293 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoltcond10-oblique.otf', name='Latin Modern Mono Light Cond', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:02,294 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-Regular.ttf', name='Noto Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,294 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Medium.ttf', name='Lato', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,295 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-BoldItalic.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,295 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTelugu-Regular.ttf', name='Noto Serif Telugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,296 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMalayalam-Bold.ttf', name='Noto Sans Malayalam', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,297 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Italic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,298 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-BoldOblique.otf', name='Nimbus Sans Narrow', style='oblique', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:02,298 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_K.otf', name='Linux Biolinum Keyboard O', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,299 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-bsmi00lp/bsmi00lp.ttf', name='AR PL Mingti2L Big5', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,299 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDevanagari-Bold.ttf', name='Noto Sans Devanagari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,301 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSansBoldOblique.otf', name='FreeSans', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,301 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNaskhArabic-Regular.ttf', name='Noto Naskh Arabic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,302 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMonoBold.ttf', name='FreeMono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,303 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstArt.ttf', name='KacstArt', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,303 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansVai-Regular.ttf', name='Noto Sans Vai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,304 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-italic.otf', name='TeX Gyre Pagella', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,305 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman9-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,306 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghHawad-Regular.ttf', name='Noto Sans Tifinagh Hawad', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,306 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/padmaa-Medium-0.5.ttf', name='padmaa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,307 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-HairlineItalic.ttf', name='Lato', style='italic', variant='normal', weight=100, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,307 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBalinese-Regular.ttf', name='Noto Sans Balinese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,308 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/gazis/GFSGazis.otf', name='GFS Gazis', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,309 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-Bold.otf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,310 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-bold.otf', name='TeX Gyre Schola', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,311 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansYi-Regular.ttf', name='Noto Sans Yi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,312 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpSm-Bold.otf', name='STIXIntegralsUpSm', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,313 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Bold.ttf', name='Go', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,313 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/Gentium-R.ttf', name='Gentium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,314 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman6-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,315 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMasaramGondi-Regular.ttf', name='Noto Sans Masaram Gondi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,315 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='condensed', size='scalable')) = 1.535\n", - "2024-10-29 15:33:02,316 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Gayathri-Thin.otf', name='Gayathri', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,316 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-Oblique.otf', name='Nimbus Sans Narrow', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:02,318 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Italic.ttf', name='Lato', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,319 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisiaIt.otf', name='GFS Artemisia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,319 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGeorgian-Bold.ttf', name='Noto Sans Georgian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,320 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda-BoldOblique.ttf', name='Garuda', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,320 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-Regular.ttf', name='Noto Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,321 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPauCinHau-Regular.ttf', name='Noto Sans Pau Cin Hau', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,321 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSiddham-Regular.ttf', name='Noto Sans Siddham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,322 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-kalapi/Kalapi.ttf', name='Kalapi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,323 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-L.ttf', name='Ubuntu', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,324 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedLao-Regular.ttf', name='Noto Looped Lao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,325 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/batang.ttf', name='Baekmuk Batang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,326 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-Bold.ttf', name='Liberation Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,327 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Suruma.ttf', name='Suruma', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,327 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/comfortaa/Comfortaa-Regular.ttf', name='Comfortaa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,328 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-oblique.otf', name='Latin Modern Mono Light', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,329 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman7-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,330 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUp-Bold.otf', name='STIXIntegralsUp', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,330 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-Bold.otf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,331 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSundanese-Regular.ttf', name='Noto Sans Sundanese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,332 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSoyombo-Regular.ttf', name='Noto Sans Soyombo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,332 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasBI.ttf', name='Gentium Basic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,333 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman-Bold.ttf', name='Laksaman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,334 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-bold.otf', name='TeX Gyre Heros Cn', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,334 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMonoBoldOblique.ttf', name='FreeMono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,335 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-Bold.ttf', name='Noto Serif Display', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,335 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode-Italic.ttf', name='Junicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,337 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono-Bold.ttf', name='Tlwg Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,337 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnBatangBold.ttf', name='UnBatang', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,338 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-bolditalic.otf', name='TeX Gyre Heros Cn', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,339 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Manjari-Regular.otf', name='Manjari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,340 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGujarati-Bold.ttf', name='Noto Sans Gujarati', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,340 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-BoldItalic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,341 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman7-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,341 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-CondItalic.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:02,342 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMarchen-Regular.ttf', name='Noto Sans Marchen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,343 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghRhissaIxa-Regular.ttf', name='Noto Sans Tifinagh Rhissa Ixa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,344 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman9-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,344 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSoraSompeng-Regular.ttf', name='Noto Sans Sora Sompeng', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,345 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDevanagari-Regular.ttf', name='Noto Serif Devanagari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,346 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/padmaa.ttf', name='padmaa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,347 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,347 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono.ttf', name='Go Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,348 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-bolditalic.otf', name='TeX Gyre Termes', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,349 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond-Initials.otf', name='EB Garamond Initials', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,349 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-BoldItalic.ttf', name='Roboto', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,350 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-Regular.otf', name='STIX', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,350 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist-Oblique.otf', name='Tlwg Typist', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,351 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-Bold.ttf', name='Gentium Plus', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,351 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Bold.ttf', name='Roboto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,352 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/FoulisGreek.ttf', name='FoulisGreek', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,352 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Italic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,353 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Smallcaps.ttf', name='Go Smallcaps', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,354 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGeorgian-Bold.ttf', name='Noto Serif Georgian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,354 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo-Bold.otf', name='Tlwg Typo', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,355 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Italic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:02,355 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKaithi-Regular.ttf', name='Noto Sans Kaithi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,356 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Dyuthi-Regular.ttf', name='Dyuthi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,356 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda-Oblique.ttf', name='Garuda', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,357 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-SemiBold.otf', name='Cabin', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,357 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-mincho/ipamp.ttf', name='IPAPMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,358 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Regular.otf', name='Gillius ADF', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,359 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Regular.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:02,359 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThai-Regular.ttf', name='Noto Sans Thai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,360 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLydian-Regular.ttf', name='Noto Sans Lydian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,360 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Light.ttf', name='Open Sans', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,361 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyretermes-math.otf', name='TeX Gyre Termes Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,361 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenicBoldIt.otf', name='GFS Neohellenic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,362 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Regular.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,362 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa.ttf', name='Purisa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,363 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBatak-Regular.ttf', name='Noto Sans Batak', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,364 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipaexfont-gothic/ipaexg.ttf', name='IPAexGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,364 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGrantha-Regular.ttf', name='Noto Serif Grantha', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,365 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Bold.ttf', name='Rasa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,365 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-BoldItalic.ttf', name='Norasi', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,366 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree-Oblique.ttf', name='Waree', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,366 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldItalic-Regular.ttf', name='Noto Sans Old Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,367 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDotum.ttf', name='UnDotum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,367 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOsmanya-Regular.ttf', name='Noto Sans Osmanya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,368 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-B.ttf', name='Ubuntu Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,368 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnPilgi.ttf', name='UnPilgi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,369 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RB.otf', name='Linux Libertine O', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,375 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Medium.ttf', name='Quicksand Medium', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,376 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoSora.ttf', name='UnJamoSora', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,376 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Manjari-Thin.otf', name='Manjari', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,377 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifSinhala-Regular.ttf', name='Noto Serif Sinhala', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,377 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifHebrew-Bold.ttf', name='Noto Serif Hebrew', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,378 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDinaruBold.ttf', name='UnDinaru', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,378 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArmenian-Bold.ttf', name='Noto Sans Armenian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,379 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Regular.ttf', name='Liberation Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,379 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee-Bold.ttf', name='Sawasdee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,380 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-SemiBold.ttf', name='Rasa', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,380 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-Regular.ttf', name='Amiri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,381 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-Italic.ttf', name='Charis SIL', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,382 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBhaiksuki-Regular.ttf', name='Noto Sans Bhaiksuki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,384 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma-BoldOblique.ttf', name='Loma', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,384 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSymbols-Bold.ttf', name='Noto Sans Symbols', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,385 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter.otf', name='Tlwg Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,386 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-BoldCond.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:02,386 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyreschola-math.otf', name='TeX Gyre Schola Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,387 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-CondItalic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:02,387 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree-BoldOblique.ttf', name='Waree', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,388 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSogdian-Regular.ttf', name='Noto Sans Sogdian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,388 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans8-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,389 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee-Oblique.ttf', name='Sawasdee', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,391 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak/Samyak-Devanagari.ttf', name='Samyak Devanagari', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,392 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Italic.otf', name='Gillius ADF', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,392 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAgrawImazighen-Regular.ttf', name='Noto Sans Tifinagh Agraw Imazighen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,393 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-Bold.ttf', name='EB Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,393 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-RI.ttf', name='Ubuntu Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,394 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-italic.otf', name='TeX Gyre Schola', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,394 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/PadaukBook-Bold.ttf', name='Padauk Book', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,395 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNabataean-Regular.ttf', name='Noto Sans Nabataean', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,395 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush.otf', name='Umpush', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,396 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/dhurjati.ttf', name='Dhurjati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,396 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGlagolitic-Regular.ttf', name='Noto Sans Glagolitic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,397 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGothic-Regular.ttf', name='Noto Sans Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,399 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-Italic.ttf', name='Kinnari', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,400 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree-Oblique.otf', name='Waree', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,400 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnPenheulim.ttf', name='UnPenheulim', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,401 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMyanmar-Regular.ttf', name='Noto Serif Myanmar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,401 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-Regular.ttf', name='Noto Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,402 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasI.ttf', name='Gentium Book Basic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,403 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerifBoldItalic.ttf', name='FreeSerif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,403 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanunsl10-regular.otf', name='Latin Modern Roman Unslanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,404 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-BoldItalic.ttf', name='Noto Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,404 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-ThinItalic.ttf', name='Roboto', style='italic', variant='normal', weight=250, stretch='normal', size='scalable')) = 11.1925\n", - "2024-10-29 15:33:02,405 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifLao-Regular.ttf', name='Noto Serif Lao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,405 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-telu-extra/Pothana2000.ttf', name='Pothana2000', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,406 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-Bold.otf', name='Umpush', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,407 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Sarai/Sarai.ttf', name='Sarai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,407 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-SemiboldItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,408 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldHungarian-Regular.ttf', name='Noto Sans Old Hungarian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,408 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMyanmar-Regular.ttf', name='Noto Sans Myanmar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,409 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-gbsn00lp/gbsn00lp.ttf', name='AR PL SungtiL GB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,409 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldPermic-Regular.ttf', name='Noto Sans Old Permic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,410 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Bold.ttf', name='Liberation Sans Narrow', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:02,410 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldSouthArabian-Regular.ttf', name='Noto Sans Old South Arabian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,411 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnGraphic.ttf', name='UnGraphic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,412 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandemi10-regular.otf', name='Latin Modern Roman Demi', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,412 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Bold.otf', name='Cantarell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,413 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-BoldCond.otf', name='Gillius ADF', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:02,417 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuMathTeXGyre.ttf', name='DejaVu Math TeX Gyre', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,417 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman7-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,418 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOriya-Regular.ttf', name='Noto Sans Oriya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,418 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSyriac-Regular.ttf', name='Noto Sans Syriac', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,419 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLisu-Regular.ttf', name='Noto Sans Lisu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,420 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-BoldItalic.ttf', name='Noto Serif Display', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,420 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAhaggar-Regular.ttf', name='Noto Sans Tifinagh Ahaggar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,421 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RI.otf', name='Linux Libertine O', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,421 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMeeteiMayek-Bold.ttf', name='Noto Sans Meetei Mayek', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,422 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansRunic-Regular.ttf', name='Noto Sans Runic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,422 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-gothic/ipagp.ttf', name='IPAPGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,423 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBengali-Bold.ttf', name='Noto Sans Bengali', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,424 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic/uming.ttc', name='AR PL UMing CN', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,424 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-BoldOblique.otf', name='Umpush', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,426 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-italic.otf', name='TeX Gyre Bonum', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,427 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasB.ttf', name='Gentium Basic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,428 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPahawhHmong-Regular.ttf', name='Noto Sans Pahawh Hmong', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,428 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-Italic.ttf', name='Caladea', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,429 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAzawagh-Regular.ttf', name='Noto Sans Tifinagh Azawagh', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,430 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Regular.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,431 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/NTR.ttf', name='NTR', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,431 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiTham-Bold.ttf', name='Noto Sans Tai Tham', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,432 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstNaskh.ttf', name='KacstNaskh', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,433 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant10-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,433 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Ramaraja-Regular.ttf', name='Ramaraja', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,434 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo-BoldOblique.ttf', name='Tlwg Typo', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,434 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-BoldItalic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,435 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond08-Regular.otf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,436 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiLe-Regular.ttf', name='Noto Sans Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,436 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-BoldItalic.otf', name='Nimbus Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,437 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-LightOblique.ttf', name='Umpush', style='oblique', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,437 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Regular.otf', name='Cantarell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,438 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonocaps10-oblique.otf', name='Latin Modern Mono Caps', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,439 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman12-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,439 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Cond.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:02,440 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-Th.ttf', name='Ubuntu', style='normal', variant='normal', weight=250, stretch='normal', size='scalable')) = 10.1925\n", - "2024-10-29 15:33:02,440 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-BlackItalic.ttf', name='Lato', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525\n", - "2024-10-29 15:33:02,441 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/libreoffice/opens___.ttf', name='OpenSymbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,442 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 1.25\n", - "2024-10-29 15:33:02,442 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Light.ttf', name='Lato', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,443 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstOffice.ttf', name='KacstOffice', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,443 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Medium-Italic.ttf', name='Go Medium', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,444 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTirhuta-Regular.ttf', name='Noto Sans Tirhuta', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,444 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa.otf', name='Purisa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,445 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeFourSym-Regular.otf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,446 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Thin.otf', name='Cantarell', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,446 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-Bold.otf', name='Accanthis ADF Std No3', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,447 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono-Bold-Italic.ttf', name='Go Mono', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,447 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,448 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Sahadeva/sahadeva.ttf', name='Sahadeva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,448 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-Regular.otf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,449 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/asana-math/Asana-Math.otf', name='Asana Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,449 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Bold.otf', name='Gillius ADF', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,450 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNewTaiLue-Regular.ttf', name='Noto Sans New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,450 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerif.otf', name='FreeSerif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,451 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghSIL-Regular.ttf', name='Noto Sans Tifinagh SIL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,452 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-CondLight.ttf', name='Open Sans', style='normal', variant='normal', weight=300, stretch='condensed', size='scalable')) = 10.344999999999999\n", - "2024-10-29 15:33:02,452 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-LightItalic.ttf', name='Lato', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,453 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidotItalic.otf', name='GFS Didot', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,453 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-ExtraBoldItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=800, stretch='normal', size='scalable')) = 11.43\n", - "2024-10-29 15:33:02,454 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-BoldSlanted.ttf', name='Amiri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,455 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDeseret-Regular.ttf', name='Noto Sans Deseret', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,460 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-telu-extra/vemana2000.ttf', name='Vemana2000', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,461 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPsalterPahlavi-Regular.ttf', name='Noto Sans Psalter Pahlavi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,461 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiTham-Regular.ttf', name='Noto Sans Tai Tham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,462 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandunh10-regular.otf', name='Latin Modern Roman Dunhill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,463 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstBook.ttf', name='KacstBook', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,463 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBamum-Bold.ttf', name='Noto Sans Bamum', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,464 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMedefaidrin-Regular.ttf', name='Noto Sans Medefaidrin', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,465 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee-Oblique.otf', name='Sawasdee', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,465 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-oriya/Lohit-Odia.ttf', name='Lohit Odia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,466 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMyanmar-Bold.ttf', name='Noto Sans Myanmar', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,466 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-Regular.otf', name='Berenis ADF Pro', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,467 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/GentiumAlt-I.ttf', name='GentiumAlt', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,467 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee.otf', name='Sawasdee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,468 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramondSC12-Regular.ttf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,469 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-Italic.ttf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,469 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-Regular.ttf', name='Gentium Plus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,470 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-regular.otf', name='TeX Gyre Heros', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,470 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Rachana-Bold.ttf', name='Rachana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,471 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/Padauk-Bold.ttf', name='Padauk', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,473 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-BI.ttf', name='Ubuntu Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,474 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeTwoSym-Regular.otf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,475 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter-Oblique.otf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,475 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist-Bold.ttf', name='Tlwg Typist', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,476 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstPoster.ttf', name='KacstPoster', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,476 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma-Oblique.ttf', name='Loma', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,477 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisiaBoldIt.otf', name='GFS Didot', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,477 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlamUnjoined-Bold.ttf', name='Noto Sans Adlam Unjoined', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,478 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant17-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,479 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPhagsPa-Regular.ttf', name='Noto Sans PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,479 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-BoldItalic.otf', name='Berenis ADF Pro', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,480 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Bold.ttf', name='Quicksand', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,480 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-Regular.ttf', name='Arimo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,481 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Navilu/Navilu.ttf', name='Navilu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,481 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Italic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,482 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldTurkic-Regular.ttf', name='Noto Sans Old Turkic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,485 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-Bold.ttf', name='Liberation Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,485 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDotumBold.ttf', name='UnDotum', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,486 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHebrew-Bold.ttf', name='Noto Sans Hebrew', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,486 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUp-Regular.otf', name='STIXIntegralsUp', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,487 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-ExtraBold.ttf', name='Open Sans', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:33:02,488 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-Regular.ttf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,488 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonocaps10-regular.otf', name='Latin Modern Mono Caps', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,489 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/dotum.ttf', name='Baekmuk Dotum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,489 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_I.otf', name='Linux Libertine Initials O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,490 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-BoldItalic.otf', name='Accanthis ADF Std No3', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,491 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-Italic.ttf', name='Carlito', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,491 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-bolditalic.otf', name='TeX Gyre Cursor', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,493 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tibetan-machine/TibetanMachineUni.ttf', name='Tibetan Machine Uni', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,494 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-CondLightItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=300, stretch='condensed', size='scalable')) = 11.344999999999999\n", - "2024-10-29 15:33:02,494 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobster/lobster.otf', name='Lobster Two', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,495 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-MediumItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,496 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/droid/DroidSansFallbackFull.ttf', name='Droid Sans Fallback', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,497 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-BoldItalic.ttf', name='Gentium Plus', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,497 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-HeavyItalic.ttf', name='Lato', style='italic', variant='normal', weight=800, stretch='normal', size='scalable')) = 11.43\n", - "2024-10-29 15:33:02,498 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/Ani.ttf', name='Ani', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,499 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAvestan-Regular.ttf', name='Noto Sans Avestan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,499 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Peddana-Regular.ttf', name='Peddana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,500 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,500 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMalayalam-Regular.ttf', name='Noto Serif Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,501 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono.ttf', name='Tlwg Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,502 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyredejavu-math.otf', name='TeX Gyre DejaVu Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,503 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-BoldItalic.otf', name='Lobster Two', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,504 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLinearB-Regular.ttf', name='Noto Sans Linear B', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,504 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-Regular.otf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,505 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-bolditalic.otf', name='TeX Gyre Heros', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,505 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo.otf', name='Tlwg Typo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,506 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335\n", - "2024-10-29 15:33:02,507 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/Padauk-Regular.ttf', name='Padauk', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,507 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst-one/KacstOne-Bold.ttf', name='KacstOne', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,508 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansJavanese-Bold.ttf', name='Noto Sans Javanese', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,508 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman12-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,509 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBuginese-Regular.ttf', name='Noto Sans Buginese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,510 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-Regular.otf', name='Nimbus Mono PS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,510 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-Regular.ttf', name='Noto Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,511 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-boldoblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,511 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Bold.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,512 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant9-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,513 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnPen.ttf', name='UnPen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,513 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSinhala-Regular.ttf', name='Noto Sans Sinhala', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,514 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-Bold.otf', name='EB Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,514 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTelugu-Bold.ttf', name='Noto Sans Telugu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,515 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHanunoo-Regular.ttf', name='Noto Sans Hanunoo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,515 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ttf-khmeros-core/KhmerOS.ttf', name='Khmer OS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,516 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMono-Bold.ttf', name='Noto Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,517 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnShinmun.ttf', name='UnShinmun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,520 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-BoldItalic.otf', name='Accanthis ADF Std No2', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,521 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLisu-Bold.ttf', name='Noto Sans Lisu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,521 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasB.ttf', name='Gentium Book Basic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,522 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus-compact/GentiumPlusCompact-R.ttf', name='Gentium Plus Compact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,522 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/JamrulNormal.ttf', name='Jamrul', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,523 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari.otf', name='Kinnari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,523 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-BoldItalic.otf', name='STIX', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,524 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman8-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,524 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-Roman.otf', name='P052', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,525 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromancaps10-oblique.otf', name='Latin Modern Roman Caps', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,526 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo.ttf', name='Tlwg Typo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,526 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-Italic.otf', name='Kinnari', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,527 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist-Bold.otf', name='Tlwg Typist', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,527 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansImperialAramaic-Regular.ttf', name='Noto Sans Imperial Aramaic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,528 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArabic-Bold.ttf', name='Noto Sans Arabic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,528 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyrepagella-math.otf', name='TeX Gyre Pagella Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,529 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrechorus-mediumitalic.otf', name='TeX Gyre Chorus', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,530 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMiao-Regular.ttf', name='Noto Sans Miao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,530 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDinaruLight.ttf', name='UnDinaru', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,531 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/sinhala/lklug.ttf', name='LKLUG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,531 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHanifiRohingya-Bold.ttf', name='Noto Sans Hanifi Rohingya', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,532 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Uroob-Regular.ttf', name='Uroob', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,532 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansInscriptionalPahlavi-Regular.ttf', name='Noto Sans Inscriptional Pahlavi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,533 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-MediumItalic.otf', name='Cabin', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,537 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode-Bold.ttf', name='Junicode', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,537 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifAhom-Regular.ttf', name='Noto Serif Ahom', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,538 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-Italic.ttf', name='Noto Sans Display', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,538 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnVada.ttf', name='UnVada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,539 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoslant10-regular.otf', name='Latin Modern Mono Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,540 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSymbols-Regular.ttf', name='Noto Sans Symbols', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,540 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans9-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,541 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi.ttf', name='Norasi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,541 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-Bold.ttf', name='Carlito', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,542 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenic.otf', name='GFS Neohellenic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,544 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOgham-Regular.ttf', name='Noto Sans Ogham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,544 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGrantha-Regular.ttf', name='Noto Sans Grantha', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,545 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerifItalic.otf', name='FreeSerif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,545 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-bolditalic.otf', name='TeX Gyre Pagella', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,546 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Light.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=300, stretch='condensed', size='scalable')) = 10.344999999999999\n", - "2024-10-29 15:33:02,547 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Karumbi-Regular.ttf', name='Karumbi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,547 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansIndicSiyaqNumbers-Regular.ttf', name='Noto Sans Indic Siyaq Numbers', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,548 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter.ttf', name='Tlwg Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,548 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-Italic.otf', name='P052', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,549 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo-BoldOblique.otf', name='Tlwg Typo', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,549 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsSm-Bold.otf', name='STIXIntegralsSm', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,550 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGujarati-Bold.ttf', name='Noto Serif Gujarati', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,551 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-BoldItalic.ttf', name='Liberation Sans Narrow', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:02,553 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansZanabazarSquare-Regular.ttf', name='Noto Sans Zanabazar Square', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,553 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoMusic-Regular.ttf', name='Noto Music', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,554 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-Bold.otf', name='Norasi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,555 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda.ttf', name='Garuda', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,555 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Gubbi/Gubbi.ttf', name='Gubbi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,556 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Bold.ttf', name='Liberation Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,557 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMalayalam-Bold.ttf', name='Noto Serif Malayalam', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,557 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifArmenian-Regular.ttf', name='Noto Serif Armenian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,558 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-AllSC.otf', name='EB Garamond 12 All SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,558 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:02,559 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-bkai00mp/bkai00mp.ttf', name='AR PL KaitiM Big5', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,559 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma-BoldOblique.otf', name='Loma', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,560 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyrebonum-math.otf', name='TeX Gyre Bonum Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,560 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-oblique.otf', name='Latin Modern Mono Prop Light', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,561 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman-BoldItalic.ttf', name='Laksaman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,562 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoRashiHebrew-Bold.ttf', name='Noto Rashi Hebrew', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,562 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Italic.ttf', name='Open Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,563 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-Italic.otf', name='Accanthis ADF Std No2', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,563 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMayanNumerals-Regular.ttf', name='Noto Sans Mayan Numerals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,564 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda.otf', name='Garuda', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,564 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBalinese-Bold.ttf', name='Noto Sans Balinese', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,565 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlam-Bold.ttf', name='Noto Sans Adlam', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,565 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnGungseo.ttf', name='UnGungseo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,566 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstDecorative.ttf', name='KacstDecorative', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,570 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstTitle.ttf', name='KacstTitle', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,571 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTibetan-Regular.ttf', name='Noto Serif Tibetan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,571 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-bold.otf', name='TeX Gyre Adventor', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,572 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant12-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,572 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-regular.otf', name='TeX Gyre Schola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,573 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono-Bold.otf', name='Tlwg Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,573 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-regular.otf', name='TeX Gyre Cursor', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,574 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-boldoblique.otf', name='Latin Modern Mono Prop Light', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,575 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoNovel.ttf', name='UnJamoNovel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,576 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-MediumItalic.ttf', name='Roboto', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,577 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-Light.otf', name='Umpush', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,577 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerifBold.otf', name='FreeSerif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,579 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Italic.otf', name='Cabin', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,579 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak-fonts/Samyak-Malayalam.ttf', name='Samyak Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,580 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/TimmanaRegular.ttf', name='Timmana', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525\n", - "2024-10-29 15:33:02,580 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Meera-Regular.ttf', name='Meera', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,581 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPhoenician-Regular.ttf', name='Noto Sans Phoenician', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,581 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_RB.otf', name='Linux Biolinum O', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,582 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-SemiBoldItalic.otf', name='Cabin', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,582 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Light.otf', name='Cantarell', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,583 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-BoldItalic.ttf', name='Gentium Book Plus', style='italic', variant='normal', weight=800, stretch='normal', size='scalable')) = 11.43\n", - "2024-10-29 15:33:02,584 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee-BoldOblique.otf', name='Sawasdee', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,584 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc', name='Noto Sans CJK JP', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,585 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinagh-Regular.ttf', name='Noto Sans Tifinagh', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,585 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-Italic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,586 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidotBoldItalic.otf', name='GFS Didot', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,587 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/GentiumAlt-R.ttf', name='GentiumAlt', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,587 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansEthiopic-Regular.ttf', name='Noto Sans Ethiopic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,590 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Medium.ttf', name='Roboto', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,591 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono-Bold.ttf', name='Go Mono', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,591 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLinearA-Regular.ttf', name='Noto Sans Linear A', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,592 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasBI.ttf', name='Gentium Book Basic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,592 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode.ttf', name='Junicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,593 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/TenaliRamakrishna-Regular.ttf', name='TenaliRamakrishna', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,594 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-regular.otf', name='Latin Modern Mono Prop Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,594 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/mry_KacstQurn.ttf', name='mry_KacstQurn', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,595 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/SreeKrushnadevaraya.ttf', name='Sree Krushnadevaraya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,596 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifBengali-Regular.ttf', name='Noto Serif Bengali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,597 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMath-Regular.ttf', name='Noto Sans Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,597 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansUgaritic-Regular.ttf', name='Noto Sans Ugaritic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,598 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerif.ttf', name='FreeSerif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,599 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-Bold.ttf', name='Arimo', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,599 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasR.ttf', name='Gentium Book Basic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,600 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerifBold.ttf', name='FreeSerif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,600 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-Bold.otf', name='Nimbus Mono PS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,601 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter-BoldOblique.ttf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,602 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-BdIta.otf', name='C059', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,602 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-japanese-gothic.ttf', name='IPAexGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,603 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-Regular.ttf', name='Cousine', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,603 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman12-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,604 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 0.5349999999999999\n", - "2024-10-29 15:33:02,604 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-bold.otf', name='Latin Modern Mono Light', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,605 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-Bold.ttf', name='Liberation Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,605 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-Italic.otf', name='Lobster Two', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,606 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Italic.ttf', name='Roboto', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,607 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-BoldItalic.otf', name='Gillius ADF', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,607 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDuployan-Regular.ttf', name='Noto Sans Duployan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,608 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFProMath-Regular.otf', name='Berenis ADF Pro Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,608 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGeorgian-Regular.ttf', name='Noto Serif Georgian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,609 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,609 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-gkai00mp/gkai00mp.ttf', name='AR PL KaitiM GB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,610 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/MitraMono.ttf', name='Mitra ', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,610 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeOneSym-Regular.otf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,611 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNastaliqUrdu-Bold.ttf', name='Noto Nastaliq Urdu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,611 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-BoldItalic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,616 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono-Italic.ttf', name='Go Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,616 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-BoldItalic.otf', name='Accanthis ADF Std', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,617 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-Bold.ttf', name='Cousine', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,618 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/Rekha.ttf', name='Rekha', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,618 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstDigital.ttf', name='KacstDigital', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,619 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-bold.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,619 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHatran-Regular.ttf', name='Noto Sans Hatran', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,620 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-bolditalic.otf', name='TeX Gyre Adventor', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,620 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnBatang.ttf', name='UnBatang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,621 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansWancho-Regular.ttf', name='Noto Sans Wancho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,622 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-BoldItalic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:02,622 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKharoshthi-Regular.ttf', name='Noto Sans Kharoshthi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,623 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAdrar-Regular.ttf', name='Noto Sans Tifinagh Adrar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,625 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpD-Regular.otf', name='STIXIntegralsUpD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,626 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Light.ttf', name='Quicksand Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,626 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-kannada/Lohit-Kannada.ttf', name='Lohit Kannada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,627 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Regular.otf', name='Cabin', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,627 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/solomos/GFSSolomos.otf', name='GFS Solomos', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,628 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Hairline.ttf', name='Lato', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,629 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAnatolianHieroglyphs-Regular.ttf', name='Noto Sans Anatolian Hieroglyphs', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,630 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-BookOblique.otf', name='URW Gothic', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,631 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-bold.otf', name='Latin Modern Sans Quotation', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,631 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Nakula/nakula.ttf', name='Nakula', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,632 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RBI.otf', name='Linux Libertine O', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,632 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNastaliqUrdu-Regular.ttf', name='Noto Nastaliq Urdu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,633 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-Italic.ttf', name='Noto Serif Display', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,634 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-Italic.otf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,635 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTamil-Bold.ttf', name='Noto Sans Tamil', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,636 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghTawellemmet-Regular.ttf', name='Noto Sans Tifinagh Tawellemmet', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,636 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGeorgian-Regular.ttf', name='Noto Sans Georgian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,637 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlamUnjoined-Regular.ttf', name='Noto Sans Adlam Unjoined', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,638 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/hline.ttf', name='Baekmuk Headline', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,638 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree-BoldOblique.otf', name='Waree', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,639 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMonoOblique.otf', name='FreeMono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,639 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-regular.otf', name='TeX Gyre Adventor', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,640 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa-BoldOblique.otf', name='Purisa', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,640 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCham-Bold.ttf', name='Noto Sans Cham', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,642 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee-BoldOblique.ttf', name='Sawasdee', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,643 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-BoldItalic.ttf', name='Tinos', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,643 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-italic.otf', name='TeX Gyre Heros', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,644 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-Bold.ttf', name='Noto Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,644 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-DemiItalic.otf', name='URW Bookman', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,645 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhmer-Bold.ttf', name='Noto Serif Khmer', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,645 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/AmiriQuran.ttf', name='Amiri Quran', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,647 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpSm-Regular.otf', name='STIXIntegralsUpSm', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,647 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTamilSupplement-Regular.ttf', name='Noto Sans Tamil Supplement', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,648 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman-Bold.otf', name='Laksaman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,649 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-italic.otf', name='TeX Gyre Heros Cn', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,650 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenicIt.otf', name='GFS Neohellenic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,650 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSoraSompeng-Bold.ttf', name='Noto Sans Sora Sompeng', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,651 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans17-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,651 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSerifCJK-Regular.ttc', name='Noto Serif CJK JP', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,652 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCoptic-Regular.ttf', name='Noto Sans Coptic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,653 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Thin.ttf', name='Roboto', style='normal', variant='normal', weight=250, stretch='normal', size='scalable')) = 10.1925\n", - "2024-10-29 15:33:02,654 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo-Oblique.otf', name='Tlwg Typo', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,654 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghGhat-Regular.ttf', name='Noto Sans Tifinagh Ghat', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,655 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak-fonts/Samyak-Gujarati.ttf', name='Samyak Gujarati', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,656 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RZI.otf', name='Linux Libertine O', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,657 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo-Oblique.ttf', name='Tlwg Typo', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,657 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-Regular.ttf', name='Liberation Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,658 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamil-Bold.ttf', name='Noto Serif Tamil', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,659 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-Bold.ttf', name='Noto Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,659 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSamaritan-Regular.ttf', name='Noto Sans Samaritan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,660 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond-InitialsF1.otf', name='EB Garamond Initials Fill1', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,661 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter-Oblique.ttf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,662 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/RaghuMalayalamSans-Regular.ttf', name='RaghuMalayalamSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,662 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandunh10-oblique.otf', name='Latin Modern Roman Dunhill', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,663 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush.ttf', name='Umpush', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,664 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,664 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Keraleeyam-Regular.ttf', name='Keraleeyam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,665 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-BoldItalic.otf', name='P052', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,666 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma-Oblique.otf', name='Loma', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,667 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifSinhala-Bold.ttf', name='Noto Serif Sinhala', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,667 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_M.otf', name='Linux Libertine Mono O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,668 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:02,669 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-Bold.otf', name='Accanthis ADF Std No2', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,669 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeThreeSym-Bold.otf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,670 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-SemiBold.ttf', name='Yrsa', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,671 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifBengali-Bold.ttf', name='Noto Serif Bengali', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,671 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-R.ttf', name='Ubuntu Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,672 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerifBoldItalic.otf', name='FreeSerif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,672 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda-BoldOblique.otf', name='Garuda', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,673 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman5-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,674 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter-Bold.ttf', name='Tlwg Typewriter', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,674 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-BoldItalic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,675 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-BoldCondItalic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:02,675 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhojki-Regular.ttf', name='Noto Serif Khojki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,677 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansJavanese-Regular.ttf', name='Noto Sans Javanese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,678 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Bold.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,678 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma.otf', name='Loma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,679 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBamum-Regular.ttf', name='Noto Sans Bamum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,680 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond-InitialsF1.ttf', name='EB Garamond Initials Fill1', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,680 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/font-awesome/fontawesome-webfont.ttf', name='FontAwesome', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,681 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-bengali/Lohit-Bengali.ttf', name='Lohit Bengali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,681 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstScreen.ttf', name='KacstScreen', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,682 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTelugu-Regular.ttf', name='Noto Sans Telugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,684 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Light.ttf', name='Roboto', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,684 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-boldoblique.otf', name='Latin Modern Sans Quotation', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,685 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhmer-Regular.ttf', name='Noto Sans Khmer', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,685 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Mandali-Regular.ttf', name='Mandali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,686 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Chilanka-Regular.otf', name='Chilanka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,686 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIXMath-Regular.otf', name='STIX Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,687 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-Regular.ttf', name='Liberation Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,687 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Regular.ttf', name='Open Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,689 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-Demi.otf', name='URW Gothic', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,690 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman9-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,690 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf', name='Liberation Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,691 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/comfortaa/Comfortaa-Light.ttf', name='Comfortaa', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,691 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMonoBoldOblique.otf', name='FreeMono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,692 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono-BoldOblique.ttf', name='Tlwg Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,693 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-Oblique.ttf', name='Norasi', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,694 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-DemiOblique.otf', name='URW Gothic', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:02,695 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans8-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,695 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman.ttf', name='Laksaman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,696 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/RaviPrakash.ttf', name='RaviPrakash', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,697 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist-Oblique.ttf', name='Tlwg Typist', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,697 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-Italic.otf', name='Norasi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,698 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Regular.ttf', name='Liberation Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,699 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Bold.ttf', name='Yrsa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,699 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-Bold.ttf', name='Amiri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,700 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter-Bold.otf', name='Tlwg Typewriter', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,700 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-Italic.otf', name='STIX', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,701 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,702 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-BoldItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,703 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerifItalic.ttf', name='FreeSerif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,704 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-italic.otf', name='TeX Gyre Cursor', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,704 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsD-Bold.otf', name='STIXIntegralsD', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,705 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Light.ttf', name='Yrsa', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,706 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-Regular.ttf', name='Caladea', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,707 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNewa-Regular.ttf', name='Noto Sans Newa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,707 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-Italic.ttf', name='Tinos', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,708 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnPilgia.ttf', name='UnPilgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,709 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond08-Italic.otf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,709 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSharada-Regular.ttf', name='Noto Sans Sharada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,710 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMyanmar-Bold.ttf', name='Noto Serif Myanmar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,711 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma-Bold.otf', name='Loma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,712 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-deva-extra/kalimati.ttf', name='Kalimati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,712 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/PottiSreeramulu.ttf', name='Potti Sreeramulu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,713 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstFarsi.ttf', name='KacstFarsi', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,713 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeFourSym-Bold.otf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,714 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_R.otf', name='Linux Libertine O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,715 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman.otf', name='Laksaman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,715 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifYezidi-Regular.ttf', name='Noto Serif Yezidi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,716 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/aakar-medium.ttf', name='aakar', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,716 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-Italic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,717 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTelugu-Bold.ttf', name='Noto Serif Telugu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,718 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/AnjaliOldLipi-Regular.ttf', name='AnjaliOldLipi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,718 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-BoldItalic.ttf', name='Charis SIL', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,719 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman6-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,719 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-regular.otf', name='TeX Gyre Heros Cn', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,722 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstQurn.ttf', name='KacstQurn', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,722 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-BoldItalic.ttf', name='Kinnari', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,723 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSinhala-Bold.ttf', name='Noto Sans Sinhala', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,724 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Gayathri-Regular.otf', name='Gayathri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,724 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeOneSym-Bold.otf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,725 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:02,726 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono10-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,727 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Cond.otf', name='Gillius ADF', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:02,727 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSignWriting-Regular.ttf', name='Noto Sans SignWriting', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,728 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-LightItalic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=300, stretch='condensed', size='scalable')) = 11.344999999999999\n", - "2024-10-29 15:33:02,728 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Gayathri-Bold.otf', name='Gayathri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,729 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCarian-Regular.ttf', name='Noto Sans Carian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,729 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist-BoldOblique.ttf', name='Tlwg Typist', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,730 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-LightItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,730 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGunjalaGondi-Regular.ttf', name='Noto Sans Gunjala Gondi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,731 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-assamese/Lohit-Assamese.ttf', name='Lohit Assamese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,732 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-Italic.ttf', name='Gentium Plus', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,732 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Bold.otf', name='Cabin', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,733 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGurmukhi-Regular.ttf', name='Noto Serif Gurmukhi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,733 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/abyssinica/AbyssinicaSIL-Regular.ttf', name='Abyssinica SIL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,734 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst-one/KacstOne.ttf', name='KacstOne', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,735 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedThai-Bold.ttf', name='Noto Looped Thai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,735 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-oblique.otf', name='Latin Modern Sans Quotation', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,736 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/padmaa-Bold.1.1.ttf', name='padmaa-Bold.1.1', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,736 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoprop10-oblique.otf', name='Latin Modern Mono Prop', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,737 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansChakma-Regular.ttf', name='Noto Sans Chakma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,737 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc', name='Noto Sans CJK JP', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,740 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond08-Italic.ttf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,741 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLimbu-Regular.ttf', name='Noto Sans Limbu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,741 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamil-Regular.ttf', name='Noto Serif Tamil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,742 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-devanagari/Lohit-Devanagari.ttf', name='Lohit Devanagari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,742 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSansBold.ttf', name='FreeSans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,743 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-AllSC.ttf', name='EB Garamond 12 All SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,744 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-mincho/ipam.ttf', name='IPAMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,745 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLao-Bold.ttf', name='Noto Sans Lao', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,746 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiViet-Regular.ttf', name='Noto Sans Tai Viet', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,747 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/font-awesome/FontAwesome.otf', name='FontAwesome', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,747 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMongolian-Regular.ttf', name='Noto Sans Mongolian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,748 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifEthiopic-Bold.ttf', name='Noto Serif Ethiopic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,749 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/LikhanNormal.ttf', name='Likhan', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,750 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSerifCJK-Bold.ttc', name='Noto Serif CJK JP', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,750 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-Bold.otf', name='STIX', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,751 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifNyiakengPuachueHmong-Regular.ttf', name='Noto Serif Hmong Nyiakeng', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,752 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOsage-Regular.ttf', name='Noto Sans Osage', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,752 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-gujarati/Lohit-Gujarati.ttf', name='Lohit Gujarati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,753 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCanadianAboriginal-Regular.ttf', name='Noto Sans Canadian Aboriginal', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,754 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDevanagari-Bold.ttf', name='Noto Serif Devanagari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,754 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-bolditalic.otf', name='TeX Gyre Bonum', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,755 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhojki-Bold.ttf', name='Noto Serif Khojki', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,756 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Gargi/Gargi.ttf', name='Gargi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,757 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/AmiriQuranColored.ttf', name='Amiri Quran Colored', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,757 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot-classic/GFSDidotClassic.otf', name='GFS Didot Classic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,758 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-Regular.otf', name='Accanthis ADF Std No3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,759 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-Bold.ttf', name='Norasi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,759 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-CondBold.ttf', name='Open Sans Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:02,760 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-BoldItalic.ttf', name='Cousine', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,760 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda-Bold.ttf', name='Garuda', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,762 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-Italic.ttf', name='Noto Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,762 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKannada-Regular.ttf', name='Noto Serif Kannada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,763 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-Regular.otf', name='Nimbus Sans Narrow', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:02,763 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamilSlanted-Regular.ttf', name='Noto Serif Tamil Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,764 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist.ttf', name='Tlwg Typist', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,764 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-Slanted.ttf', name='Amiri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,765 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-RI.ttf', name='Ubuntu', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,765 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo-Bold.ttf', name='Tlwg Typo', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,767 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNKo-Regular.ttf', name='Noto Sans NKo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,768 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnTaza.ttf', name='UnTaza', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,768 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisiaBold.otf', name='GFS Artemisia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,769 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Medium.otf', name='Cabin', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,769 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Italic.ttf', name='Yrsa', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:02,770 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-japanese-mincho.ttf', name='IPAexMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,771 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RZ.otf', name='Linux Libertine O', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:02,771 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-Bold.ttf', name='Noto Sans Display', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,772 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTamil-Regular.ttf', name='Noto Sans Tamil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,772 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpD-Bold.otf', name='STIXIntegralsUpD', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,773 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenicBold.otf', name='GFS Neohellenic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,773 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTakri-Regular.ttf', name='Noto Sans Takri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,774 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-MediumItalic.ttf', name='Lato', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,774 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifLao-Bold.ttf', name='Noto Serif Lao', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:02,775 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-LightItalic.ttf', name='Roboto', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,777 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-BoldItalic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,778 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-Italic.ttf', name='Gentium Book Plus', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:02,778 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKayahLi-Regular.ttf', name='Noto Sans Kayah Li', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,779 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-BoldItalic.ttf', name='Carlito', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:02,780 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Bold.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:02,781 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansWarangCiti-Regular.ttf', name='Noto Sans Warang Citi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,781 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasR.ttf', name='Gentium Basic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:02,782 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-Regular.ttf', name='Gentium Book Plus', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:02,783 - matplotlib.font_manager - DEBUG - findfont: Matching sans\\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=18.0 to DejaVu Sans ('/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000.\n", - "2024-10-29 15:33:04,208 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig1_exp_dict/CorrQuantification_pept_act_sum_filter_by_im_log_fdr_0.2_log_int_2.png\n", - "2024-10-29 15:33:07,900 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig1_exp_dict/CorrQuantification_pept_act_sum_filter_by_im_log_fdr_0.2_log_int_2.svg\n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from result_analysis import result_analysis\n", - "\n", - "pept_act_sum_df = pd.read_csv(os.path.join(act_dir, \"pept_act_sum.csv\"))\n", - "infer_int_col = \"pept_act_sum\"\n", - "# TODO: fix im filter config\n", - "if cfg.RESULT_ANALYSIS.POST_PROCESSING.FILTER_BY_IM:\n", - " pept_act_sum_filter_by_im_df = pd.read_csv(\n", - " os.path.join(act_dir, \"pept_act_sum_filter_by_im.csv\")\n", - " )\n", - " # pept_act_sum_filter_by_im_df = pept_act_sum_filter_by_im_df.rename(\n", - " # {\"sum_intensity\": \"sum_intensity_filter_by_im\"}, axis=1\n", - " # )\n", - " pept_act_sum_df = pd.merge(\n", - " left=pept_act_sum_df,\n", - " right=pept_act_sum_filter_by_im_df,\n", - " on=[\"mz_rank\"],\n", - " how=\"left\",\n", - " suffixes=(\"\", \"_filter_by_im\"),\n", - " )\n", - " #infer_int_col = \"pept_act_sum_filter_by_im\"\n", - " infer_int_col = \"pept_act_sum_filter_by_im\"\n", - "\n", - "\n", - "swaps_result = result_analysis.SWAPSResult(\n", - " maxquant_dict=maxquant_result_ref,\n", - " pept_act_sum_df=pept_act_sum_filter_by_im_df,\n", - " infer_intensity_col=infer_int_col,\n", - " fdr_thres=cfg.RESULT_ANALYSIS.FDR_THRESHOLD,\n", - " log_sum_intensity_thres=cfg.RESULT_ANALYSIS.LOG_SUM_INTENSITY_THRESHOLD,\n", - " save_dir=eval_dir,\n", - " include_decoys=cfg.PREPARE_DICT.GENERATE_DECOY,\n", - ")\n", - "swaps_result.plot_intensity_corr(title=None, show_diag=False, font_size=20,\n", - " line_width=2)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 15:33:08,117 - matplotlib.font_manager - DEBUG - findfont: Matching sans\\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=24.0.\n", - "2024-10-29 15:33:08,118 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996\n", - "2024-10-29 15:33:08,119 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,119 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,120 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,120 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,121 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,122 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,122 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,123 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,123 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,124 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05\n", - "2024-10-29 15:33:08,124 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,125 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,125 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,125 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,126 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,126 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,127 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,127 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,128 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,128 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,129 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,129 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,130 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,130 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,131 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,131 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,131 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,132 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,132 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335\n", - "2024-10-29 15:33:08,133 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,133 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,134 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05\n", - "2024-10-29 15:33:08,134 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,135 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,135 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,136 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,136 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,136 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-Bold.otf', name='Nimbus Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,137 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-malayalam/Lohit-Malayalam.ttf', name='Lohit Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,137 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramondSC08-Regular.ttf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,138 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Medium.ttf', name='Rasa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,138 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05\n", - "2024-10-29 15:33:08,139 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstTitleL.ttf', name='KacstTitleL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,139 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhojki-Regular.ttf', name='Noto Sans Khojki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,140 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode-BoldItalic.ttf', name='Junicode', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,140 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThaana-Bold.ttf', name='Noto Sans Thaana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,141 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-bold.otf', name='TeX Gyre Pagella', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,141 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGurmukhi-Regular.ttf', name='Noto Sans Gurmukhi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,142 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-Bold.otf', name='C059', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,142 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansShavian-Regular.ttf', name='Noto Sans Shavian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,143 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-BoldOblique.otf', name='Norasi', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,143 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-SemiboldItalic.ttf', name='Lato', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,144 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Black.ttf', name='Roboto', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525\n", - "2024-10-29 15:33:08,144 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa-Bold.ttf', name='Purisa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,144 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-B.ttf', name='Ubuntu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,145 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMultani-Regular.ttf', name='Noto Sans Multani', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,145 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBengali-Regular.ttf', name='Noto Sans Bengali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,146 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi.otf', name='Norasi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,146 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-Italic.ttf', name='Cousine', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,147 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-tamil/Lohit-Tamil.ttf', name='Lohit Tamil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,147 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-Demi.otf', name='URW Bookman', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,148 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-regular.otf', name='TeX Gyre Termes', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,148 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-Regular.otf', name='Accanthis ADF Std', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,149 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono.otf', name='Tlwg Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,149 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-Regular.ttf', name='Tinos', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,150 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCaucasianAlbanian-Regular.ttf', name='Noto Sans Caucasian Albanian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,150 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baskerville/GFSBaskerville.otf', name='GFS Baskerville', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,150 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-MediumItalic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=500, stretch='condensed', size='scalable')) = 11.344999999999999\n", - "2024-10-29 15:33:08,151 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDogra-Regular.ttf', name='Noto Serif Dogra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,151 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-Italic.otf', name='Accanthis ADF Std', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,152 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-bold.otf', name='TeX Gyre Heros', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,152 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Regular.ttf', name='Liberation Sans Narrow', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:08,153 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-BoldItalic.ttf', name='Caladea', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,153 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-BoldOblique.ttf', name='Umpush', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,154 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono12-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,154 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSans.otf', name='FreeSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,155 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansManichaean-Regular.ttf', name='Noto Sans Manichaean', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,155 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-Oblique.otf', name='Umpush', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,155 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,156 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman8-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,156 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNushu-Regular.ttf', name='Noto Sans Nushu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,157 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/Muktibold.ttf', name='Mukti', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,157 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-BoldItalic.otf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,158 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/Gentium-I.ttf', name='Gentium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,158 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist-BoldOblique.otf', name='Tlwg Typist', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,159 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree.ttf', name='Waree', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,159 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHanifiRohingya-Regular.ttf', name='Noto Sans Hanifi Rohingya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,160 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono-BoldOblique.otf', name='Tlwg Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,160 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-BoldItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,160 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/mallanna.ttf', name='Mallanna', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,161 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMandaic-Regular.ttf', name='Noto Sans Mandaic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,161 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-telugu/Lohit-Telugu.ttf', name='Lohit Telugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,162 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa-Oblique.ttf', name='Purisa', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,162 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans17-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,163 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsSm-Regular.otf', name='STIXIntegralsSm', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,163 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-Bold.otf', name='Nimbus Sans Narrow', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:08,164 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMonoOblique.ttf', name='FreeMono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,164 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-bolditalic.otf', name='TeX Gyre Schola', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,165 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-italic.otf', name='TeX Gyre Termes', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,165 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda-Oblique.otf', name='Garuda', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,165 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Gurajada.ttf', name='Gurajada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,166 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhmer-Bold.ttf', name='Noto Sans Khmer', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,166 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCuneiform-Regular.ttf', name='Noto Sans Cuneiform', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,167 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsD-Regular.otf', name='STIXIntegralsD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,167 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-Italic.otf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,168 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-Bold.otf', name='Accanthis ADF Std', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,168 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipaexfont-mincho/ipaexm.ttf', name='IPAexMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,169 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidot.otf', name='GFS Didot', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,169 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono-Oblique.otf', name='Tlwg Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,170 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Bold.ttf', name='Liberation Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,170 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-Regular.ttf', name='Liberation Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,171 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBuhid-Regular.ttf', name='Noto Sans Buhid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,171 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThaana-Regular.ttf', name='Noto Sans Thaana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,171 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-BoldItalic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,172 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedThai-Regular.ttf', name='Noto Looped Thai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,172 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSans.ttf', name='FreeSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,173 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-Oblique.ttf', name='Umpush', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,173 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-regular.otf', name='Latin Modern Mono Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,174 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-LightItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,174 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/StandardSymbolsPS.otf', name='Standard Symbols PS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,175 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/ramabhadra.ttf', name='Ramabhadra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,175 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05\n", - "2024-10-29 15:33:08,176 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-BoldCondIt.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:08,176 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/D050000L.otf', name='D050000L', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,177 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAir-Regular.ttf', name='Noto Sans Tifinagh Air', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,177 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMahajani-Regular.ttf', name='Noto Sans Mahajani', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,177 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-Regular.ttf', name='Carlito', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,178 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansEthiopic-Bold.ttf', name='Noto Sans Ethiopic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,178 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-Regular.otf', name='Nimbus Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,179 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-guru-extra/Saab.ttf', name='Saab', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,179 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,180 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/suranna.ttf', name='Suranna', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,180 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandemi10-oblique.otf', name='Latin Modern Roman Demi', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,181 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifThai-Bold.ttf', name='Noto Serif Thai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,181 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa-Oblique.otf', name='Purisa', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,182 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGujarati-Regular.ttf', name='Noto Sans Gujarati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,182 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Manjari-Bold.otf', name='Manjari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,182 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOlChiki-Regular.ttf', name='Noto Sans Ol Chiki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,183 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-CondItalic.otf', name='Gillius ADF', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:08,183 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-deva-extra/chandas1-2.ttf', name='Chandas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,184 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Bold-Italic.ttf', name='Go', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,184 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-Roman.otf', name='C059', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,185 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_RI.otf', name='Linux Biolinum O', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,185 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-BoldCond.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:08,186 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono8-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,186 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansdemicond10-oblique.otf', name='Latin Modern Sans Demi Cond', style='oblique', variant='normal', weight=600, stretch='condensed', size='scalable')) = 11.44\n", - "2024-10-29 15:33:08,187 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoDotum.ttf', name='UnJamoDotum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,187 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstLetter.ttf', name='KacstLetter', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,187 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-Book.otf', name='URW Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,188 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-boldoblique.otf', name='Latin Modern Mono Light', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,188 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTagalog-Regular.ttf', name='Noto Sans Tagalog', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,189 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifArmenian-Bold.ttf', name='Noto Serif Armenian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,189 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-deva-extra/samanata.ttf', name='Samanata', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,190 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMonoBold.otf', name='FreeMono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,190 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstPen.ttf', name='KacstPen', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,191 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Regular.ttf', name='Roboto', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,191 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans12-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,192 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-Italic.otf', name='Accanthis ADF Std No3', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,192 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSundanese-Bold.ttf', name='Noto Sans Sundanese', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,193 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-MI.ttf', name='Ubuntu', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,193 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBassaVah-Regular.ttf', name='Noto Sans Bassa Vah', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,193 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-Italic.otf', name='C059', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,194 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoTraditionalNushu-Regular.ttf', name='Noto Traditional Nushu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,194 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:08,195 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-LightItalic.otf', name='URW Bookman', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,195 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-LightOblique.otf', name='Umpush', style='oblique', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,196 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-Italic.otf', name='Berenis ADF Pro', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,196 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasI.ttf', name='Gentium Basic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,197 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari.ttf', name='Kinnari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,197 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArabic-Regular.ttf', name='Noto Sans Arabic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,198 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHebrew-Regular.ttf', name='Noto Sans Hebrew', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,198 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-Bold.ttf', name='Gentium Book Plus', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:33:08,199 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant10-bold.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,199 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-Bold.otf', name='Berenis ADF Pro', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,199 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree.otf', name='Waree', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,200 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-Bold.ttf', name='Tinos', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,200 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-C.ttf', name='Ubuntu Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:08,201 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,201 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans9-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,202 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-BoldOblique.ttf', name='Kinnari', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,202 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman5-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,203 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoKufiArabic-Bold.ttf', name='Noto Kufi Arabic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,203 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-Regular.ttf', name='Charis SIL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,204 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlam-Regular.ttf', name='Noto Sans Adlam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,204 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Semibold.ttf', name='Lato', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,205 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansModi-Regular.ttf', name='Noto Sans Modi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,205 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-Italic.otf', name='Nimbus Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,206 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond-Initials.ttf', name='EB Garamond Initials', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,206 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/gulim.ttf', name='Baekmuk Gulim', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,207 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Regular.ttf', name='Go', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,207 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXVariants-Regular.otf', name='STIXVariants', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,207 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoBatang.ttf', name='UnJamoBatang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,208 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTagbanwa-Regular.ttf', name='Noto Sans Tagbanwa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,208 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-SemiBoldItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,209 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-gothic/ipag.ttf', name='IPAGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,209 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-tamil-classical/Lohit-Tamil-Classical.ttf', name='Lohit Tamil Classical', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,210 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeThreeSym-Regular.otf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,210 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeFiveSym-Regular.otf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,211 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSansBoldOblique.ttf', name='FreeSans', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,211 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSylotiNagri-Regular.ttf', name='Noto Sans Syloti Nagri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,212 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramondSC08-Regular.otf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,212 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamilSlanted-Bold.ttf', name='Noto Serif Tamil Slanted', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,212 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Black.ttf', name='Lato', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525\n", - "2024-10-29 15:33:08,213 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAPT-Regular.ttf', name='Noto Sans Tifinagh APT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,213 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond08-Regular.ttf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,214 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisia.otf', name='GFS Artemisia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,214 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee.ttf', name='Sawasdee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,215 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXVariants-Bold.otf', name='STIXVariants', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,215 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLycian-Regular.ttf', name='Noto Sans Lycian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,216 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-LI.ttf', name='Ubuntu', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,216 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman-Italic.ttf', name='Laksaman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,217 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOlChiki-Bold.ttf', name='Noto Sans Ol Chiki', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,217 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-Bold.ttf', name='Caladea', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,217 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Rachana-Regular.ttf', name='Rachana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,218 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Gidugu.ttf', name='Gidugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,218 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoRashiHebrew-Regular.ttf', name='Noto Rashi Hebrew', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,219 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansEgyptianHieroglyphs-Regular.ttf', name='Noto Sans Egyptian Hieroglyphs', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,219 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant8-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,220 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCherokee-Bold.ttf', name='Noto Sans Cherokee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,220 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhmer-Regular.ttf', name='Noto Serif Khmer', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,221 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_DR.otf', name='Linux Libertine Display O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,221 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/bodoni-classic/GFSBodoniClassic.otf', name='GFS BodoniClassic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,222 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-Bold.ttf', name='Umpush', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,222 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 0.25\n", - "2024-10-29 15:33:08,223 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-bold.otf', name='TeX Gyre Termes', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,223 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono10-italic.otf', name='Latin Modern Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,223 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa-Bold.otf', name='Purisa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,224 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman-BoldItalic.otf', name='Laksaman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,224 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Regular.ttf', name='Rasa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,225 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThai-Bold.ttf', name='Noto Sans Thai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,225 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-BoldItalic.otf', name='Nimbus Mono PS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,226 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Semibold.ttf', name='Open Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,226 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Italic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,227 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/LakkiReddy.ttf', name='LakkiReddy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,227 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldPersian-Regular.ttf', name='Noto Sans Old Persian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,228 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-BoldItalic.ttf', name='Noto Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,228 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansElymaic-Regular.ttf', name='Noto Sans Elymaic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,228 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifBalinese-Regular.ttf', name='Noto Serif Balinese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,229 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBrahmi-Regular.ttf', name='Noto Sans Brahmi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,229 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/pagul/Pagul.ttf', name='Pagul', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,230 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/porson/GFSPorson.otf', name='GFS Porson', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,230 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-BoldItalic.otf', name='Cabin', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,231 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKannada-Bold.ttf', name='Noto Sans Kannada', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,231 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-Regular.otf', name='Nimbus Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,232 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMeroitic-Regular.ttf', name='Noto Sans Meroitic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,232 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMalayalam-Regular.ttf', name='Noto Sans Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,233 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansRejang-Regular.ttf', name='Noto Sans Rejang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,233 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansInscriptionalParthian-Regular.ttf', name='Noto Sans Inscriptional Parthian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,233 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Regular.ttf', name='Lato', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,234 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa-BoldOblique.ttf', name='Purisa', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,234 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-BoldOblique.ttf', name='Norasi', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,235 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifYezidi-Bold.ttf', name='Noto Serif Yezidi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,235 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-orya-extra/utkal.ttf', name='ori1Uni', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,236 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-regular.otf', name='TeX Gyre Bonum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,236 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-Bold.otf', name='Lobster Two', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,237 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996\n", - "2024-10-29 15:33:08,237 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKannada-Regular.ttf', name='Noto Sans Kannada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,238 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm-math/latinmodern-math.otf', name='Latin Modern Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,238 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/SyamalaRamana.ttf', name='Syamala Ramana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,239 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Bold.ttf', name='Lato', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,239 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono-Oblique.ttf', name='Tlwg Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,239 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Regular.ttf', name='Liberation Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,240 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-bold.otf', name='Latin Modern Mono Prop Light', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,240 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter-BoldOblique.otf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,241 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist.otf', name='Tlwg Typist', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,241 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-BoldItalic.otf', name='Nimbus Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,242 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-Italic.ttf', name='Norasi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,242 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKayahLi-Bold.ttf', name='Noto Sans Kayah Li', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,243 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-Italic.ttf', name='Arimo', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,243 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLepcha-Regular.ttf', name='Noto Sans Lepcha', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,244 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Medium.ttf', name='Yrsa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,244 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidotBold.otf', name='GFS Didot', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,244 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-BoldItalic.ttf', name='Arimo', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,245 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-BoldItalic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,245 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree-Bold.otf', name='Waree', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,246 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoprop10-regular.otf', name='Latin Modern Mono Prop', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,246 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-italic.otf', name='TeX Gyre Adventor', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,247 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSansOblique.ttf', name='FreeSans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,247 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedLao-Bold.ttf', name='Noto Looped Lao', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,248 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Italic.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,248 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman-Italic.otf', name='Laksaman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,249 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,249 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Medium.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=500, stretch='condensed', size='scalable')) = 10.344999999999999\n", - "2024-10-29 15:33:08,250 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-BoldItalic.otf', name='Norasi', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,250 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Ponnala.ttf', name='Ponnala', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,250 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-bold.otf', name='TeX Gyre Cursor', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,251 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Suravaram.ttf', name='Suravaram', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,251 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-BoldItalic.otf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,252 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree-Bold.ttf', name='Waree', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,252 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-Italic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,253 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_R.otf', name='Linux Biolinum O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,253 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/Z003-MediumItalic.otf', name='Z003', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,254 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Thin.ttf', name='Lato', style='normal', variant='normal', weight=200, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,254 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-Regular.otf', name='Accanthis ADF Std No2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,255 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/glyphicons/glyphicons-halflings-regular.ttf', name='GLYPHICONS Halflings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,255 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee-Bold.otf', name='Sawasdee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,255 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansdemicond10-regular.otf', name='Latin Modern Sans Demi Cond', style='normal', variant='normal', weight=600, stretch='condensed', size='scalable')) = 10.44\n", - "2024-10-29 15:33:08,256 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTibetan-Bold.ttf', name='Noto Serif Tibetan', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,256 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-Bold.ttf', name='Kinnari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,257 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMono.otf', name='FreeMono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,257 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-BI.ttf', name='Ubuntu', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,258 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPalmyrene-Regular.ttf', name='Noto Sans Palmyrene', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,258 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-Oblique.ttf', name='Kinnari', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,259 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/theokritos/GFSTheokritos.otf', name='GFS Theokritos', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,259 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLao-Regular.ttf', name='Noto Sans Lao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,260 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCham-Regular.ttf', name='Noto Sans Cham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,260 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGurmukhi-Bold.ttf', name='Noto Serif Gurmukhi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,265 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTangut-Regular.ttf', name='Noto Serif Tangut', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,265 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Smallcaps-Italic.ttf', name='Go Smallcaps', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,266 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSymbols2-Regular.ttf', name='Noto Sans Symbols2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,266 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Heavy.ttf', name='Lato', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:33:08,267 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond-InitialsF2.ttf', name='EB Garamond Initials Fill2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,267 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-bolditalic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,267 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-Oblique.otf', name='Kinnari', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,268 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifHebrew-Regular.ttf', name='Noto Serif Hebrew', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,268 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans12-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,269 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Italic.ttf', name='Liberation Sans Narrow', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:08,269 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMeeteiMayek-Regular.ttf', name='Noto Sans Meetei Mayek', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,270 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMono-Regular.ttf', name='Noto Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,270 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifNyiakengPuachueHmong-Bold.ttf', name='Noto Serif Hmong Nyiakeng', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,271 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lao/Phetsarath_OT.ttf', name='Phetsarath OT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,271 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSans-Bold.otf', name='Nimbus Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,272 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldNorthArabian-Regular.ttf', name='Noto Sans Old North Arabian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,272 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-regular.otf', name='Latin Modern Sans Quotation', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,273 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifThai-Regular.ttf', name='Noto Serif Thai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,273 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGujarati-Regular.ttf', name='Noto Serif Gujarati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,274 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoKufiArabic-Regular.ttf', name='Noto Kufi Arabic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,274 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-Italic.otf', name='Nimbus Mono PS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,274 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ttf-khmeros-core/KhmerOSsys.ttf', name='Khmer OS System', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,275 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-Regular.otf', name='Lobster Two', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,275 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnPilgiBold.ttf', name='UnPilgi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,276 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMendeKikakui-Regular.ttf', name='Noto Sans Mende Kikakui', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,276 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Cond.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:08,277 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMro-Regular.ttf', name='Noto Sans Mro', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,277 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKannada-Bold.ttf', name='Noto Serif Kannada', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,278 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-M.ttf', name='Ubuntu', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,278 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoltcond10-regular.otf', name='Latin Modern Mono Light Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:08,279 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-Bold.otf', name='Kinnari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,279 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-Italic.otf', name='Nimbus Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,280 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Italic.ttf', name='Go', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,280 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus-compact/GentiumPlusCompact-I.ttf', name='Gentium Plus Compact', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,280 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-Light.otf', name='URW Bookman', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,281 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNaskhArabic-Bold.ttf', name='Noto Naskh Arabic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,281 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansElbasan-Regular.ttf', name='Noto Sans Elbasan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,282 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramondSC12-Regular.otf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,282 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Light.ttf', name='Rasa', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,283 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-BoldItalic.ttf', name='Noto Sans Display', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,283 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-Italic.ttf', name='Noto Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,284 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMono.ttf', name='FreeMono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,284 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Regular.ttf', name='Quicksand', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,285 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/comfortaa/Comfortaa-Bold.ttf', name='Comfortaa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,285 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,285 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-Regular.otf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,286 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-Bold.otf', name='P052', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,286 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/PadaukBook-Regular.ttf', name='Padauk Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,287 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromancaps10-regular.otf', name='Latin Modern Roman Caps', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,287 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak-fonts/Samyak-Tamil.ttf', name='Samyak Tamil', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,288 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-ExtraBold.otf', name='Cantarell', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:33:08,288 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma-Bold.ttf', name='Loma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,289 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman17-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,289 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond-InitialsF2.otf', name='EB Garamond Initials Fill2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,290 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-BoldOblique.otf', name='Kinnari', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,290 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-BoldItalic.ttf', name='Lato', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,291 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOriya-Bold.ttf', name='Noto Sans Oriya', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,291 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-Italic.otf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,291 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCypriot-Regular.ttf', name='Noto Sans Cypriot', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,292 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCherokee-Regular.ttf', name='Noto Sans Cherokee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,292 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-Light.ttf', name='Umpush', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,293 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeTwoSym-Bold.otf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,293 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-BlackItalic.ttf', name='Roboto', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525\n", - "2024-10-29 15:33:08,294 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma.ttf', name='Loma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,294 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMedefaidrin-Bold.ttf', name='Noto Sans Medefaidrin', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,295 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnGraphicBold.ttf', name='UnGraphic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,295 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-BoldCondItalic.otf', name='Gillius ADF', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:08,296 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSansBold.otf', name='FreeSans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,296 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnYetgul.ttf', name='UnYetgul', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,297 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-regular.otf', name='TeX Gyre Pagella', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,297 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,298 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-BoldItalic.otf', name='Kinnari', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,298 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCanadianAboriginal-Bold.ttf', name='Noto Sans Canadian Aboriginal', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,299 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSaurashtra-Regular.ttf', name='Noto Sans Saurashtra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,299 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArmenian-Regular.ttf', name='Noto Sans Armenian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,299 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/complutum/GFSPolyglot.otf', name='GFS Complutum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,300 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhudawadi-Regular.ttf', name='Noto Sans Khudawadi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,300 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSansOblique.otf', name='FreeSans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,301 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGurmukhi-Bold.ttf', name='Noto Sans Gurmukhi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,301 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-bold.otf', name='TeX Gyre Bonum', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,302 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldSogdian-Regular.ttf', name='Noto Sans Old Sogdian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,302 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoMono-Regular.ttf', name='Noto Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,303 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/olga/GFSOlga.otf', name='GFS Olga', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,303 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,304 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-ExtraLight.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=200, stretch='normal', size='scalable')) = 0.24\n", - "2024-10-29 15:33:08,304 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-ThinItalic.ttf', name='Lato', style='italic', variant='normal', weight=200, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,305 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/Mukti.ttf', name='Mukti', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,305 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-Bold.ttf', name='Charis SIL', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,305 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-punjabi/Lohit-Gurmukhi.ttf', name='Lohit Gurmukhi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,306 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda-Bold.otf', name='Garuda', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,306 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDinaru.ttf', name='UnDinaru', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,307 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman8-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,307 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifEthiopic-Regular.ttf', name='Noto Serif Ethiopic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,308 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono9-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,308 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Medium.ttf', name='Go Medium', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,309 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Regular.ttf', name='Yrsa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,309 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-R.ttf', name='Ubuntu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,310 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/NATS.ttf', name='NATS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,310 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Bold.ttf', name='Open Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,311 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-Oblique.otf', name='Norasi', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,311 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDevanagari-Regular.ttf', name='Noto Sans Devanagari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,311 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoltcond10-oblique.otf', name='Latin Modern Mono Light Cond', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:08,312 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-Regular.ttf', name='Noto Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,312 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Medium.ttf', name='Lato', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,313 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-BoldItalic.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,313 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTelugu-Regular.ttf', name='Noto Serif Telugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,314 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMalayalam-Bold.ttf', name='Noto Sans Malayalam', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,314 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Italic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,315 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-BoldOblique.otf', name='Nimbus Sans Narrow', style='oblique', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:08,315 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_K.otf', name='Linux Biolinum Keyboard O', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,316 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-bsmi00lp/bsmi00lp.ttf', name='AR PL Mingti2L Big5', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,316 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDevanagari-Bold.ttf', name='Noto Sans Devanagari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,317 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSansBoldOblique.otf', name='FreeSans', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,317 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNaskhArabic-Regular.ttf', name='Noto Naskh Arabic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,318 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMonoBold.ttf', name='FreeMono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,318 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstArt.ttf', name='KacstArt', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,318 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansVai-Regular.ttf', name='Noto Sans Vai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,319 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-italic.otf', name='TeX Gyre Pagella', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,319 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman9-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,320 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghHawad-Regular.ttf', name='Noto Sans Tifinagh Hawad', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,320 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/padmaa-Medium-0.5.ttf', name='padmaa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,321 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-HairlineItalic.ttf', name='Lato', style='italic', variant='normal', weight=100, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,321 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBalinese-Regular.ttf', name='Noto Sans Balinese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,322 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/gazis/GFSGazis.otf', name='GFS Gazis', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,322 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-Bold.otf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,323 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-bold.otf', name='TeX Gyre Schola', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,323 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansYi-Regular.ttf', name='Noto Sans Yi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,323 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpSm-Bold.otf', name='STIXIntegralsUpSm', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,324 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Bold.ttf', name='Go', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,325 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/Gentium-R.ttf', name='Gentium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,325 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman6-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,326 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMasaramGondi-Regular.ttf', name='Noto Sans Masaram Gondi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,326 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='condensed', size='scalable')) = 1.535\n", - "2024-10-29 15:33:08,327 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Gayathri-Thin.otf', name='Gayathri', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,327 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-Oblique.otf', name='Nimbus Sans Narrow', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:08,328 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Italic.ttf', name='Lato', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,328 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisiaIt.otf', name='GFS Artemisia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,329 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGeorgian-Bold.ttf', name='Noto Sans Georgian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,329 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda-BoldOblique.ttf', name='Garuda', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,371 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-Regular.ttf', name='Noto Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,371 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPauCinHau-Regular.ttf', name='Noto Sans Pau Cin Hau', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,372 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSiddham-Regular.ttf', name='Noto Sans Siddham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,372 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-kalapi/Kalapi.ttf', name='Kalapi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,373 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-L.ttf', name='Ubuntu', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,373 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedLao-Regular.ttf', name='Noto Looped Lao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,374 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/batang.ttf', name='Baekmuk Batang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,375 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-Bold.ttf', name='Liberation Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,375 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Suruma.ttf', name='Suruma', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,376 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/comfortaa/Comfortaa-Regular.ttf', name='Comfortaa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,376 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-oblique.otf', name='Latin Modern Mono Light', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,377 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman7-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,379 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUp-Bold.otf', name='STIXIntegralsUp', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,380 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-Bold.otf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,380 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSundanese-Regular.ttf', name='Noto Sans Sundanese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,381 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSoyombo-Regular.ttf', name='Noto Sans Soyombo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,382 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasBI.ttf', name='Gentium Basic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,383 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman-Bold.ttf', name='Laksaman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,383 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-bold.otf', name='TeX Gyre Heros Cn', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,384 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeMonoBoldOblique.ttf', name='FreeMono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,384 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-Bold.ttf', name='Noto Serif Display', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,385 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode-Italic.ttf', name='Junicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,385 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono-Bold.ttf', name='Tlwg Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,386 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnBatangBold.ttf', name='UnBatang', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,387 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-bolditalic.otf', name='TeX Gyre Heros Cn', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,388 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Manjari-Regular.otf', name='Manjari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,389 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGujarati-Bold.ttf', name='Noto Sans Gujarati', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,389 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-BoldItalic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,390 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman7-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,390 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-CondItalic.otf', name='Universalis ADF Std', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:08,391 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMarchen-Regular.ttf', name='Noto Sans Marchen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,391 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghRhissaIxa-Regular.ttf', name='Noto Sans Tifinagh Rhissa Ixa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,392 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman9-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,392 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSoraSompeng-Regular.ttf', name='Noto Sans Sora Sompeng', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,393 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDevanagari-Regular.ttf', name='Noto Serif Devanagari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,393 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/padmaa.ttf', name='padmaa', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,394 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,394 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono.ttf', name='Go Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,395 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyretermes-bolditalic.otf', name='TeX Gyre Termes', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,397 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond-Initials.otf', name='EB Garamond Initials', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,398 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-BoldItalic.ttf', name='Roboto', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,399 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-Regular.otf', name='STIX', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,399 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist-Oblique.otf', name='Tlwg Typist', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,400 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-Bold.ttf', name='Gentium Plus', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,400 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Bold.ttf', name='Roboto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,401 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/FoulisGreek.ttf', name='FoulisGreek', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,401 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Italic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,402 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Smallcaps.ttf', name='Go Smallcaps', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,402 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGeorgian-Bold.ttf', name='Noto Serif Georgian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,403 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo-Bold.otf', name='Tlwg Typo', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,403 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Italic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:08,404 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKaithi-Regular.ttf', name='Noto Sans Kaithi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,404 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Dyuthi-Regular.ttf', name='Dyuthi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,405 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda-Oblique.ttf', name='Garuda', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,408 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-SemiBold.otf', name='Cabin', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,408 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-mincho/ipamp.ttf', name='IPAPMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,409 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Regular.otf', name='Gillius ADF', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,409 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Regular.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:08,410 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansThai-Regular.ttf', name='Noto Sans Thai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,410 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLydian-Regular.ttf', name='Noto Sans Lydian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,411 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Light.ttf', name='Open Sans', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,411 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyretermes-math.otf', name='TeX Gyre Termes Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,412 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenicBoldIt.otf', name='GFS Neohellenic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,412 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Regular.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,413 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Purisa.ttf', name='Purisa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,414 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBatak-Regular.ttf', name='Noto Sans Batak', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,414 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipaexfont-gothic/ipaexg.ttf', name='IPAexGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,415 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGrantha-Regular.ttf', name='Noto Serif Grantha', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,415 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-Bold.ttf', name='Rasa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,416 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-BoldItalic.ttf', name='Norasi', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,416 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree-Oblique.ttf', name='Waree', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,417 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldItalic-Regular.ttf', name='Noto Sans Old Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,417 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDotum.ttf', name='UnDotum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,418 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOsmanya-Regular.ttf', name='Noto Sans Osmanya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,418 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-B.ttf', name='Ubuntu Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,422 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnPilgi.ttf', name='UnPilgi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,422 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RB.otf', name='Linux Libertine O', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,423 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Medium.ttf', name='Quicksand Medium', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,423 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoSora.ttf', name='UnJamoSora', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,424 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Manjari-Thin.otf', name='Manjari', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,424 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifSinhala-Regular.ttf', name='Noto Serif Sinhala', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,426 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifHebrew-Bold.ttf', name='Noto Serif Hebrew', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,426 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDinaruBold.ttf', name='UnDinaru', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,427 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArmenian-Bold.ttf', name='Noto Sans Armenian', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,428 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Regular.ttf', name='Liberation Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,429 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee-Bold.ttf', name='Sawasdee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,429 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Rasa-SemiBold.ttf', name='Rasa', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,430 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-Regular.ttf', name='Amiri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,431 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-Italic.ttf', name='Charis SIL', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,431 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBhaiksuki-Regular.ttf', name='Noto Sans Bhaiksuki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,432 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma-BoldOblique.ttf', name='Loma', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,433 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSymbols-Bold.ttf', name='Noto Sans Symbols', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,433 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter.otf', name='Tlwg Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,434 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-BoldCond.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:08,435 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyreschola-math.otf', name='TeX Gyre Schola Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,435 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-CondItalic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25\n", - "2024-10-29 15:33:08,436 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Waree-BoldOblique.ttf', name='Waree', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,437 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSogdian-Regular.ttf', name='Noto Sans Sogdian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,438 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans8-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,438 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee-Oblique.ttf', name='Sawasdee', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,439 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak/Samyak-Devanagari.ttf', name='Samyak Devanagari', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,440 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Italic.otf', name='Gillius ADF', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,441 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAgrawImazighen-Regular.ttf', name='Noto Sans Tifinagh Agraw Imazighen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,441 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-Bold.ttf', name='EB Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,442 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-RI.ttf', name='Ubuntu Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,443 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-italic.otf', name='TeX Gyre Schola', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,443 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/PadaukBook-Bold.ttf', name='Padauk Book', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,444 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNabataean-Regular.ttf', name='Noto Sans Nabataean', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,444 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush.otf', name='Umpush', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,446 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/dhurjati.ttf', name='Dhurjati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,446 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGlagolitic-Regular.ttf', name='Noto Sans Glagolitic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,447 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGothic-Regular.ttf', name='Noto Sans Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,447 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-Italic.ttf', name='Kinnari', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,448 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree-Oblique.otf', name='Waree', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,448 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnPenheulim.ttf', name='UnPenheulim', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,449 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMyanmar-Regular.ttf', name='Noto Serif Myanmar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,449 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-Regular.ttf', name='Noto Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,450 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasI.ttf', name='Gentium Book Basic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,450 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerifBoldItalic.ttf', name='FreeSerif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,451 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanunsl10-regular.otf', name='Latin Modern Roman Unslanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,452 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-BoldItalic.ttf', name='Noto Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,452 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-ThinItalic.ttf', name='Roboto', style='italic', variant='normal', weight=250, stretch='normal', size='scalable')) = 11.1925\n", - "2024-10-29 15:33:08,453 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifLao-Regular.ttf', name='Noto Serif Lao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,453 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-telu-extra/Pothana2000.ttf', name='Pothana2000', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,454 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-Bold.otf', name='Umpush', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,456 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Sarai/Sarai.ttf', name='Sarai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,457 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-SemiboldItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,457 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldHungarian-Regular.ttf', name='Noto Sans Old Hungarian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,458 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMyanmar-Regular.ttf', name='Noto Sans Myanmar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,459 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-gbsn00lp/gbsn00lp.ttf', name='AR PL SungtiL GB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,459 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldPermic-Regular.ttf', name='Noto Sans Old Permic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,460 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Bold.ttf', name='Liberation Sans Narrow', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:08,460 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldSouthArabian-Regular.ttf', name='Noto Sans Old South Arabian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,461 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnGraphic.ttf', name='UnGraphic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,461 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandemi10-regular.otf', name='Latin Modern Roman Demi', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,462 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Bold.otf', name='Cantarell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,462 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-BoldCond.otf', name='Gillius ADF', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:08,463 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuMathTeXGyre.ttf', name='DejaVu Math TeX Gyre', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,463 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman7-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,466 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOriya-Regular.ttf', name='Noto Sans Oriya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,466 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSyriac-Regular.ttf', name='Noto Sans Syriac', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,467 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLisu-Regular.ttf', name='Noto Sans Lisu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,467 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-BoldItalic.ttf', name='Noto Serif Display', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,468 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAhaggar-Regular.ttf', name='Noto Sans Tifinagh Ahaggar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,469 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RI.otf', name='Linux Libertine O', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,470 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMeeteiMayek-Bold.ttf', name='Noto Sans Meetei Mayek', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,471 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansRunic-Regular.ttf', name='Noto Sans Runic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,472 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-gothic/ipagp.ttf', name='IPAPGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,472 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBengali-Bold.ttf', name='Noto Sans Bengali', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,473 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic/uming.ttc', name='AR PL UMing CN', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,473 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-BoldOblique.otf', name='Umpush', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,474 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-italic.otf', name='TeX Gyre Bonum', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,474 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasB.ttf', name='Gentium Basic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,475 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPahawhHmong-Regular.ttf', name='Noto Sans Pahawh Hmong', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,475 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-Italic.ttf', name='Caladea', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,476 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAzawagh-Regular.ttf', name='Noto Sans Tifinagh Azawagh', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,476 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Regular.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,477 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/NTR.ttf', name='NTR', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,479 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiTham-Bold.ttf', name='Noto Sans Tai Tham', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,480 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstNaskh.ttf', name='KacstNaskh', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,480 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant10-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,481 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Ramaraja-Regular.ttf', name='Ramaraja', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,481 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo-BoldOblique.ttf', name='Tlwg Typo', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,482 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-BoldItalic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,482 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond08-Regular.otf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,483 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiLe-Regular.ttf', name='Noto Sans Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,483 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusRoman-BoldItalic.otf', name='Nimbus Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,485 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush-LightOblique.ttf', name='Umpush', style='oblique', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,486 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Regular.otf', name='Cantarell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,486 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonocaps10-oblique.otf', name='Latin Modern Mono Caps', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,487 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman12-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,488 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Cond.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:08,489 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-Th.ttf', name='Ubuntu', style='normal', variant='normal', weight=250, stretch='normal', size='scalable')) = 10.1925\n", - "2024-10-29 15:33:08,489 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-BlackItalic.ttf', name='Lato', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525\n", - "2024-10-29 15:33:08,490 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/libreoffice/opens___.ttf', name='OpenSymbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,490 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 1.25\n", - "2024-10-29 15:33:08,491 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Light.ttf', name='Lato', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,491 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstOffice.ttf', name='KacstOffice', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,492 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Medium-Italic.ttf', name='Go Medium', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,494 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTirhuta-Regular.ttf', name='Noto Sans Tirhuta', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,494 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa.otf', name='Purisa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,495 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeFourSym-Regular.otf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,496 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Thin.otf', name='Cantarell', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,496 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-Bold.otf', name='Accanthis ADF Std No3', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,497 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono-Bold-Italic.ttf', name='Go Mono', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,498 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,499 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Sahadeva/sahadeva.ttf', name='Sahadeva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,499 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXGeneral-Regular.otf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,500 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/asana-math/Asana-Math.otf', name='Asana Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,500 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Bold.otf', name='Gillius ADF', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,501 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNewTaiLue-Regular.ttf', name='Noto Sans New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,501 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerif.otf', name='FreeSerif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,502 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghSIL-Regular.ttf', name='Noto Sans Tifinagh SIL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,503 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-CondLight.ttf', name='Open Sans', style='normal', variant='normal', weight=300, stretch='condensed', size='scalable')) = 10.344999999999999\n", - "2024-10-29 15:33:08,503 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-LightItalic.ttf', name='Lato', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,504 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidotItalic.otf', name='GFS Didot', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,504 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-ExtraBoldItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=800, stretch='normal', size='scalable')) = 11.43\n", - "2024-10-29 15:33:08,505 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-BoldSlanted.ttf', name='Amiri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,505 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDeseret-Regular.ttf', name='Noto Sans Deseret', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,506 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-telu-extra/vemana2000.ttf', name='Vemana2000', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,506 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPsalterPahlavi-Regular.ttf', name='Noto Sans Psalter Pahlavi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,507 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiTham-Regular.ttf', name='Noto Sans Tai Tham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,507 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandunh10-regular.otf', name='Latin Modern Roman Dunhill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,508 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstBook.ttf', name='KacstBook', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,508 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBamum-Bold.ttf', name='Noto Sans Bamum', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,509 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMedefaidrin-Regular.ttf', name='Noto Sans Medefaidrin', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,509 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee-Oblique.otf', name='Sawasdee', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,510 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-oriya/Lohit-Odia.ttf', name='Lohit Odia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,510 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMyanmar-Bold.ttf', name='Noto Sans Myanmar', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,511 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-Regular.otf', name='Berenis ADF Pro', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,511 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/GentiumAlt-I.ttf', name='GentiumAlt', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,512 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee.otf', name='Sawasdee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,513 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramondSC12-Regular.ttf', name='EB Garamond SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,513 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-Italic.ttf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,514 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-Regular.ttf', name='Gentium Plus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,514 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-regular.otf', name='TeX Gyre Heros', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,515 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Rachana-Bold.ttf', name='Rachana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,515 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/Padauk-Bold.ttf', name='Padauk', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,516 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-BI.ttf', name='Ubuntu Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,516 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeTwoSym-Regular.otf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,517 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter-Oblique.otf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,517 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist-Bold.ttf', name='Tlwg Typist', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,518 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstPoster.ttf', name='KacstPoster', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,518 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Loma-Oblique.ttf', name='Loma', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,519 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisiaBoldIt.otf', name='GFS Didot', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,519 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlamUnjoined-Bold.ttf', name='Noto Sans Adlam Unjoined', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,525 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant17-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,526 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPhagsPa-Regular.ttf', name='Noto Sans PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,527 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFPro-BoldItalic.otf', name='Berenis ADF Pro', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,528 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Bold.ttf', name='Quicksand', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,528 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-Regular.ttf', name='Arimo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,529 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Navilu/Navilu.ttf', name='Navilu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,529 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Italic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,530 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOldTurkic-Regular.ttf', name='Noto Sans Old Turkic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,530 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-Bold.ttf', name='Liberation Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,531 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDotumBold.ttf', name='UnDotum', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,532 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHebrew-Bold.ttf', name='Noto Sans Hebrew', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,533 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUp-Regular.otf', name='STIXIntegralsUp', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,534 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-ExtraBold.ttf', name='Open Sans', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43\n", - "2024-10-29 15:33:08,534 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-Regular.ttf', name='EB Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,535 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonocaps10-regular.otf', name='Latin Modern Mono Caps', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,536 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/dotum.ttf', name='Baekmuk Dotum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,536 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_I.otf', name='Linux Libertine Initials O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,537 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-BoldItalic.otf', name='Accanthis ADF Std No3', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,538 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-Italic.ttf', name='Carlito', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,538 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-bolditalic.otf', name='TeX Gyre Cursor', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,539 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tibetan-machine/TibetanMachineUni.ttf', name='Tibetan Machine Uni', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,540 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-CondLightItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=300, stretch='condensed', size='scalable')) = 11.344999999999999\n", - "2024-10-29 15:33:08,541 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobster/lobster.otf', name='Lobster Two', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,541 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-MediumItalic.ttf', name='Yrsa', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,542 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/droid/DroidSansFallbackFull.ttf', name='Droid Sans Fallback', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,542 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-BoldItalic.ttf', name='Gentium Plus', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,543 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-HeavyItalic.ttf', name='Lato', style='italic', variant='normal', weight=800, stretch='normal', size='scalable')) = 11.43\n", - "2024-10-29 15:33:08,544 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/Ani.ttf', name='Ani', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,544 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAvestan-Regular.ttf', name='Noto Sans Avestan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,545 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Peddana-Regular.ttf', name='Peddana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,545 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman10-italic.otf', name='Latin Modern Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,546 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMalayalam-Regular.ttf', name='Noto Serif Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,546 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono.ttf', name='Tlwg Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,547 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyredejavu-math.otf', name='TeX Gyre DejaVu Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,548 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-BoldItalic.otf', name='Lobster Two', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,548 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLinearB-Regular.ttf', name='Noto Sans Linear B', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,549 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-Regular.otf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,551 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-bolditalic.otf', name='TeX Gyre Heros', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,551 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo.otf', name='Tlwg Typo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,552 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335\n", - "2024-10-29 15:33:08,553 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/padauk/Padauk-Regular.ttf', name='Padauk', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,553 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst-one/KacstOne-Bold.ttf', name='KacstOne', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,554 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansJavanese-Bold.ttf', name='Noto Sans Javanese', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,555 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman12-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,555 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBuginese-Regular.ttf', name='Noto Sans Buginese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,556 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-Regular.otf', name='Nimbus Mono PS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,556 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-Regular.ttf', name='Noto Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,557 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-boldoblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,558 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/UniversalisADFStd-Bold.otf', name='Universalis ADF Std', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,558 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant9-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,559 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnPen.ttf', name='UnPen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,559 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSinhala-Regular.ttf', name='Noto Sans Sinhala', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,560 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-Bold.otf', name='EB Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,560 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTelugu-Bold.ttf', name='Noto Sans Telugu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,561 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHanunoo-Regular.ttf', name='Noto Sans Hanunoo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,562 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ttf-khmeros-core/KhmerOS.ttf', name='Khmer OS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,562 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMono-Bold.ttf', name='Noto Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,564 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnShinmun.ttf', name='UnShinmun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,565 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-BoldItalic.otf', name='Accanthis ADF Std No2', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,565 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLisu-Bold.ttf', name='Noto Sans Lisu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,566 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasB.ttf', name='Gentium Book Basic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,567 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus-compact/GentiumPlusCompact-R.ttf', name='Gentium Plus Compact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,568 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/JamrulNormal.ttf', name='Jamrul', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,568 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari.otf', name='Kinnari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,569 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-BoldItalic.otf', name='STIX', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,570 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman8-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,571 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-Roman.otf', name='P052', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,571 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromancaps10-oblique.otf', name='Latin Modern Roman Caps', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,572 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo.ttf', name='Tlwg Typo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,572 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Kinnari-Italic.otf', name='Kinnari', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,574 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypist-Bold.otf', name='Tlwg Typist', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,574 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansImperialAramaic-Regular.ttf', name='Noto Sans Imperial Aramaic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,575 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansArabic-Bold.ttf', name='Noto Sans Arabic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,575 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyrepagella-math.otf', name='TeX Gyre Pagella Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,576 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrechorus-mediumitalic.otf', name='TeX Gyre Chorus', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,576 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMiao-Regular.ttf', name='Noto Sans Miao', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,577 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnDinaruLight.ttf', name='UnDinaru', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,577 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/sinhala/lklug.ttf', name='LKLUG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,579 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHanifiRohingya-Bold.ttf', name='Noto Sans Hanifi Rohingya', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,580 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Uroob-Regular.ttf', name='Uroob', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,580 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansInscriptionalPahlavi-Regular.ttf', name='Noto Sans Inscriptional Pahlavi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,581 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-MediumItalic.otf', name='Cabin', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,581 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode-Bold.ttf', name='Junicode', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,582 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifAhom-Regular.ttf', name='Noto Serif Ahom', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,583 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-Italic.ttf', name='Noto Sans Display', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,583 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnVada.ttf', name='UnVada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,584 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoslant10-regular.otf', name='Latin Modern Mono Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,584 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSymbols-Regular.ttf', name='Noto Sans Symbols', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,585 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans9-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,587 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi.ttf', name='Norasi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,587 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-Bold.ttf', name='Carlito', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,588 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenic.otf', name='GFS Neohellenic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,588 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOgham-Regular.ttf', name='Noto Sans Ogham', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,589 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGrantha-Regular.ttf', name='Noto Sans Grantha', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,589 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerifItalic.otf', name='FreeSerif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,590 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrepagella-bolditalic.otf', name='TeX Gyre Pagella', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,591 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Light.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=300, stretch='condensed', size='scalable')) = 10.344999999999999\n", - "2024-10-29 15:33:08,592 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Karumbi-Regular.ttf', name='Karumbi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,593 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansIndicSiyaqNumbers-Regular.ttf', name='Noto Sans Indic Siyaq Numbers', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,593 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter.ttf', name='Tlwg Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,594 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-Italic.otf', name='P052', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,594 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo-BoldOblique.otf', name='Tlwg Typo', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,595 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsSm-Bold.otf', name='STIXIntegralsSm', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,595 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGujarati-Bold.ttf', name='Noto Serif Gujarati', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,596 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-BoldItalic.ttf', name='Liberation Sans Narrow', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:08,597 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansZanabazarSquare-Regular.ttf', name='Noto Sans Zanabazar Square', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,597 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoMusic-Regular.ttf', name='Noto Music', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,598 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-Bold.otf', name='Norasi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,598 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda.ttf', name='Garuda', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,599 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Gubbi/Gubbi.ttf', name='Gubbi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,599 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Bold.ttf', name='Liberation Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,600 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMalayalam-Bold.ttf', name='Noto Serif Malayalam', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,601 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifArmenian-Regular.ttf', name='Noto Serif Armenian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,601 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond12-AllSC.otf', name='EB Garamond 12 All SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,602 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:08,604 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-bkai00mp/bkai00mp.ttf', name='AR PL KaitiM Big5', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,605 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma-BoldOblique.otf', name='Loma', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,606 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre-math/texgyrebonum-math.otf', name='TeX Gyre Bonum Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,606 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-oblique.otf', name='Latin Modern Mono Prop Light', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,607 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman-BoldItalic.ttf', name='Laksaman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,607 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoRashiHebrew-Bold.ttf', name='Noto Rashi Hebrew', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,608 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Italic.ttf', name='Open Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,608 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-Italic.otf', name='Accanthis ADF Std No2', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,609 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMayanNumerals-Regular.ttf', name='Noto Sans Mayan Numerals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,610 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda.otf', name='Garuda', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,610 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBalinese-Bold.ttf', name='Noto Sans Balinese', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,611 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlam-Bold.ttf', name='Noto Sans Adlam', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,611 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnGungseo.ttf', name='UnGungseo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,612 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstDecorative.ttf', name='KacstDecorative', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,613 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstTitle.ttf', name='KacstTitle', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,613 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTibetan-Regular.ttf', name='Noto Serif Tibetan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,614 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-bold.otf', name='TeX Gyre Adventor', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,614 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromanslant12-regular.otf', name='Latin Modern Roman Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,615 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreschola-regular.otf', name='TeX Gyre Schola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,615 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgMono-Bold.otf', name='Tlwg Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,616 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-regular.otf', name='TeX Gyre Cursor', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,616 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-boldoblique.otf', name='Latin Modern Mono Prop Light', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,617 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnJamoNovel.ttf', name='UnJamoNovel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,617 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-MediumItalic.ttf', name='Roboto', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,618 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Umpush-Light.otf', name='Umpush', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,618 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerifBold.otf', name='FreeSerif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,622 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Italic.otf', name='Cabin', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,623 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak-fonts/Samyak-Malayalam.ttf', name='Samyak Malayalam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,623 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/TimmanaRegular.ttf', name='Timmana', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525\n", - "2024-10-29 15:33:08,624 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Meera-Regular.ttf', name='Meera', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,625 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansPhoenician-Regular.ttf', name='Noto Sans Phoenician', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,626 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinBiolinum_RB.otf', name='Linux Biolinum O', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,626 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-SemiBoldItalic.otf', name='Cabin', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,627 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cantarell/Cantarell-Light.otf', name='Cantarell', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,628 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-BoldItalic.ttf', name='Gentium Book Plus', style='italic', variant='normal', weight=800, stretch='normal', size='scalable')) = 11.43\n", - "2024-10-29 15:33:08,629 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Sawasdee-BoldOblique.otf', name='Sawasdee', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,629 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc', name='Noto Sans CJK JP', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,630 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinagh-Regular.ttf', name='Noto Sans Tifinagh', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,630 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-Italic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,631 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot/GFSDidotBoldItalic.otf', name='GFS Didot', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,632 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium/GentiumAlt-R.ttf', name='GentiumAlt', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,632 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansEthiopic-Regular.ttf', name='Noto Sans Ethiopic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,633 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Medium.ttf', name='Roboto', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,633 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono-Bold.ttf', name='Go Mono', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,634 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLinearA-Regular.ttf', name='Noto Sans Linear A', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,636 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasBI.ttf', name='Gentium Book Basic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,636 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/junicode/Junicode.ttf', name='Junicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,637 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/TenaliRamakrishna-Regular.ttf', name='TenaliRamakrishna', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,637 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoproplt10-regular.otf', name='Latin Modern Mono Prop Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,638 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/mry_KacstQurn.ttf', name='mry_KacstQurn', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,638 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/SreeKrushnadevaraya.ttf', name='Sree Krushnadevaraya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,640 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifBengali-Regular.ttf', name='Noto Serif Bengali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,640 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMath-Regular.ttf', name='Noto Sans Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,641 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansUgaritic-Regular.ttf', name='Noto Sans Ugaritic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,641 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerif.ttf', name='FreeSerif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,642 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Arimo-Bold.ttf', name='Arimo', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,643 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBkBasR.ttf', name='Gentium Book Basic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,643 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerifBold.ttf', name='FreeSerif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,644 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusMonoPS-Bold.otf', name='Nimbus Mono PS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,644 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter-BoldOblique.ttf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,645 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/C059-BdIta.otf', name='C059', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,645 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-japanese-gothic.ttf', name='IPAexGothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,646 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-Regular.ttf', name='Cousine', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,647 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman12-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,647 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansCondensed-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 0.5349999999999999\n", - "2024-10-29 15:33:08,648 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonolt10-bold.otf', name='Latin Modern Mono Light', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,648 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSans-Bold.ttf', name='Liberation Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,649 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/lobstertwo/LobsterTwo-Italic.otf', name='Lobster Two', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,651 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Italic.ttf', name='Roboto', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,652 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-BoldItalic.otf', name='Gillius ADF', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,653 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDuployan-Regular.ttf', name='Noto Sans Duployan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,654 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/BerenisADFProMath-Regular.otf', name='Berenis ADF Pro Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,654 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGeorgian-Regular.ttf', name='Noto Serif Georgian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,655 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,655 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/arphic-gkai00mp/gkai00mp.ttf', name='AR PL KaitiM GB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,656 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/MitraMono.ttf', name='Mitra ', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,657 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeOneSym-Regular.otf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,657 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNastaliqUrdu-Bold.ttf', name='Noto Nastaliq Urdu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,658 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-BoldItalic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,659 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/fonts-go/Go-Mono-Italic.ttf', name='Go Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,659 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStd-BoldItalic.otf', name='Accanthis ADF Std', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,660 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-Bold.ttf', name='Cousine', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,660 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/Rekha.ttf', name='Rekha', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,661 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstDigital.ttf', name='KacstDigital', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,663 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-bold.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,663 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansHatran-Regular.ttf', name='Noto Sans Hatran', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,664 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-bolditalic.otf', name='TeX Gyre Adventor', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,665 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-core/UnBatang.ttf', name='UnBatang', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,665 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansWancho-Regular.ttf', name='Noto Sans Wancho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,666 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-BoldItalic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:08,666 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKharoshthi-Regular.ttf', name='Noto Sans Kharoshthi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,667 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghAdrar-Regular.ttf', name='Noto Sans Tifinagh Adrar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,668 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpD-Regular.otf', name='STIXIntegralsUpD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,669 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/quicksand/Quicksand-Light.ttf', name='Quicksand Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,669 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-kannada/Lohit-Kannada.ttf', name='Lohit Kannada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,670 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Regular.otf', name='Cabin', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,671 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/solomos/GFSSolomos.otf', name='GFS Solomos', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,671 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-Hairline.ttf', name='Lato', style='normal', variant='normal', weight=100, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,672 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAnatolianHieroglyphs-Regular.ttf', name='Noto Sans Anatolian Hieroglyphs', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,672 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-BookOblique.otf', name='URW Gothic', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,673 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-bold.otf', name='Latin Modern Sans Quotation', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,674 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Nakula/nakula.ttf', name='Nakula', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,674 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RBI.otf', name='Linux Libertine O', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,675 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoNastaliqUrdu-Regular.ttf', name='Noto Nastaliq Urdu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,675 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDisplay-Italic.ttf', name='Noto Serif Display', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,676 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXNonUnicode-Italic.otf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,676 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTamil-Bold.ttf', name='Noto Sans Tamil', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,677 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghTawellemmet-Regular.ttf', name='Noto Sans Tifinagh Tawellemmet', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,677 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGeorgian-Regular.ttf', name='Noto Sans Georgian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,678 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansAdlamUnjoined-Regular.ttf', name='Noto Sans Adlam Unjoined', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,679 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/baekmuk/hline.ttf', name='Baekmuk Headline', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,679 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Waree-BoldOblique.otf', name='Waree', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,680 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMonoOblique.otf', name='FreeMono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,683 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreadventor-regular.otf', name='TeX Gyre Adventor', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,683 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Purisa-BoldOblique.otf', name='Purisa', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,684 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCham-Bold.ttf', name='Noto Sans Cham', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,684 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Sawasdee-BoldOblique.ttf', name='Sawasdee', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,685 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-BoldItalic.ttf', name='Tinos', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,686 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheros-italic.otf', name='TeX Gyre Heros', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,687 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-Bold.ttf', name='Noto Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,687 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWBookman-DemiItalic.otf', name='URW Bookman', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,688 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhmer-Bold.ttf', name='Noto Serif Khmer', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,689 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/AmiriQuran.ttf', name='Amiri Quran', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,689 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpSm-Regular.otf', name='STIXIntegralsUpSm', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,690 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTamilSupplement-Regular.ttf', name='Noto Sans Tamil Supplement', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,691 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman-Bold.otf', name='Laksaman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,692 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-italic.otf', name='TeX Gyre Heros Cn', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,692 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenicIt.otf', name='GFS Neohellenic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,693 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSoraSompeng-Bold.ttf', name='Noto Sans Sora Sompeng', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,693 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans17-oblique.otf', name='Latin Modern Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,694 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSerifCJK-Regular.ttc', name='Noto Serif CJK JP', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,694 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCoptic-Regular.ttf', name='Noto Sans Coptic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,695 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Thin.ttf', name='Roboto', style='normal', variant='normal', weight=250, stretch='normal', size='scalable')) = 10.1925\n", - "2024-10-29 15:33:08,696 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypo-Oblique.otf', name='Tlwg Typo', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,697 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTifinaghGhat-Regular.ttf', name='Noto Sans Tifinagh Ghat', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,698 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/samyak-fonts/Samyak-Gujarati.ttf', name='Samyak Gujarati', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,699 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RZI.otf', name='Linux Libertine O', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,699 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo-Oblique.ttf', name='Tlwg Typo', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,700 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-Regular.ttf', name='Liberation Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,700 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamil-Bold.ttf', name='Noto Serif Tamil', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,701 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSans-Bold.ttf', name='Noto Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,701 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSamaritan-Regular.ttf', name='Noto Sans Samaritan', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,702 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond-InitialsF1.otf', name='EB Garamond Initials Fill1', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,703 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter-Oblique.ttf', name='Tlwg Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,704 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/RaghuMalayalamSans-Regular.ttf', name='RaghuMalayalamSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,705 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmromandunh10-oblique.otf', name='Latin Modern Roman Dunhill', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,706 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Umpush.ttf', name='Umpush', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,706 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans10-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,707 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/Keraleeyam-Regular.ttf', name='Keraleeyam', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,707 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/P052-BoldItalic.otf', name='P052', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,708 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma-Oblique.otf', name='Loma', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,708 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifSinhala-Bold.ttf', name='Noto Serif Sinhala', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,709 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_M.otf', name='Linux Libertine Mono O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,709 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:08,711 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo2-Bold.otf', name='Accanthis ADF Std No2', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,712 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeThreeSym-Bold.otf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,712 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-SemiBold.ttf', name='Yrsa', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,713 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifBengali-Bold.ttf', name='Noto Serif Bengali', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,714 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/UbuntuMono-R.ttf', name='Ubuntu Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,714 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeSerifBoldItalic.otf', name='FreeSerif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,715 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Garuda-BoldOblique.otf', name='Garuda', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,715 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman5-regular.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,716 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypewriter-Bold.ttf', name='Tlwg Typewriter', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,716 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-BoldItalic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,717 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-BoldCondItalic.otf', name='Gillius ADF No2', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:08,717 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhojki-Regular.ttf', name='Noto Serif Khojki', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,718 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansJavanese-Regular.ttf', name='Noto Sans Javanese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,721 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADFNo2-Bold.otf', name='Gillius ADF No2', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,723 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma.otf', name='Loma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,724 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansBamum-Regular.ttf', name='Noto Sans Bamum', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,725 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond-InitialsF1.ttf', name='EB Garamond Initials Fill1', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,725 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/font-awesome/fontawesome-webfont.ttf', name='FontAwesome', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,726 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-bengali/Lohit-Bengali.ttf', name='Lohit Bengali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,727 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstScreen.ttf', name='KacstScreen', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,728 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTelugu-Regular.ttf', name='Noto Sans Telugu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,728 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-Light.ttf', name='Roboto', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,729 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-boldoblique.otf', name='Latin Modern Sans Quotation', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,730 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKhmer-Regular.ttf', name='Noto Sans Khmer', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,731 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/Mandali-Regular.ttf', name='Mandali', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,731 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Chilanka-Regular.otf', name='Chilanka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,732 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIXMath-Regular.otf', name='STIX Math', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,733 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-Regular.ttf', name='Liberation Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,734 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-Regular.ttf', name='Open Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,734 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-Demi.otf', name='URW Gothic', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,735 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman9-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,735 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf', name='Liberation Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,736 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/comfortaa/Comfortaa-Light.ttf', name='Comfortaa', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,737 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/freefont/FreeMonoBoldOblique.otf', name='FreeMono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,737 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgMono-BoldOblique.ttf', name='Tlwg Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,738 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-Oblique.ttf', name='Norasi', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,739 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/URWGothic-DemiOblique.otf', name='URW Gothic', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24\n", - "2024-10-29 15:33:08,740 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsans8-regular.otf', name='Latin Modern Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,741 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Laksaman.ttf', name='Laksaman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,742 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/RaviPrakash.ttf', name='RaviPrakash', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,742 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist-Oblique.ttf', name='Tlwg Typist', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,743 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Norasi-Italic.otf', name='Norasi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,743 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Regular.ttf', name='Liberation Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,744 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Bold.ttf', name='Yrsa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,745 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-Bold.ttf', name='Amiri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,746 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/TlwgTypewriter-Bold.otf', name='Tlwg Typewriter', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,746 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-Italic.otf', name='STIX', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,747 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,748 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-BoldItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,748 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSerifItalic.ttf', name='FreeSerif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,749 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrecursor-italic.otf', name='TeX Gyre Cursor', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,749 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsD-Bold.otf', name='STIXIntegralsD', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,750 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Light.ttf', name='Yrsa', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,751 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Caladea-Regular.ttf', name='Caladea', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,752 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNewa-Regular.ttf', name='Noto Sans Newa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,753 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Tinos-Italic.ttf', name='Tinos', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,753 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnPilgia.ttf', name='UnPilgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,754 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ebgaramond/EBGaramond08-Italic.otf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,755 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSharada-Regular.ttf', name='Noto Sans Sharada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,755 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifMyanmar-Bold.ttf', name='Noto Serif Myanmar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,756 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Loma-Bold.otf', name='Loma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,757 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-deva-extra/kalimati.ttf', name='Kalimati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,758 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/teluguvijayam/PottiSreeramulu.ttf', name='Potti Sreeramulu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,758 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstFarsi.ttf', name='KacstFarsi', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,759 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeFourSym-Bold.otf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,760 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_R.otf', name='Linux Libertine O', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,760 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/tlwg/Laksaman.otf', name='Laksaman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,761 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifYezidi-Regular.ttf', name='Noto Serif Yezidi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,761 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/aakar-medium.ttf', name='aakar', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,762 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationMono-Italic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,762 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTelugu-Bold.ttf', name='Noto Serif Telugu', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,763 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/malayalam/AnjaliOldLipi-Regular.ttf', name='AnjaliOldLipi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,764 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/charis/CharisSIL-BoldItalic.ttf', name='Charis SIL', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,764 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmroman6-bold.otf', name='Latin Modern Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,765 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyreheroscn-regular.otf', name='TeX Gyre Heros Cn', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,765 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst/KacstQurn.ttf', name='KacstQurn', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,766 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Kinnari-BoldItalic.ttf', name='Kinnari', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,766 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSinhala-Bold.ttf', name='Noto Sans Sinhala', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,767 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Gayathri-Regular.otf', name='Gayathri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,768 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXSizeOneSym-Bold.otf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,768 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/dejavu/DejaVuSerifCondensed-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535\n", - "2024-10-29 15:33:08,771 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmono10-regular.otf', name='Latin Modern Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,772 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/GilliusADF-Cond.otf', name='Gillius ADF', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:08,772 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansSignWriting-Regular.ttf', name='Noto Sans SignWriting', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,773 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-LightItalic.ttf', name='Roboto Condensed', style='italic', variant='normal', weight=300, stretch='condensed', size='scalable')) = 11.344999999999999\n", - "2024-10-29 15:33:08,773 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/malayalam/Gayathri-Bold.otf', name='Gayathri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,774 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCarian-Regular.ttf', name='Noto Sans Carian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,774 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist-BoldOblique.ttf', name='Tlwg Typist', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,775 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-LightItalic.ttf', name='Open Sans', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,777 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansGunjalaGondi-Regular.ttf', name='Noto Sans Gunjala Gondi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,777 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-assamese/Lohit-Assamese.ttf', name='Lohit Assamese', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,778 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumPlus-Italic.ttf', name='Gentium Plus', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,778 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Bold.otf', name='Cabin', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,779 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifGurmukhi-Regular.ttf', name='Noto Serif Gurmukhi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,780 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/abyssinica/AbyssinicaSIL-Regular.ttf', name='Abyssinica SIL', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,781 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/kacst-one/KacstOne.ttf', name='KacstOne', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,781 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoLoopedThai-Bold.ttf', name='Noto Looped Thai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,782 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmsansquot8-oblique.otf', name='Latin Modern Sans Quotation', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,783 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-gujr-extra/padmaa-Bold.1.1.ttf', name='padmaa-Bold.1.1', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,784 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/lm/lmmonoprop10-oblique.otf', name='Latin Modern Mono Prop', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,784 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansChakma-Regular.ttf', name='Noto Sans Chakma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,785 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc', name='Noto Sans CJK JP', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,786 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond08-Italic.ttf', name='EB Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,786 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLimbu-Regular.ttf', name='Noto Sans Limbu', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,787 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamil-Regular.ttf', name='Noto Serif Tamil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,788 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-devanagari/Lohit-Devanagari.ttf', name='Lohit Devanagari', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,788 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/freefont/FreeSansBold.ttf', name='FreeSans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,789 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ebgaramond/EBGaramond12-AllSC.ttf', name='EB Garamond 12 All SC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,789 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/ipafont-mincho/ipam.ttf', name='IPAMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,790 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansLao-Bold.ttf', name='Noto Sans Lao', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,790 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTaiViet-Regular.ttf', name='Noto Sans Tai Viet', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,791 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/font-awesome/FontAwesome.otf', name='FontAwesome', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,792 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansMongolian-Regular.ttf', name='Noto Sans Mongolian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,792 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifEthiopic-Bold.ttf', name='Noto Serif Ethiopic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,793 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-beng-extra/LikhanNormal.ttf', name='Likhan', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,795 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/noto/NotoSerifCJK-Bold.ttc', name='Noto Serif CJK JP', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,795 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix-word/STIX-Bold.otf', name='STIX', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,796 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifNyiakengPuachueHmong-Regular.ttf', name='Noto Serif Hmong Nyiakeng', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,797 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansOsage-Regular.ttf', name='Noto Sans Osage', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,797 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lohit-gujarati/Lohit-Gujarati.ttf', name='Lohit Gujarati', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,798 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansCanadianAboriginal-Regular.ttf', name='Noto Sans Canadian Aboriginal', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,798 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifDevanagari-Bold.ttf', name='Noto Serif Devanagari', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,799 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/texmf/fonts/opentype/public/tex-gyre/texgyrebonum-bolditalic.otf', name='TeX Gyre Bonum', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,799 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKhojki-Bold.ttf', name='Noto Serif Khojki', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,801 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/Gargi/Gargi.ttf', name='Gargi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,802 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/AmiriQuranColored.ttf', name='Amiri Quran Colored', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,802 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/didot-classic/GFSDidotClassic.otf', name='GFS Didot Classic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,803 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/adf/AccanthisADFStdNo3-Regular.otf', name='Accanthis ADF Std No3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,804 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Norasi-Bold.ttf', name='Norasi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,804 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/open-sans/OpenSans-CondBold.ttf', name='Open Sans Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:08,805 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/croscore/Cousine-BoldItalic.ttf', name='Cousine', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,806 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/Garuda-Bold.ttf', name='Garuda', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,806 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerif-Italic.ttf', name='Noto Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,807 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifKannada-Regular.ttf', name='Noto Serif Kannada', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,808 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/urw-base35/NimbusSansNarrow-Regular.otf', name='Nimbus Sans Narrow', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25\n", - "2024-10-29 15:33:08,809 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifTamilSlanted-Regular.ttf', name='Noto Serif Tamil Slanted', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,809 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypist.ttf', name='Tlwg Typist', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,810 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/fonts-hosny-amiri/Amiri-Slanted.ttf', name='Amiri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,810 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/ubuntu/Ubuntu-RI.ttf', name='Ubuntu', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,811 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/tlwg/TlwgTypo-Bold.ttf', name='Tlwg Typo', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,812 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansNKo-Regular.ttf', name='Noto Sans NKo', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,812 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/unfonts-extra/UnTaza.ttf', name='UnTaza', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,813 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/artemisia/GFSArtemisiaBold.otf', name='GFS Artemisia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,813 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/cabin/Cabin-Medium.otf', name='Cabin', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,814 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-yrsa-rasa/Yrsa-Italic.ttf', name='Yrsa', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05\n", - "2024-10-29 15:33:08,816 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/fonts-japanese-mincho.ttf', name='IPAexMincho', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,816 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/linux-libertine/LinLibertine_RZ.otf', name='Linux Libertine O', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24\n", - "2024-10-29 15:33:08,817 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansDisplay-Bold.ttf', name='Noto Sans Display', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,817 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTamil-Regular.ttf', name='Noto Sans Tamil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,818 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/stix/STIXIntegralsUpD-Bold.otf', name='STIXIntegralsUpD', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,818 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/opentype/neohellenic/GFSNeohellenicBold.otf', name='GFS Neohellenic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,819 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansTakri-Regular.ttf', name='Noto Sans Takri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,820 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/lato/Lato-MediumItalic.ttf', name='Lato', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,820 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSerifLao-Bold.ttf', name='Noto Serif Lao', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335\n", - "2024-10-29 15:33:08,821 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoTTF/Roboto-LightItalic.ttf', name='Roboto', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,821 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation2/LiberationSerif-BoldItalic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,822 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-Italic.ttf', name='Gentium Book Plus', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145\n", - "2024-10-29 15:33:08,823 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansKayahLi-Regular.ttf', name='Noto Sans Kayah Li', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,823 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/crosextra/Carlito-BoldItalic.ttf', name='Carlito', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335\n", - "2024-10-29 15:33:08,824 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/roboto/unhinted/RobotoCondensed-Bold.ttf', name='Roboto Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535\n", - "2024-10-29 15:33:08,824 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/noto/NotoSansWarangCiti-Regular.ttf', name='Noto Sans Warang Citi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,827 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentium-basic/GenBasR.ttf', name='Gentium Basic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05\n", - "2024-10-29 15:33:08,827 - matplotlib.font_manager - DEBUG - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/gentiumplus/GentiumBookPlus-Regular.ttf', name='Gentium Book Plus', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145\n", - "2024-10-29 15:33:08,828 - matplotlib.font_manager - DEBUG - findfont: Matching sans\\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=24.0 to DejaVu Sans ('/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000.\n", - "2024-10-29 15:33:09,051 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig1_exp_dict/VennDiag_precursor_fdr_0.2_log_int_2.png\n", - "2024-10-29 15:33:09,121 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig1_exp_dict/VennDiag_precursor_fdr_0.2_log_int_2.svg\n" - ] - } - ], - "source": [ - "swaps_result.plot_overlap_with_MQ(show_ref=False, level=\"precursor\")" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 11:04:15,890 - result_analysis.result_analysis - INFO - Number of entries after merging 51799 and columns Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'MS1_frame_idx_right_ref', 'IsoMZ', 'IsoAbundance', 'mz_rank', 'mz_bin',\n", - " 'mz_length', 'pept_batch_idx', 'Decoy', 'pept_act_sum_filter_by_im',\n", - " 'log_sum_intensity'],\n", - " dtype='object', length=109)\n", - "2024-10-16 11:04:15,962 - utils.plot - INFO - Data: Intensity_log, pept_act_sum_filter_by_im_log, slope = 1.036, intercept = -0.696, Pearson's R = 0.942, Spearman's R = 0.931\n" - ] - }, - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - 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pept_act_sum_filter_by_im_log = 1.03551 * Intensity_log + -0.696351
R2=0.888013

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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "swaps_result.plot_intensity_corr(\n", - " interactive=True,\n", - " hover_data=[\n", - " \"mz_rank\",\n", - " \"Charge\",\n", - " \"Number of scans\",\n", - " \"Number of isotopic peaks\",\n", - " \"Retention length\",\n", - " \"Modified sequence\",\n", - " ],\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Candidate specific raw data visualization" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [], - "source": [ - "act_dir = os.path.join(cfg.RESULT_PATH, \"results\", \"activation\")\n", - "act_3d = sparse.load_npz(os.path.join(act_dir, \"im_rt_pept_act_coo_peptbatch0.npz\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 10:10:34,452 - root - INFO - Importing data from /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "2024-10-16 10:10:34,454 - root - INFO - Using .d import for /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "2024-10-16 10:10:34,455 - root - INFO - Reading frame metadata for /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/alphatims/bruker.py:237: FutureWarning:\n", - "\n", - "ChainedAssignmentError: behaviour will change in pandas 3.0!\n", - "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", - "A typical example is when you are setting values in a column of a DataFrame, like:\n", - "\n", - "df[\"col\"][row_indexer] = value\n", - "\n", - "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - "\n", - "\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/alphatims/bruker.py:238: FutureWarning:\n", - "\n", - "ChainedAssignmentError: behaviour will change in pandas 3.0!\n", - "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", - "A typical example is when you are setting values in a column of a DataFrame, like:\n", - "\n", - "df[\"col\"][row_indexer] = value\n", - "\n", - "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - "\n", - "\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/alphatims/bruker.py:239: FutureWarning:\n", - "\n", - "ChainedAssignmentError: behaviour will change in pandas 3.0!\n", - "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", - "A typical example is when you are setting values in a column of a DataFrame, like:\n", - "\n", - "df[\"col\"][row_indexer] = value\n", - "\n", - "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - "\n", - "\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/alphatims/bruker.py:240: FutureWarning:\n", - "\n", - "ChainedAssignmentError: behaviour will change in pandas 3.0!\n", - "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", - "A typical example is when you are setting values in a column of a DataFrame, like:\n", - "\n", - "df[\"col\"][row_indexer] = value\n", - "\n", - "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - "\n", - "\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/alphatims/bruker.py:241: FutureWarning:\n", - "\n", - "ChainedAssignmentError: behaviour will change in pandas 3.0!\n", - "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", - "A typical example is when you are setting values in a column of a DataFrame, like:\n", - "\n", - "df[\"col\"][row_indexer] = value\n", - "\n", - "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - "\n", - "\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/alphatims/bruker.py:242: FutureWarning:\n", - "\n", - "ChainedAssignmentError: behaviour will change in pandas 3.0!\n", - "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", - "A typical example is when you are setting values in a column of a DataFrame, like:\n", - "\n", - "df[\"col\"][row_indexer] = value\n", - "\n", - "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - "\n", - "\n", - "2024-10-16 10:10:40,498 - root - INFO - Reading 16,759 frames with 785,316,713 detector events for /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - " 0%| | 0/16759 [00:00 0\tNOP(arg=None, lineno=267)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=282)\n", - " 4\tLOAD_ATTR(arg=1, lineno=282)\n", - " 6\tLOAD_FAST(arg=0, lineno=282)\n", - " 8\tLOAD_GLOBAL(arg=0, lineno=282)\n", - " 10\tLOAD_ATTR(arg=2, lineno=282)\n", - " 12\tLOAD_CONST(arg=1, lineno=282)\n", - " 14\tCALL_FUNCTION_KW(arg=2, lineno=282)\n", - " 16\tSTORE_FAST(arg=1, lineno=282)\n", - " 18\tLOAD_GLOBAL(arg=0, lineno=283)\n", - " 20\tLOAD_ATTR(arg=1, lineno=283)\n", - " 22\tLOAD_FAST(arg=1, lineno=283)\n", - " 24\tLOAD_METHOD(arg=3, lineno=283)\n", - " 26\tLOAD_CONST(arg=2, lineno=283)\n", - " 28\tLOAD_CONST(arg=3, lineno=283)\n", - " 30\tCALL_METHOD(arg=2, lineno=283)\n", - " 32\tLOAD_ATTR(arg=4, lineno=283)\n", - " 34\tLOAD_METHOD(arg=5, lineno=283)\n", - " 36\tCALL_METHOD(arg=0, lineno=283)\n", - " 38\tLOAD_GLOBAL(arg=0, lineno=283)\n", - " 40\tLOAD_ATTR(arg=6, lineno=283)\n", - " 42\tLOAD_CONST(arg=1, lineno=283)\n", - " 44\tCALL_FUNCTION_KW(arg=2, lineno=283)\n", - " 46\tSTORE_FAST(arg=2, lineno=283)\n", - " 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230\tLOAD_CONST(arg=7, lineno=298)\n", - " 232\tBINARY_SUBTRACT(arg=None, lineno=298)\n", - " 234\tLOAD_FAST(arg=5, lineno=298)\n", - " 236\tBUILD_TUPLE(arg=3, lineno=298)\n", - " 238\tRETURN_VALUE(arg=None, lineno=298)\n", - "2024-10-16 10:10:42,273 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:42,274 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:42,275 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:42,276 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=267)\n", - "2024-10-16 10:10:42,277 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,278 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=282)\n", - "2024-10-16 10:10:42,279 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,279 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=282)\n", - "2024-10-16 10:10:42,280 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:10:42,281 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=0, lineno=282)\n", - "2024-10-16 10:10:42,282 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-10-16 10:10:42,283 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_GLOBAL(arg=0, lineno=282)\n", - "2024-10-16 10:10:42,284 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$decompressed_bytes6.2']\n", - "2024-10-16 10:10:42,284 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_ATTR(arg=2, lineno=282)\n", - "2024-10-16 10:10:42,285 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$decompressed_bytes6.2', '$8load_global.3']\n", - "2024-10-16 10:10:42,286 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_CONST(arg=1, lineno=282)\n", - "2024-10-16 10:10:42,287 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$decompressed_bytes6.2', '$10load_attr.4']\n", - "2024-10-16 10:10:42,288 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=CALL_FUNCTION_KW(arg=2, lineno=282)\n", - "2024-10-16 10:10:42,289 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$decompressed_bytes6.2', '$10load_attr.4', '$const12.5']\n", - "2024-10-16 10:10:42,290 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=STORE_FAST(arg=1, lineno=282)\n", - "2024-10-16 10:10:42,290 - numba.core.byteflow - DEBUG - stack ['$14call_function_kw.6']\n", - "2024-10-16 10:10:42,291 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_GLOBAL(arg=0, lineno=283)\n", - "2024-10-16 10:10:42,292 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,293 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_ATTR(arg=1, lineno=283)\n", - "2024-10-16 10:10:42,294 - numba.core.byteflow - DEBUG - stack ['$18load_global.7']\n", - "2024-10-16 10:10:42,295 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=1, lineno=283)\n", - "2024-10-16 10:10:42,295 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8']\n", - "2024-10-16 10:10:42,296 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_METHOD(arg=3, lineno=283)\n", - "2024-10-16 10:10:42,297 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$temp22.9']\n", - "2024-10-16 10:10:42,298 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_CONST(arg=2, lineno=283)\n", - "2024-10-16 10:10:42,299 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$24load_method.10']\n", - "2024-10-16 10:10:42,300 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_CONST(arg=3, lineno=283)\n", - "2024-10-16 10:10:42,300 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$24load_method.10', '$const26.11']\n", - "2024-10-16 10:10:42,301 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=CALL_METHOD(arg=2, lineno=283)\n", - "2024-10-16 10:10:42,302 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$24load_method.10', '$const26.11', '$const28.12']\n", - "2024-10-16 10:10:42,303 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_ATTR(arg=4, lineno=283)\n", - "2024-10-16 10:10:42,304 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$30call_method.13']\n", - "2024-10-16 10:10:42,305 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_METHOD(arg=5, lineno=283)\n", - "2024-10-16 10:10:42,305 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$32load_attr.14']\n", - "2024-10-16 10:10:42,306 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=CALL_METHOD(arg=0, lineno=283)\n", - "2024-10-16 10:10:42,307 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$34load_method.15']\n", - "2024-10-16 10:10:42,308 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_GLOBAL(arg=0, lineno=283)\n", - "2024-10-16 10:10:42,309 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$36call_method.16']\n", - "2024-10-16 10:10:42,310 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_ATTR(arg=6, lineno=283)\n", - "2024-10-16 10:10:42,310 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$36call_method.16', '$38load_global.17']\n", - "2024-10-16 10:10:42,311 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_CONST(arg=1, lineno=283)\n", - "2024-10-16 10:10:42,312 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$36call_method.16', '$40load_attr.18']\n", - "2024-10-16 10:10:42,313 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=CALL_FUNCTION_KW(arg=2, lineno=283)\n", - "2024-10-16 10:10:42,314 - numba.core.byteflow - DEBUG - stack ['$20load_attr.8', '$36call_method.16', '$40load_attr.18', '$const42.19']\n", - "2024-10-16 10:10:42,315 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=STORE_FAST(arg=2, lineno=283)\n", - "2024-10-16 10:10:42,315 - numba.core.byteflow - DEBUG - stack ['$44call_function_kw.20']\n", - "2024-10-16 10:10:42,316 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_FAST(arg=2, lineno=284)\n", - "2024-10-16 10:10:42,317 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,318 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_CONST(arg=4, lineno=284)\n", - "2024-10-16 10:10:42,319 - numba.core.byteflow - DEBUG - stack ['$buffer48.21']\n", - "2024-10-16 10:10:42,319 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=BINARY_SUBSCR(arg=None, lineno=284)\n", - "2024-10-16 10:10:42,320 - numba.core.byteflow - DEBUG - stack ['$buffer48.21', '$const50.22']\n", - "2024-10-16 10:10:42,321 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=STORE_FAST(arg=3, lineno=284)\n", - "2024-10-16 10:10:42,322 - numba.core.byteflow - DEBUG - stack ['$52binary_subscr.23']\n", - "2024-10-16 10:10:42,323 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_FAST(arg=2, lineno=285)\n", - "2024-10-16 10:10:42,324 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,324 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_CONST(arg=5, lineno=285)\n", - "2024-10-16 10:10:42,325 - numba.core.byteflow - DEBUG - stack ['$buffer56.24']\n", - "2024-10-16 10:10:42,326 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_FAST(arg=3, lineno=285)\n", - "2024-10-16 10:10:42,327 - numba.core.byteflow - DEBUG - stack ['$buffer56.24', '$const58.25']\n", - "2024-10-16 10:10:42,328 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=BUILD_SLICE(arg=2, lineno=285)\n", - "2024-10-16 10:10:42,329 - numba.core.byteflow - DEBUG - stack ['$buffer56.24', '$const58.25', '$scan_count60.26']\n", - "2024-10-16 10:10:42,329 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=BINARY_SUBSCR(arg=None, lineno=285)\n", - "2024-10-16 10:10:42,330 - numba.core.byteflow - DEBUG - stack ['$buffer56.24', '$62build_slice.28']\n", - "2024-10-16 10:10:42,331 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_METHOD(arg=7, lineno=285)\n", - "2024-10-16 10:10:42,332 - numba.core.byteflow - DEBUG - stack ['$64binary_subscr.29']\n", - "2024-10-16 10:10:42,333 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=CALL_METHOD(arg=0, lineno=285)\n", - "2024-10-16 10:10:42,333 - numba.core.byteflow - DEBUG - stack ['$66load_method.30']\n", - "2024-10-16 10:10:42,335 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=LOAD_CONST(arg=6, lineno=285)\n", - "2024-10-16 10:10:42,335 - numba.core.byteflow - DEBUG - stack ['$68call_method.31']\n", - "2024-10-16 10:10:42,336 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=BINARY_FLOOR_DIVIDE(arg=None, lineno=285)\n", - "2024-10-16 10:10:42,337 - numba.core.byteflow - DEBUG - stack ['$68call_method.31', '$const70.32']\n", - "2024-10-16 10:10:42,338 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=STORE_FAST(arg=4, lineno=285)\n", - "2024-10-16 10:10:42,339 - numba.core.byteflow - DEBUG - stack ['$72binary_floor_divide.33']\n", - "2024-10-16 10:10:42,340 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=LOAD_FAST(arg=2, lineno=286)\n", - "2024-10-16 10:10:42,340 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,341 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=3, lineno=286)\n", - "2024-10-16 10:10:42,342 - numba.core.byteflow - DEBUG - stack ['$buffer76.34']\n", - "2024-10-16 10:10:42,343 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_CONST(arg=7, lineno=286)\n", - "2024-10-16 10:10:42,344 - numba.core.byteflow - DEBUG - stack ['$buffer76.34', '$scan_count78.35']\n", - "2024-10-16 10:10:42,345 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=BINARY_ADD(arg=None, lineno=286)\n", - "2024-10-16 10:10:42,346 - numba.core.byteflow - DEBUG - stack ['$buffer76.34', '$scan_count78.35', '$const80.36']\n", - "2024-10-16 10:10:42,346 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=LOAD_CONST(arg=5, lineno=286)\n", - "2024-10-16 10:10:42,347 - numba.core.byteflow - DEBUG - stack ['$buffer76.34', '$82binary_add.37']\n", - "2024-10-16 10:10:42,348 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_CONST(arg=6, lineno=286)\n", - "2024-10-16 10:10:42,349 - numba.core.byteflow - DEBUG - stack ['$buffer76.34', '$82binary_add.37', '$const84.38']\n", - "2024-10-16 10:10:42,350 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=BUILD_SLICE(arg=3, lineno=286)\n", - "2024-10-16 10:10:42,351 - numba.core.byteflow - DEBUG - stack ['$buffer76.34', '$82binary_add.37', '$const84.38', '$const86.39']\n", - "2024-10-16 10:10:42,352 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=BINARY_SUBSCR(arg=None, lineno=286)\n", - "2024-10-16 10:10:42,352 - numba.core.byteflow - DEBUG - stack ['$buffer76.34', '$88build_slice.41']\n", - "2024-10-16 10:10:42,353 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=STORE_FAST(arg=5, lineno=286)\n", - "2024-10-16 10:10:42,354 - numba.core.byteflow - DEBUG - stack ['$90binary_subscr.42']\n", - "2024-10-16 10:10:42,355 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_GLOBAL(arg=8, lineno=287)\n", - "2024-10-16 10:10:42,356 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,357 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=LOAD_FAST(arg=5, lineno=287)\n", - "2024-10-16 10:10:42,358 - numba.core.byteflow - DEBUG - stack ['$94load_global.43']\n", - "2024-10-16 10:10:42,358 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=CALL_FUNCTION(arg=1, lineno=287)\n", - "2024-10-16 10:10:42,359 - numba.core.byteflow - DEBUG - stack ['$94load_global.43', '$intensities96.44']\n", - "2024-10-16 10:10:42,360 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_GLOBAL(arg=0, lineno=287)\n", - "2024-10-16 10:10:42,361 - numba.core.byteflow - DEBUG - stack ['$98call_function.45']\n", - "2024-10-16 10:10:42,362 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=LOAD_METHOD(arg=9, lineno=287)\n", - "2024-10-16 10:10:42,363 - numba.core.byteflow - DEBUG - stack ['$98call_function.45', '$100load_global.46']\n", - "2024-10-16 10:10:42,364 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=LOAD_FAST(arg=4, lineno=287)\n", - "2024-10-16 10:10:42,364 - numba.core.byteflow - DEBUG - stack ['$98call_function.45', '$102load_method.47']\n", - "2024-10-16 10:10:42,365 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_CONST(arg=7, lineno=287)\n", - "2024-10-16 10:10:42,366 - numba.core.byteflow - DEBUG - stack ['$98call_function.45', '$102load_method.47', '$scan_indices104.48']\n", - "2024-10-16 10:10:42,367 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_CONST(arg=5, lineno=287)\n", - "2024-10-16 10:10:42,368 - numba.core.byteflow - DEBUG - stack ['$98call_function.45', '$102load_method.47', '$scan_indices104.48', '$const106.49']\n", - "2024-10-16 10:10:42,369 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=BUILD_SLICE(arg=2, lineno=287)\n", - "2024-10-16 10:10:42,369 - numba.core.byteflow - DEBUG - stack ['$98call_function.45', '$102load_method.47', '$scan_indices104.48', '$const106.49', '$const108.50']\n", - "2024-10-16 10:10:42,370 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=BINARY_SUBSCR(arg=None, lineno=287)\n", - "2024-10-16 10:10:42,371 - numba.core.byteflow - DEBUG - stack ['$98call_function.45', '$102load_method.47', '$scan_indices104.48', '$110build_slice.52']\n", - "2024-10-16 10:10:42,372 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=CALL_METHOD(arg=1, lineno=287)\n", - "2024-10-16 10:10:42,373 - numba.core.byteflow - DEBUG - stack ['$98call_function.45', '$102load_method.47', '$112binary_subscr.53']\n", - "2024-10-16 10:10:42,374 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=BINARY_SUBTRACT(arg=None, lineno=287)\n", - "2024-10-16 10:10:42,375 - numba.core.byteflow - DEBUG - stack ['$98call_function.45', '$114call_method.54']\n", - "2024-10-16 10:10:42,375 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=STORE_FAST(arg=6, lineno=287)\n", - "2024-10-16 10:10:42,376 - numba.core.byteflow - DEBUG - stack ['$116binary_subtract.55']\n", - "2024-10-16 10:10:42,377 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=4, lineno=288)\n", - "2024-10-16 10:10:42,378 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,379 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_CONST(arg=7, lineno=288)\n", - "2024-10-16 10:10:42,379 - numba.core.byteflow - DEBUG - stack ['$scan_indices120.56']\n", - "2024-10-16 10:10:42,380 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=LOAD_CONST(arg=5, lineno=288)\n", - "2024-10-16 10:10:42,381 - numba.core.byteflow - DEBUG - stack ['$scan_indices120.56', '$const122.57']\n", - "2024-10-16 10:10:42,382 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=BUILD_SLICE(arg=2, lineno=288)\n", - "2024-10-16 10:10:42,383 - numba.core.byteflow - DEBUG - stack ['$scan_indices120.56', '$const122.57', '$const124.58']\n", - "2024-10-16 10:10:42,383 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=BINARY_SUBSCR(arg=None, lineno=288)\n", - "2024-10-16 10:10:42,384 - numba.core.byteflow - DEBUG - stack ['$scan_indices120.56', '$126build_slice.60']\n", - "2024-10-16 10:10:42,385 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=LOAD_FAST(arg=4, lineno=288)\n", - "2024-10-16 10:10:42,386 - numba.core.byteflow - DEBUG - stack ['$128binary_subscr.61']\n", - "2024-10-16 10:10:42,387 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_CONST(arg=5, lineno=288)\n", - "2024-10-16 10:10:42,387 - numba.core.byteflow - DEBUG - stack ['$128binary_subscr.61', '$scan_indices130.62']\n", - "2024-10-16 10:10:42,388 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_CONST(arg=3, lineno=288)\n", - "2024-10-16 10:10:42,389 - numba.core.byteflow - DEBUG - stack ['$128binary_subscr.61', '$scan_indices130.62', '$const132.63']\n", - "2024-10-16 10:10:42,390 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BUILD_SLICE(arg=2, lineno=288)\n", - "2024-10-16 10:10:42,391 - numba.core.byteflow - DEBUG - stack ['$128binary_subscr.61', '$scan_indices130.62', '$const132.63', '$const134.64']\n", - "2024-10-16 10:10:42,391 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=STORE_SUBSCR(arg=None, lineno=288)\n", - "2024-10-16 10:10:42,392 - numba.core.byteflow - DEBUG - stack ['$128binary_subscr.61', '$scan_indices130.62', '$136build_slice.66']\n", - "2024-10-16 10:10:42,393 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=LOAD_FAST(arg=6, lineno=289)\n", - "2024-10-16 10:10:42,394 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,395 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=4, lineno=289)\n", - "2024-10-16 10:10:42,395 - numba.core.byteflow - DEBUG - stack ['$last_scan140.67']\n", - "2024-10-16 10:10:42,396 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=LOAD_CONST(arg=3, lineno=289)\n", - "2024-10-16 10:10:42,397 - numba.core.byteflow - DEBUG - stack ['$last_scan140.67', '$scan_indices142.68']\n", - "2024-10-16 10:10:42,398 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=STORE_SUBSCR(arg=None, lineno=289)\n", - "2024-10-16 10:10:42,399 - numba.core.byteflow - DEBUG - stack ['$last_scan140.67', '$scan_indices142.68', '$const144.69']\n", - "2024-10-16 10:10:42,399 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=2, lineno=290)\n", - "2024-10-16 10:10:42,400 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,401 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=LOAD_FAST(arg=3, lineno=290)\n", - "2024-10-16 10:10:42,402 - numba.core.byteflow - DEBUG - stack ['$buffer148.70']\n", - "2024-10-16 10:10:42,403 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=LOAD_CONST(arg=5, lineno=290)\n", - "2024-10-16 10:10:42,403 - numba.core.byteflow - DEBUG - stack ['$buffer148.70', '$scan_count150.71']\n", - "2024-10-16 10:10:42,404 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_CONST(arg=6, lineno=290)\n", - "2024-10-16 10:10:42,405 - numba.core.byteflow - DEBUG - stack ['$buffer148.70', '$scan_count150.71', '$const152.72']\n", - "2024-10-16 10:10:42,406 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=BUILD_SLICE(arg=3, lineno=290)\n", - "2024-10-16 10:10:42,407 - numba.core.byteflow - DEBUG - stack ['$buffer148.70', '$scan_count150.71', '$const152.72', '$const154.73']\n", - "2024-10-16 10:10:42,407 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=BINARY_SUBSCR(arg=None, lineno=290)\n", - "2024-10-16 10:10:42,408 - numba.core.byteflow - DEBUG - stack ['$buffer148.70', '$156build_slice.75']\n", - "2024-10-16 10:10:42,409 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=LOAD_METHOD(arg=7, lineno=290)\n", - "2024-10-16 10:10:42,410 - numba.core.byteflow - DEBUG - stack ['$158binary_subscr.76']\n", - "2024-10-16 10:10:42,411 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=CALL_METHOD(arg=0, lineno=290)\n", - "2024-10-16 10:10:42,411 - numba.core.byteflow - DEBUG - stack ['$160load_method.77']\n", - "2024-10-16 10:10:42,412 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=STORE_FAST(arg=7, lineno=290)\n", - "2024-10-16 10:10:42,413 - numba.core.byteflow - DEBUG - stack ['$162call_method.78']\n", - "2024-10-16 10:10:42,414 - numba.core.byteflow - DEBUG - dispatch pc=166, inst=LOAD_CONST(arg=4, lineno=291)\n", - "2024-10-16 10:10:42,414 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,415 - numba.core.byteflow - DEBUG - dispatch pc=168, inst=STORE_FAST(arg=8, lineno=291)\n", - "2024-10-16 10:10:42,416 - numba.core.byteflow - DEBUG - stack ['$const166.79']\n", - "2024-10-16 10:10:42,417 - numba.core.byteflow - DEBUG - dispatch pc=170, inst=LOAD_FAST(arg=4, lineno=292)\n", - "2024-10-16 10:10:42,418 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,418 - numba.core.byteflow - DEBUG - dispatch pc=172, inst=GET_ITER(arg=None, lineno=292)\n", - "2024-10-16 10:10:42,419 - numba.core.byteflow - DEBUG - stack ['$scan_indices170.80']\n", - "2024-10-16 10:10:42,420 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=174, stack=('$172get_iter.81',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:42,421 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=174 nstack_initial=1)])\n", - "2024-10-16 10:10:42,421 - numba.core.byteflow - DEBUG - stack: ['$phi174.0']\n", - "2024-10-16 10:10:42,422 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=174 nstack_initial=1)\n", - "2024-10-16 10:10:42,423 - numba.core.byteflow - DEBUG - dispatch pc=174, inst=FOR_ITER(arg=25, lineno=292)\n", - "2024-10-16 10:10:42,424 - numba.core.byteflow - DEBUG - stack ['$phi174.0']\n", - "2024-10-16 10:10:42,425 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=226, stack=(), blockstack=(), npush=0), Edge(pc=176, stack=('$phi174.0', '$174for_iter.2'), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:42,425 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=226 nstack_initial=0), State(pc_initial=176 nstack_initial=2)])\n", - "2024-10-16 10:10:42,426 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:42,427 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=226 nstack_initial=0)\n", - "2024-10-16 10:10:42,428 - numba.core.byteflow - DEBUG - dispatch pc=226, inst=LOAD_FAST(arg=4, lineno=298)\n", - "2024-10-16 10:10:42,428 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:42,429 - numba.core.byteflow - DEBUG - dispatch pc=228, inst=LOAD_FAST(arg=7, lineno=298)\n", - "2024-10-16 10:10:42,430 - numba.core.byteflow - DEBUG - stack ['$scan_indices226.0']\n", - "2024-10-16 10:10:42,431 - numba.core.byteflow - DEBUG - dispatch pc=230, inst=LOAD_CONST(arg=7, lineno=298)\n", - "2024-10-16 10:10:42,432 - numba.core.byteflow - DEBUG - stack ['$scan_indices226.0', '$tof_indices228.1']\n", - "2024-10-16 10:10:42,432 - numba.core.byteflow - DEBUG - dispatch pc=232, inst=BINARY_SUBTRACT(arg=None, lineno=298)\n", - "2024-10-16 10:10:42,433 - numba.core.byteflow - DEBUG - stack ['$scan_indices226.0', '$tof_indices228.1', '$const230.2']\n", - "2024-10-16 10:10:42,434 - numba.core.byteflow - DEBUG - dispatch pc=234, inst=LOAD_FAST(arg=5, lineno=298)\n", - "2024-10-16 10:10:42,434 - numba.core.byteflow - DEBUG - stack ['$scan_indices226.0', '$232binary_subtract.3']\n", - "2024-10-16 10:10:42,435 - numba.core.byteflow - DEBUG - dispatch pc=236, inst=BUILD_TUPLE(arg=3, lineno=298)\n", - "2024-10-16 10:10:42,436 - numba.core.byteflow - DEBUG - stack ['$scan_indices226.0', '$232binary_subtract.3', '$intensities234.4']\n", - "2024-10-16 10:10:42,437 - numba.core.byteflow - DEBUG - dispatch pc=238, inst=RETURN_VALUE(arg=None, lineno=298)\n", - "2024-10-16 10:10:42,437 - numba.core.byteflow - DEBUG - stack ['$236build_tuple.5']\n", - "2024-10-16 10:10:42,438 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:42,439 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=176 nstack_initial=2)])\n", - "2024-10-16 10:10:42,440 - numba.core.byteflow - DEBUG - stack: ['$phi176.0', '$phi176.1']\n", - "2024-10-16 10:10:42,440 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=176 nstack_initial=2)\n", - "2024-10-16 10:10:42,441 - numba.core.byteflow - DEBUG - dispatch pc=176, inst=STORE_FAST(arg=9, lineno=292)\n", - "2024-10-16 10:10:42,442 - numba.core.byteflow - DEBUG - stack ['$phi176.0', '$phi176.1']\n", - "2024-10-16 10:10:42,442 - numba.core.byteflow - DEBUG - dispatch pc=178, inst=LOAD_CONST(arg=4, lineno=293)\n", - "2024-10-16 10:10:42,443 - numba.core.byteflow - DEBUG - stack ['$phi176.0']\n", - "2024-10-16 10:10:42,444 - numba.core.byteflow - DEBUG - dispatch pc=180, inst=STORE_FAST(arg=10, lineno=293)\n", - "2024-10-16 10:10:42,445 - numba.core.byteflow - DEBUG - stack ['$phi176.0', '$const178.2']\n", - "2024-10-16 10:10:42,445 - numba.core.byteflow - DEBUG - dispatch pc=182, inst=LOAD_GLOBAL(arg=10, lineno=294)\n", - "2024-10-16 10:10:42,446 - numba.core.byteflow - DEBUG - stack ['$phi176.0']\n", - "2024-10-16 10:10:42,447 - numba.core.byteflow - DEBUG - dispatch pc=184, inst=LOAD_FAST(arg=9, lineno=294)\n", - "2024-10-16 10:10:42,448 - numba.core.byteflow - DEBUG - stack ['$phi176.0', '$182load_global.3']\n", - "2024-10-16 10:10:42,448 - numba.core.byteflow - DEBUG - dispatch pc=186, inst=CALL_FUNCTION(arg=1, lineno=294)\n", - "2024-10-16 10:10:42,449 - numba.core.byteflow - DEBUG - stack ['$phi176.0', '$182load_global.3', '$size184.4']\n", - "2024-10-16 10:10:42,450 - numba.core.byteflow - DEBUG - dispatch pc=188, inst=GET_ITER(arg=None, lineno=294)\n", - "2024-10-16 10:10:42,451 - numba.core.byteflow - DEBUG - stack ['$phi176.0', '$186call_function.5']\n", - "2024-10-16 10:10:42,451 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=190, stack=('$phi176.0', '$188get_iter.6'), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:42,452 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=190 nstack_initial=2)])\n", - "2024-10-16 10:10:42,453 - numba.core.byteflow - DEBUG - stack: ['$phi190.0', '$phi190.1']\n", - "2024-10-16 10:10:42,454 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=190 nstack_initial=2)\n", - "2024-10-16 10:10:42,454 - numba.core.byteflow - DEBUG - dispatch pc=190, inst=FOR_ITER(arg=16, lineno=294)\n", - "2024-10-16 10:10:42,455 - numba.core.byteflow - DEBUG - stack ['$phi190.0', '$phi190.1']\n", - "2024-10-16 10:10:42,456 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=224, stack=('$phi190.0',), blockstack=(), npush=0), Edge(pc=192, stack=('$phi190.0', '$phi190.1', '$190for_iter.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:42,457 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=224 nstack_initial=1), State(pc_initial=192 nstack_initial=3)])\n", - "2024-10-16 10:10:42,457 - numba.core.byteflow - DEBUG - stack: ['$phi224.0']\n", - "2024-10-16 10:10:42,458 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=224 nstack_initial=1)\n", - "2024-10-16 10:10:42,459 - numba.core.byteflow - DEBUG - dispatch pc=224, inst=JUMP_ABSOLUTE(arg=88, lineno=294)\n", - "2024-10-16 10:10:42,460 - numba.core.byteflow - DEBUG - stack ['$phi224.0']\n", - "2024-10-16 10:10:42,460 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=174, stack=('$phi224.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:42,461 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=192 nstack_initial=3), State(pc_initial=174 nstack_initial=1)])\n", - "2024-10-16 10:10:42,462 - numba.core.byteflow - DEBUG - stack: ['$phi192.0', '$phi192.1', '$phi192.2']\n", - "2024-10-16 10:10:42,463 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=192 nstack_initial=3)\n", - "2024-10-16 10:10:42,463 - numba.core.byteflow - DEBUG - dispatch pc=192, inst=STORE_FAST(arg=11, lineno=294)\n", - "2024-10-16 10:10:42,464 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2']\n", - "2024-10-16 10:10:42,465 - numba.core.byteflow - DEBUG - dispatch pc=194, inst=LOAD_FAST(arg=10, lineno=295)\n", - "2024-10-16 10:10:42,466 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1']\n", - "2024-10-16 10:10:42,466 - numba.core.byteflow - DEBUG - dispatch pc=196, inst=LOAD_FAST(arg=7, lineno=295)\n", - "2024-10-16 10:10:42,467 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$current_sum194.3']\n", - "2024-10-16 10:10:42,468 - numba.core.byteflow - DEBUG - dispatch pc=198, inst=LOAD_FAST(arg=8, lineno=295)\n", - "2024-10-16 10:10:42,469 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$current_sum194.3', '$tof_indices196.4']\n", - "2024-10-16 10:10:42,469 - numba.core.byteflow - DEBUG - dispatch pc=200, inst=BINARY_SUBSCR(arg=None, lineno=295)\n", - "2024-10-16 10:10:42,470 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$current_sum194.3', '$tof_indices196.4', '$index198.5']\n", - "2024-10-16 10:10:42,471 - numba.core.byteflow - DEBUG - dispatch pc=202, inst=INPLACE_ADD(arg=None, lineno=295)\n", - "2024-10-16 10:10:42,471 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$current_sum194.3', '$200binary_subscr.6']\n", - "2024-10-16 10:10:42,472 - numba.core.byteflow - DEBUG - dispatch pc=204, inst=STORE_FAST(arg=10, lineno=295)\n", - "2024-10-16 10:10:42,473 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$202inplace_add.7']\n", - "2024-10-16 10:10:42,473 - numba.core.byteflow - DEBUG - dispatch pc=206, inst=LOAD_FAST(arg=10, lineno=296)\n", - "2024-10-16 10:10:42,474 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1']\n", - "2024-10-16 10:10:42,475 - numba.core.byteflow - DEBUG - dispatch pc=208, inst=LOAD_FAST(arg=7, lineno=296)\n", - "2024-10-16 10:10:42,475 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$current_sum206.8']\n", - "2024-10-16 10:10:42,476 - numba.core.byteflow - DEBUG - dispatch pc=210, inst=LOAD_FAST(arg=8, lineno=296)\n", - "2024-10-16 10:10:42,477 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$current_sum206.8', '$tof_indices208.9']\n", - "2024-10-16 10:10:42,478 - numba.core.byteflow - DEBUG - dispatch pc=212, inst=STORE_SUBSCR(arg=None, lineno=296)\n", - "2024-10-16 10:10:42,478 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$current_sum206.8', '$tof_indices208.9', '$index210.10']\n", - "2024-10-16 10:10:42,479 - numba.core.byteflow - DEBUG - dispatch pc=214, inst=LOAD_FAST(arg=8, lineno=297)\n", - "2024-10-16 10:10:42,480 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1']\n", - "2024-10-16 10:10:42,480 - numba.core.byteflow - DEBUG - dispatch pc=216, inst=LOAD_CONST(arg=7, lineno=297)\n", - "2024-10-16 10:10:42,481 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$index214.11']\n", - "2024-10-16 10:10:42,482 - numba.core.byteflow - DEBUG - dispatch pc=218, inst=INPLACE_ADD(arg=None, lineno=297)\n", - "2024-10-16 10:10:42,482 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$index214.11', '$const216.12']\n", - "2024-10-16 10:10:42,483 - numba.core.byteflow - DEBUG - dispatch pc=220, inst=STORE_FAST(arg=8, lineno=297)\n", - "2024-10-16 10:10:42,484 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$218inplace_add.13']\n", - "2024-10-16 10:10:42,485 - numba.core.byteflow - DEBUG - dispatch pc=222, inst=JUMP_ABSOLUTE(arg=96, lineno=297)\n", - "2024-10-16 10:10:42,485 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1']\n", - "2024-10-16 10:10:42,486 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=190, stack=('$phi192.0', '$phi192.1'), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:42,487 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=174 nstack_initial=1), State(pc_initial=190 nstack_initial=2)])\n", - "2024-10-16 10:10:42,487 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=190 nstack_initial=2)])\n", - "2024-10-16 10:10:42,488 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:42,489 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=174 nstack_initial=1): {'$phi174.0'},\n", - " State(pc_initial=176 nstack_initial=2): {'$phi176.1'},\n", - " State(pc_initial=190 nstack_initial=2): {'$phi190.1'},\n", - " State(pc_initial=192 nstack_initial=3): {'$phi192.2'},\n", - " State(pc_initial=224 nstack_initial=1): set(),\n", - " State(pc_initial=226 nstack_initial=0): set()})\n", - "2024-10-16 10:10:42,490 - numba.core.byteflow - DEBUG - defmap: {'$phi174.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi176.1': State(pc_initial=174 nstack_initial=1),\n", - " '$phi190.1': State(pc_initial=176 nstack_initial=2),\n", - " '$phi192.2': State(pc_initial=190 nstack_initial=2)}\n", - "2024-10-16 10:10:42,491 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi174.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi224.0',\n", - " State(pc_initial=224 nstack_initial=1))},\n", - " '$phi176.0': {('$phi174.0',\n", - " State(pc_initial=174 nstack_initial=1))},\n", - " '$phi176.1': {('$174for_iter.2',\n", - " State(pc_initial=174 nstack_initial=1))},\n", - " '$phi190.0': {('$phi176.0',\n", - " State(pc_initial=176 nstack_initial=2)),\n", - " ('$phi192.0',\n", - " State(pc_initial=192 nstack_initial=3))},\n", - " '$phi190.1': {('$188get_iter.6',\n", - " State(pc_initial=176 nstack_initial=2)),\n", - " ('$phi192.1',\n", - " State(pc_initial=192 nstack_initial=3))},\n", - " '$phi192.0': {('$phi190.0',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi192.1': {('$phi190.1',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi192.2': {('$190for_iter.3',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi224.0': {('$phi190.0',\n", - " State(pc_initial=190 nstack_initial=2))}})\n", - "2024-10-16 10:10:42,493 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi174.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi190.0',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi176.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi190.0',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi176.1': {('$174for_iter.2',\n", - " State(pc_initial=174 nstack_initial=1))},\n", - " '$phi190.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi190.0',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi190.1': {('$188get_iter.6',\n", - " State(pc_initial=176 nstack_initial=2)),\n", - " ('$phi190.1',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi192.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi192.1': {('$188get_iter.6',\n", - " State(pc_initial=176 nstack_initial=2))},\n", - " '$phi192.2': {('$190for_iter.3',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi224.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))}})\n", - "2024-10-16 10:10:42,528 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi174.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi176.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi176.1': {('$174for_iter.2',\n", - " State(pc_initial=174 nstack_initial=1))},\n", - " '$phi190.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi190.1': {('$188get_iter.6',\n", - " State(pc_initial=176 nstack_initial=2))},\n", - " '$phi192.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi192.1': {('$188get_iter.6',\n", - " State(pc_initial=176 nstack_initial=2))},\n", - " '$phi192.2': {('$190for_iter.3',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi224.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))}})\n", - "2024-10-16 10:10:42,529 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi174.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi176.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi176.1': {('$174for_iter.2',\n", - " State(pc_initial=174 nstack_initial=1))},\n", - " '$phi190.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi190.1': {('$188get_iter.6',\n", - " State(pc_initial=176 nstack_initial=2))},\n", - " '$phi192.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi192.1': {('$188get_iter.6',\n", - " State(pc_initial=176 nstack_initial=2))},\n", - " '$phi192.2': {('$190for_iter.3',\n", - " State(pc_initial=190 nstack_initial=2))},\n", - " '$phi224.0': {('$172get_iter.81',\n", - " State(pc_initial=0 nstack_initial=0))}})\n", - "2024-10-16 10:10:42,531 - numba.core.byteflow - DEBUG - keep phismap: {'$phi174.0': {('$172get_iter.81', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi176.1': {('$174for_iter.2', State(pc_initial=174 nstack_initial=1))},\n", - " '$phi190.1': {('$188get_iter.6', State(pc_initial=176 nstack_initial=2))},\n", - " '$phi192.2': {('$190for_iter.3', State(pc_initial=190 nstack_initial=2))}}\n", - "2024-10-16 10:10:42,531 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi174.0': '$172get_iter.81'},\n", - " State(pc_initial=174 nstack_initial=1): {'$phi176.1': '$174for_iter.2'},\n", - " State(pc_initial=176 nstack_initial=2): {'$phi190.1': '$188get_iter.6'},\n", - " State(pc_initial=190 nstack_initial=2): {'$phi192.2': '$190for_iter.3'}})\n", - "2024-10-16 10:10:42,533 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:42,534 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'res': '$decompressed_bytes6.2'}), (8, {'res': '$8load_global.3'}), (10, {'item': '$8load_global.3', 'res': '$10load_attr.4'}), (12, {'res': '$const12.5'}), (14, {'func': '$4load_attr.1', 'args': ['$decompressed_bytes6.2', '$10load_attr.4'], 'names': '$const12.5', 'res': '$14call_function_kw.6'}), (16, {'value': '$14call_function_kw.6'}), (18, {'res': '$18load_global.7'}), (20, {'item': '$18load_global.7', 'res': '$20load_attr.8'}), (22, {'res': '$temp22.9'}), (24, {'item': '$temp22.9', 'res': '$24load_method.10'}), (26, {'res': '$const26.11'}), (28, {'res': '$const28.12'}), (30, {'func': '$24load_method.10', 'args': ['$const26.11', '$const28.12'], 'res': '$30call_method.13'}), (32, {'item': '$30call_method.13', 'res': '$32load_attr.14'}), (34, {'item': '$32load_attr.14', 'res': '$34load_method.15'}), (36, {'func': '$34load_method.15', 'args': [], 'res': '$36call_method.16'}), (38, {'res': '$38load_global.17'}), (40, {'item': '$38load_global.17', 'res': '$40load_attr.18'}), (42, {'res': '$const42.19'}), (44, {'func': '$20load_attr.8', 'args': ['$36call_method.16', '$40load_attr.18'], 'names': '$const42.19', 'res': '$44call_function_kw.20'}), (46, {'value': '$44call_function_kw.20'}), (48, {'res': '$buffer48.21'}), (50, {'res': '$const50.22'}), (52, {'index': '$const50.22', 'target': '$buffer48.21', 'res': '$52binary_subscr.23'}), (54, {'value': '$52binary_subscr.23'}), (56, {'res': '$buffer56.24'}), (58, {'res': '$const58.25'}), (60, {'res': '$scan_count60.26'}), (62, {'start': '$const58.25', 'stop': '$scan_count60.26', 'step': None, 'res': '$62build_slice.28', 'slicevar': '$62build_slice.27'}), (64, {'index': '$62build_slice.28', 'target': '$buffer56.24', 'res': '$64binary_subscr.29'}), (66, {'item': '$64binary_subscr.29', 'res': '$66load_method.30'}), (68, {'func': '$66load_method.30', 'args': [], 'res': '$68call_method.31'}), (70, {'res': '$const70.32'}), (72, {'lhs': '$68call_method.31', 'rhs': '$const70.32', 'res': '$72binary_floor_divide.33'}), (74, {'value': '$72binary_floor_divide.33'}), (76, {'res': '$buffer76.34'}), (78, {'res': '$scan_count78.35'}), (80, {'res': '$const80.36'}), (82, {'lhs': '$scan_count78.35', 'rhs': '$const80.36', 'res': '$82binary_add.37'}), (84, {'res': '$const84.38'}), (86, {'res': '$const86.39'}), (88, {'start': '$82binary_add.37', 'stop': '$const84.38', 'step': '$const86.39', 'res': '$88build_slice.41', 'slicevar': '$88build_slice.40'}), (90, {'index': '$88build_slice.41', 'target': '$buffer76.34', 'res': '$90binary_subscr.42'}), (92, {'value': '$90binary_subscr.42'}), (94, {'res': '$94load_global.43'}), (96, {'res': '$intensities96.44'}), (98, {'func': '$94load_global.43', 'args': ['$intensities96.44'], 'res': '$98call_function.45'}), (100, {'res': '$100load_global.46'}), (102, {'item': '$100load_global.46', 'res': '$102load_method.47'}), (104, {'res': '$scan_indices104.48'}), (106, {'res': '$const106.49'}), (108, {'res': '$const108.50'}), (110, {'start': '$const106.49', 'stop': '$const108.50', 'step': None, 'res': '$110build_slice.52', 'slicevar': '$110build_slice.51'}), (112, {'index': '$110build_slice.52', 'target': '$scan_indices104.48', 'res': '$112binary_subscr.53'}), (114, {'func': '$102load_method.47', 'args': ['$112binary_subscr.53'], 'res': '$114call_method.54'}), (116, {'lhs': '$98call_function.45', 'rhs': '$114call_method.54', 'res': '$116binary_subtract.55'}), (118, {'value': '$116binary_subtract.55'}), (120, {'res': '$scan_indices120.56'}), (122, {'res': '$const122.57'}), (124, {'res': '$const124.58'}), (126, {'start': '$const122.57', 'stop': '$const124.58', 'step': None, 'res': '$126build_slice.60', 'slicevar': '$126build_slice.59'}), (128, {'index': '$126build_slice.60', 'target': '$scan_indices120.56', 'res': '$128binary_subscr.61'}), (130, {'res': '$scan_indices130.62'}), (132, {'res': '$const132.63'}), (134, {'res': '$const134.64'}), (136, {'start': '$const132.63', 'stop': '$const134.64', 'step': None, 'res': '$136build_slice.66', 'slicevar': '$136build_slice.65'}), (138, {'target': '$scan_indices130.62', 'index': '$136build_slice.66', 'value': '$128binary_subscr.61'}), (140, {'res': '$last_scan140.67'}), (142, {'res': '$scan_indices142.68'}), (144, {'res': '$const144.69'}), (146, {'target': '$scan_indices142.68', 'index': '$const144.69', 'value': '$last_scan140.67'}), (148, {'res': '$buffer148.70'}), (150, {'res': '$scan_count150.71'}), (152, {'res': '$const152.72'}), (154, {'res': '$const154.73'}), (156, {'start': '$scan_count150.71', 'stop': '$const152.72', 'step': '$const154.73', 'res': '$156build_slice.75', 'slicevar': '$156build_slice.74'}), (158, {'index': '$156build_slice.75', 'target': '$buffer148.70', 'res': '$158binary_subscr.76'}), (160, {'item': '$158binary_subscr.76', 'res': '$160load_method.77'}), (162, {'func': '$160load_method.77', 'args': [], 'res': '$162call_method.78'}), (164, {'value': '$162call_method.78'}), (166, {'res': '$const166.79'}), (168, {'value': '$const166.79'}), (170, {'res': '$scan_indices170.80'}), (172, {'value': '$scan_indices170.80', 'res': '$172get_iter.81'})), outgoing_phis={'$phi174.0': '$172get_iter.81'}, blockstack=(), active_try_block=None, outgoing_edgepushed={174: ('$172get_iter.81',)})\n", - "2024-10-16 10:10:42,534 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=174 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((174, {'iterator': '$phi174.0', 'pair': '$174for_iter.1', 'indval': '$174for_iter.2', 'pred': '$174for_iter.3'}),), outgoing_phis={'$phi176.1': '$174for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={226: (), 176: ('$phi174.0', '$174for_iter.2')})\n", - "2024-10-16 10:10:42,535 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=176 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((176, {'value': '$phi176.1'}), (178, {'res': '$const178.2'}), (180, {'value': '$const178.2'}), (182, {'res': '$182load_global.3'}), (184, {'res': '$size184.4'}), (186, {'func': '$182load_global.3', 'args': ['$size184.4'], 'res': '$186call_function.5'}), (188, {'value': '$186call_function.5', 'res': '$188get_iter.6'})), outgoing_phis={'$phi190.1': '$188get_iter.6'}, blockstack=(), active_try_block=None, outgoing_edgepushed={190: ('$phi176.0', '$188get_iter.6')})\n", - "2024-10-16 10:10:42,536 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=190 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((190, {'iterator': '$phi190.1', 'pair': '$190for_iter.2', 'indval': '$190for_iter.3', 'pred': '$190for_iter.4'}),), outgoing_phis={'$phi192.2': '$190for_iter.3'}, blockstack=(), active_try_block=None, outgoing_edgepushed={224: ('$phi190.0',), 192: ('$phi190.0', '$phi190.1', '$190for_iter.3')})\n", - "2024-10-16 10:10:42,536 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=192 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((192, {'value': '$phi192.2'}), (194, {'res': '$current_sum194.3'}), (196, {'res': '$tof_indices196.4'}), (198, {'res': '$index198.5'}), (200, {'index': '$index198.5', 'target': '$tof_indices196.4', 'res': '$200binary_subscr.6'}), (202, {'lhs': '$current_sum194.3', 'rhs': '$200binary_subscr.6', 'res': '$202inplace_add.7'}), (204, {'value': '$202inplace_add.7'}), (206, {'res': '$current_sum206.8'}), (208, {'res': '$tof_indices208.9'}), (210, {'res': '$index210.10'}), (212, {'target': '$tof_indices208.9', 'index': '$index210.10', 'value': '$current_sum206.8'}), (214, {'res': '$index214.11'}), (216, {'res': '$const216.12'}), (218, {'lhs': '$index214.11', 'rhs': '$const216.12', 'res': '$218inplace_add.13'}), (220, {'value': '$218inplace_add.13'}), (222, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={190: ('$phi192.0', '$phi192.1')})\n", - "2024-10-16 10:10:42,538 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=224 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((224, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={174: ('$phi224.0',)})\n", - "2024-10-16 10:10:42,538 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=226 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((226, {'res': '$scan_indices226.0'}), (228, {'res': '$tof_indices228.1'}), (230, {'res': '$const230.2'}), (232, {'lhs': '$tof_indices228.1', 'rhs': '$const230.2', 'res': '$232binary_subtract.3'}), (234, {'res': '$intensities234.4'}), (236, {'items': ['$scan_indices226.0', '$232binary_subtract.3', '$intensities234.4'], 'res': '$236build_tuple.5'}), (238, {'retval': '$236build_tuple.5', 'castval': '$238return_value.6'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:42,547 - numba.core.interpreter - DEBUG - label 0:\n", - " decompressed_bytes = arg(0, name=decompressed_bytes) ['decompressed_bytes']\n", - " $2load_global.0 = global(np: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=frombuffer) ['$2load_global.0', '$4load_attr.1']\n", - " $8load_global.3 = global(np: ) ['$8load_global.3']\n", - " $10load_attr.4 = getattr(value=$8load_global.3, attr=uint8) ['$10load_attr.4', '$8load_global.3']\n", - " temp = call $4load_attr.1(decompressed_bytes, func=$4load_attr.1, args=[Var(decompressed_bytes, bruker.py:267)], kws=[('dtype', Var($10load_attr.4, bruker.py:282))], vararg=None, varkwarg=None, target=None) ['$10load_attr.4', '$4load_attr.1', 'decompressed_bytes', 'temp']\n", - " $18load_global.7 = global(np: ) ['$18load_global.7']\n", - " $20load_attr.8 = getattr(value=$18load_global.7, attr=frombuffer) ['$18load_global.7', '$20load_attr.8']\n", - " $24load_method.10 = getattr(value=temp, attr=reshape) ['$24load_method.10', 'temp']\n", - " $const26.11 = const(int, 4) ['$const26.11']\n", - " $const28.12 = const(int, -1) ['$const28.12']\n", - " $30call_method.13 = call $24load_method.10($const26.11, $const28.12, func=$24load_method.10, args=[Var($const26.11, bruker.py:283), Var($const28.12, bruker.py:283)], kws=(), vararg=None, varkwarg=None, target=None) ['$24load_method.10', '$30call_method.13', '$const26.11', '$const28.12']\n", - " $32load_attr.14 = getattr(value=$30call_method.13, attr=T) ['$30call_method.13', '$32load_attr.14']\n", - " $34load_method.15 = getattr(value=$32load_attr.14, attr=flatten) ['$32load_attr.14', '$34load_method.15']\n", - " $36call_method.16 = call $34load_method.15(func=$34load_method.15, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$34load_method.15', '$36call_method.16']\n", - " $38load_global.17 = global(np: ) ['$38load_global.17']\n", - " $40load_attr.18 = getattr(value=$38load_global.17, attr=uint32) ['$38load_global.17', '$40load_attr.18']\n", - " buffer = call $20load_attr.8($36call_method.16, func=$20load_attr.8, args=[Var($36call_method.16, bruker.py:283)], kws=[('dtype', Var($40load_attr.18, bruker.py:283))], vararg=None, varkwarg=None, target=None) ['$20load_attr.8', '$36call_method.16', '$40load_attr.18', 'buffer']\n", - " $const50.22 = const(int, 0) ['$const50.22']\n", - " scan_count = getitem(value=buffer, index=$const50.22, fn=) ['$const50.22', 'buffer', 'scan_count']\n", - " $const58.25 = const(NoneType, None) ['$const58.25']\n", - " $62build_slice.27 = global(slice: ) ['$62build_slice.27']\n", - " $62build_slice.28 = call $62build_slice.27($const58.25, scan_count, func=$62build_slice.27, args=(Var($const58.25, bruker.py:285), Var(scan_count, bruker.py:284)), kws=(), vararg=None, varkwarg=None, target=None) ['$62build_slice.27', '$62build_slice.28', '$const58.25', 'scan_count']\n", - " $64binary_subscr.29 = getitem(value=buffer, index=$62build_slice.28, fn=) ['$62build_slice.28', '$64binary_subscr.29', 'buffer']\n", - " $66load_method.30 = getattr(value=$64binary_subscr.29, attr=copy) ['$64binary_subscr.29', '$66load_method.30']\n", - " $68call_method.31 = call $66load_method.30(func=$66load_method.30, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$66load_method.30', '$68call_method.31']\n", - " $const70.32 = const(int, 2) ['$const70.32']\n", - " scan_indices = $68call_method.31 // $const70.32 ['$68call_method.31', '$const70.32', 'scan_indices']\n", - " $const80.36 = const(int, 1) ['$const80.36']\n", - " $82binary_add.37 = scan_count + $const80.36 ['$82binary_add.37', '$const80.36', 'scan_count']\n", - " $const84.38 = const(NoneType, None) ['$const84.38']\n", - " $const86.39 = const(int, 2) ['$const86.39']\n", - " $88build_slice.40 = global(slice: ) ['$88build_slice.40']\n", - " $88build_slice.41 = call $88build_slice.40($82binary_add.37, $const84.38, $const86.39, func=$88build_slice.40, args=(Var($82binary_add.37, bruker.py:286), Var($const84.38, bruker.py:286), Var($const86.39, bruker.py:286)), kws=(), vararg=None, varkwarg=None, target=None) ['$82binary_add.37', '$88build_slice.40', '$88build_slice.41', '$const84.38', '$const86.39']\n", - " intensities = getitem(value=buffer, index=$88build_slice.41, fn=) ['$88build_slice.41', 'buffer', 'intensities']\n", - " $94load_global.43 = global(len: ) ['$94load_global.43']\n", - " $98call_function.45 = call $94load_global.43(intensities, func=$94load_global.43, args=[Var(intensities, bruker.py:286)], kws=(), vararg=None, varkwarg=None, target=None) ['$94load_global.43', '$98call_function.45', 'intensities']\n", - " $100load_global.46 = global(np: ) ['$100load_global.46']\n", - " $102load_method.47 = getattr(value=$100load_global.46, attr=sum) ['$100load_global.46', '$102load_method.47']\n", - " $const106.49 = const(int, 1) ['$const106.49']\n", - " $const108.50 = const(NoneType, None) ['$const108.50']\n", - " $110build_slice.51 = global(slice: ) ['$110build_slice.51']\n", - " $110build_slice.52 = call $110build_slice.51($const106.49, $const108.50, func=$110build_slice.51, args=(Var($const106.49, bruker.py:287), Var($const108.50, bruker.py:287)), kws=(), vararg=None, varkwarg=None, target=None) ['$110build_slice.51', '$110build_slice.52', '$const106.49', '$const108.50']\n", - " $112binary_subscr.53 = getitem(value=scan_indices, index=$110build_slice.52, fn=) ['$110build_slice.52', '$112binary_subscr.53', 'scan_indices']\n", - " $114call_method.54 = call $102load_method.47($112binary_subscr.53, func=$102load_method.47, args=[Var($112binary_subscr.53, bruker.py:287)], kws=(), vararg=None, varkwarg=None, target=None) ['$102load_method.47', '$112binary_subscr.53', '$114call_method.54']\n", - " last_scan = $98call_function.45 - $114call_method.54 ['$114call_method.54', '$98call_function.45', 'last_scan']\n", - " $const122.57 = const(int, 1) ['$const122.57']\n", - " $const124.58 = const(NoneType, None) ['$const124.58']\n", - " $126build_slice.59 = global(slice: ) ['$126build_slice.59']\n", - " $126build_slice.60 = call $126build_slice.59($const122.57, $const124.58, func=$126build_slice.59, args=(Var($const122.57, bruker.py:288), Var($const124.58, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None) ['$126build_slice.59', '$126build_slice.60', '$const122.57', '$const124.58']\n", - " $128binary_subscr.61 = getitem(value=scan_indices, index=$126build_slice.60, fn=) ['$126build_slice.60', '$128binary_subscr.61', 'scan_indices']\n", - " $const132.63 = const(NoneType, None) ['$const132.63']\n", - " $const134.64 = const(int, -1) ['$const134.64']\n", - " $136build_slice.65 = global(slice: ) ['$136build_slice.65']\n", - " $136build_slice.66 = call $136build_slice.65($const132.63, $const134.64, func=$136build_slice.65, args=(Var($const132.63, bruker.py:288), Var($const134.64, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None) ['$136build_slice.65', '$136build_slice.66', '$const132.63', '$const134.64']\n", - " scan_indices[$136build_slice.66] = $128binary_subscr.61 ['$128binary_subscr.61', '$136build_slice.66', 'scan_indices']\n", - " $const144.69 = const(int, -1) ['$const144.69']\n", - " scan_indices[$const144.69] = last_scan ['$const144.69', 'last_scan', 'scan_indices']\n", - " $const152.72 = const(NoneType, None) ['$const152.72']\n", - " $const154.73 = const(int, 2) ['$const154.73']\n", - " $156build_slice.74 = global(slice: ) ['$156build_slice.74']\n", - " $156build_slice.75 = call $156build_slice.74(scan_count, $const152.72, $const154.73, func=$156build_slice.74, args=(Var(scan_count, bruker.py:284), Var($const152.72, bruker.py:290), Var($const154.73, bruker.py:290)), kws=(), vararg=None, varkwarg=None, target=None) ['$156build_slice.74', '$156build_slice.75', '$const152.72', '$const154.73', 'scan_count']\n", - " $158binary_subscr.76 = getitem(value=buffer, index=$156build_slice.75, fn=) ['$156build_slice.75', '$158binary_subscr.76', 'buffer']\n", - " $160load_method.77 = getattr(value=$158binary_subscr.76, attr=copy) ['$158binary_subscr.76', '$160load_method.77']\n", - " tof_indices = call $160load_method.77(func=$160load_method.77, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$160load_method.77', 'tof_indices']\n", - " index = const(int, 0) ['index']\n", - " $172get_iter.81 = getiter(value=scan_indices) ['$172get_iter.81', 'scan_indices']\n", - " $phi174.0 = $172get_iter.81 ['$172get_iter.81', '$phi174.0']\n", - " jump 174 []\n", - "label 174:\n", - " $174for_iter.1 = iternext(value=$phi174.0) ['$174for_iter.1', '$phi174.0']\n", - " $174for_iter.2 = pair_first(value=$174for_iter.1) ['$174for_iter.1', '$174for_iter.2']\n", - " $174for_iter.3 = pair_second(value=$174for_iter.1) ['$174for_iter.1', '$174for_iter.3']\n", - " $phi176.1 = $174for_iter.2 ['$174for_iter.2', '$phi176.1']\n", - " branch $174for_iter.3, 176, 226 ['$174for_iter.3']\n", - "label 176:\n", - " size = $phi176.1 ['$phi176.1', 'size']\n", - " current_sum = const(int, 0) ['current_sum']\n", - " $182load_global.3 = global(range: ) ['$182load_global.3']\n", - " $186call_function.5 = call $182load_global.3(size, func=$182load_global.3, args=[Var(size, bruker.py:292)], kws=(), vararg=None, varkwarg=None, target=None) ['$182load_global.3', '$186call_function.5', 'size']\n", - " $188get_iter.6 = getiter(value=$186call_function.5) ['$186call_function.5', '$188get_iter.6']\n", - " $phi190.1 = $188get_iter.6 ['$188get_iter.6', '$phi190.1']\n", - " jump 190 []\n", - "label 190:\n", - " $190for_iter.2 = iternext(value=$phi190.1) ['$190for_iter.2', '$phi190.1']\n", - " $190for_iter.3 = pair_first(value=$190for_iter.2) ['$190for_iter.2', '$190for_iter.3']\n", - " $190for_iter.4 = pair_second(value=$190for_iter.2) ['$190for_iter.2', '$190for_iter.4']\n", - " $phi192.2 = $190for_iter.3 ['$190for_iter.3', '$phi192.2']\n", - " branch $190for_iter.4, 192, 224 ['$190for_iter.4']\n", - "label 192:\n", - " i = $phi192.2 ['$phi192.2', 'i']\n", - " $200binary_subscr.6 = getitem(value=tof_indices, index=index, fn=) ['$200binary_subscr.6', 'index', 'tof_indices']\n", - " $202inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=current_sum, rhs=$200binary_subscr.6, static_lhs=Undefined, static_rhs=Undefined) ['$200binary_subscr.6', '$202inplace_add.7', 'current_sum']\n", - " current_sum = $202inplace_add.7 ['$202inplace_add.7', 'current_sum']\n", - " tof_indices[index] = current_sum ['current_sum', 'index', 'tof_indices']\n", - " $const216.12 = const(int, 1) ['$const216.12']\n", - " $218inplace_add.13 = inplace_binop(fn=, immutable_fn=, lhs=index, rhs=$const216.12, static_lhs=Undefined, static_rhs=Undefined) ['$218inplace_add.13', '$const216.12', 'index']\n", - " index = $218inplace_add.13 ['$218inplace_add.13', 'index']\n", - " jump 190 []\n", - "label 224:\n", - " jump 174 []\n", - "label 226:\n", - " $const230.2 = const(int, 1) ['$const230.2']\n", - " $232binary_subtract.3 = tof_indices - $const230.2 ['$232binary_subtract.3', '$const230.2', 'tof_indices']\n", - " $236build_tuple.5 = build_tuple(items=[Var(scan_indices, bruker.py:285), Var($232binary_subtract.3, bruker.py:298), Var(intensities, bruker.py:286)]) ['$232binary_subtract.3', '$236build_tuple.5', 'intensities', 'scan_indices']\n", - " $238return_value.6 = cast(value=$236build_tuple.5) ['$236build_tuple.5', '$238return_value.6']\n", - " return $238return_value.6 ['$238return_value.6']\n", - "\n", - "2024-10-16 10:10:42,610 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:42,612 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,613 - numba.core.ssa - DEBUG - on stmt: decompressed_bytes = arg(0, name=decompressed_bytes)\n", - "2024-10-16 10:10:42,614 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:10:42,615 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=frombuffer)\n", - "2024-10-16 10:10:42,616 - numba.core.ssa - DEBUG - on stmt: $8load_global.3 = global(np: )\n", - "2024-10-16 10:10:42,616 - numba.core.ssa - DEBUG - on stmt: $10load_attr.4 = getattr(value=$8load_global.3, attr=uint8)\n", - "2024-10-16 10:10:42,617 - numba.core.ssa - DEBUG - on stmt: temp = call $4load_attr.1(decompressed_bytes, func=$4load_attr.1, args=[Var(decompressed_bytes, bruker.py:267)], kws=[('dtype', Var($10load_attr.4, bruker.py:282))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,618 - numba.core.ssa - DEBUG - on stmt: $18load_global.7 = global(np: )\n", - "2024-10-16 10:10:42,619 - numba.core.ssa - DEBUG - on stmt: $20load_attr.8 = getattr(value=$18load_global.7, attr=frombuffer)\n", - "2024-10-16 10:10:42,619 - numba.core.ssa - DEBUG - on stmt: $24load_method.10 = getattr(value=temp, attr=reshape)\n", - "2024-10-16 10:10:42,620 - numba.core.ssa - DEBUG - on stmt: $const26.11 = const(int, 4)\n", - "2024-10-16 10:10:42,621 - numba.core.ssa - DEBUG - on stmt: $const28.12 = const(int, -1)\n", - "2024-10-16 10:10:42,622 - numba.core.ssa - DEBUG - on stmt: $30call_method.13 = call $24load_method.10($const26.11, $const28.12, func=$24load_method.10, args=[Var($const26.11, bruker.py:283), Var($const28.12, bruker.py:283)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,623 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30call_method.13, attr=T)\n", - "2024-10-16 10:10:42,623 - numba.core.ssa - DEBUG - on stmt: $34load_method.15 = getattr(value=$32load_attr.14, attr=flatten)\n", - "2024-10-16 10:10:42,624 - numba.core.ssa - DEBUG - on stmt: $36call_method.16 = call $34load_method.15(func=$34load_method.15, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,625 - numba.core.ssa - DEBUG - on stmt: $38load_global.17 = global(np: )\n", - "2024-10-16 10:10:42,626 - numba.core.ssa - DEBUG - on stmt: $40load_attr.18 = getattr(value=$38load_global.17, attr=uint32)\n", - "2024-10-16 10:10:42,626 - numba.core.ssa - DEBUG - on stmt: buffer = call $20load_attr.8($36call_method.16, func=$20load_attr.8, args=[Var($36call_method.16, bruker.py:283)], kws=[('dtype', Var($40load_attr.18, bruker.py:283))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,627 - numba.core.ssa - DEBUG - on stmt: $const50.22 = const(int, 0)\n", - "2024-10-16 10:10:42,628 - numba.core.ssa - DEBUG - on stmt: scan_count = static_getitem(value=buffer, index=0, index_var=$const50.22, fn=)\n", - "2024-10-16 10:10:42,629 - numba.core.ssa - DEBUG - on stmt: $const58.25 = const(NoneType, None)\n", - "2024-10-16 10:10:42,629 - numba.core.ssa - DEBUG - on stmt: $62build_slice.27 = global(slice: )\n", - "2024-10-16 10:10:42,630 - numba.core.ssa - DEBUG - on stmt: $62build_slice.28 = call $62build_slice.27($const58.25, scan_count, func=$62build_slice.27, args=(Var($const58.25, bruker.py:285), Var(scan_count, bruker.py:284)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,631 - numba.core.ssa - DEBUG - on stmt: $64binary_subscr.29 = getitem(value=buffer, index=$62build_slice.28, fn=)\n", - "2024-10-16 10:10:42,632 - numba.core.ssa - DEBUG - on stmt: $66load_method.30 = getattr(value=$64binary_subscr.29, attr=copy)\n", - "2024-10-16 10:10:42,633 - numba.core.ssa - DEBUG - on stmt: $68call_method.31 = call $66load_method.30(func=$66load_method.30, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,633 - numba.core.ssa - DEBUG - on stmt: $const70.32 = const(int, 2)\n", - "2024-10-16 10:10:42,634 - numba.core.ssa - DEBUG - on stmt: scan_indices = $68call_method.31 // $const70.32\n", - "2024-10-16 10:10:42,635 - numba.core.ssa - DEBUG - on stmt: $const80.36 = const(int, 1)\n", - "2024-10-16 10:10:42,636 - numba.core.ssa - DEBUG - on stmt: $82binary_add.37 = scan_count + $const80.36\n", - "2024-10-16 10:10:42,636 - numba.core.ssa - DEBUG - on stmt: $const84.38 = const(NoneType, None)\n", - "2024-10-16 10:10:42,637 - numba.core.ssa - DEBUG - on stmt: $const86.39 = const(int, 2)\n", - "2024-10-16 10:10:42,638 - numba.core.ssa - DEBUG - on stmt: $88build_slice.40 = global(slice: )\n", - "2024-10-16 10:10:42,639 - numba.core.ssa - DEBUG - on stmt: $88build_slice.41 = call $88build_slice.40($82binary_add.37, $const84.38, $const86.39, func=$88build_slice.40, args=(Var($82binary_add.37, bruker.py:286), Var($const84.38, bruker.py:286), Var($const86.39, bruker.py:286)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,639 - numba.core.ssa - DEBUG - on stmt: intensities = getitem(value=buffer, index=$88build_slice.41, fn=)\n", - "2024-10-16 10:10:42,640 - numba.core.ssa - DEBUG - on stmt: $94load_global.43 = global(len: )\n", - "2024-10-16 10:10:42,641 - numba.core.ssa - DEBUG - on stmt: $98call_function.45 = call $94load_global.43(intensities, func=$94load_global.43, args=[Var(intensities, bruker.py:286)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,642 - numba.core.ssa - DEBUG - on stmt: $100load_global.46 = global(np: )\n", - "2024-10-16 10:10:42,642 - numba.core.ssa - DEBUG - on stmt: $102load_method.47 = getattr(value=$100load_global.46, attr=sum)\n", - "2024-10-16 10:10:42,643 - numba.core.ssa - DEBUG - on stmt: $const106.49 = const(int, 1)\n", - "2024-10-16 10:10:42,644 - numba.core.ssa - DEBUG - on stmt: $const108.50 = const(NoneType, None)\n", - "2024-10-16 10:10:42,645 - numba.core.ssa - DEBUG - on stmt: $110build_slice.51 = global(slice: )\n", - "2024-10-16 10:10:42,645 - numba.core.ssa - DEBUG - on stmt: $110build_slice.52 = call $110build_slice.51($const106.49, $const108.50, func=$110build_slice.51, args=(Var($const106.49, bruker.py:287), Var($const108.50, bruker.py:287)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,646 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.53 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$110build_slice.52, fn=)\n", - "2024-10-16 10:10:42,647 - numba.core.ssa - DEBUG - on stmt: $114call_method.54 = call $102load_method.47($112binary_subscr.53, func=$102load_method.47, args=[Var($112binary_subscr.53, bruker.py:287)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,648 - numba.core.ssa - DEBUG - on stmt: last_scan = $98call_function.45 - $114call_method.54\n", - "2024-10-16 10:10:42,649 - numba.core.ssa - DEBUG - on stmt: $const122.57 = const(int, 1)\n", - "2024-10-16 10:10:42,649 - numba.core.ssa - DEBUG - on stmt: $const124.58 = const(NoneType, None)\n", - "2024-10-16 10:10:42,650 - numba.core.ssa - DEBUG - on stmt: $126build_slice.59 = global(slice: )\n", - "2024-10-16 10:10:42,651 - numba.core.ssa - DEBUG - on stmt: $126build_slice.60 = call $126build_slice.59($const122.57, $const124.58, func=$126build_slice.59, args=(Var($const122.57, bruker.py:288), Var($const124.58, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,652 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.61 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$126build_slice.60, fn=)\n", - "2024-10-16 10:10:42,652 - numba.core.ssa - DEBUG - on stmt: $const132.63 = const(NoneType, None)\n", - "2024-10-16 10:10:42,653 - numba.core.ssa - DEBUG - on stmt: $const134.64 = const(int, -1)\n", - "2024-10-16 10:10:42,654 - numba.core.ssa - DEBUG - on stmt: $136build_slice.65 = global(slice: )\n", - "2024-10-16 10:10:42,655 - numba.core.ssa - DEBUG - on stmt: $136build_slice.66 = call $136build_slice.65($const132.63, $const134.64, func=$136build_slice.65, args=(Var($const132.63, bruker.py:288), Var($const134.64, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,655 - numba.core.ssa - DEBUG - on stmt: scan_indices[slice(None, -1, None)] = $128binary_subscr.61\n", - "2024-10-16 10:10:42,656 - numba.core.ssa - DEBUG - on stmt: $const144.69 = const(int, -1)\n", - "2024-10-16 10:10:42,657 - numba.core.ssa - DEBUG - on stmt: scan_indices[-1] = last_scan\n", - "2024-10-16 10:10:42,658 - numba.core.ssa - DEBUG - on stmt: $const152.72 = const(NoneType, None)\n", - "2024-10-16 10:10:42,659 - numba.core.ssa - DEBUG - on stmt: $const154.73 = const(int, 2)\n", - "2024-10-16 10:10:42,660 - numba.core.ssa - DEBUG - on stmt: $156build_slice.74 = global(slice: )\n", - "2024-10-16 10:10:42,660 - numba.core.ssa - DEBUG - on stmt: $156build_slice.75 = call $156build_slice.74(scan_count, $const152.72, $const154.73, func=$156build_slice.74, args=(Var(scan_count, bruker.py:284), Var($const152.72, bruker.py:290), Var($const154.73, bruker.py:290)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,661 - numba.core.ssa - DEBUG - on stmt: $158binary_subscr.76 = getitem(value=buffer, index=$156build_slice.75, fn=)\n", - "2024-10-16 10:10:42,662 - numba.core.ssa - DEBUG - on stmt: $160load_method.77 = getattr(value=$158binary_subscr.76, attr=copy)\n", - "2024-10-16 10:10:42,663 - numba.core.ssa - DEBUG - on stmt: tof_indices = call $160load_method.77(func=$160load_method.77, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,663 - numba.core.ssa - DEBUG - on stmt: index = const(int, 0)\n", - "2024-10-16 10:10:42,664 - numba.core.ssa - DEBUG - on stmt: $172get_iter.81 = getiter(value=scan_indices)\n", - "2024-10-16 10:10:42,665 - numba.core.ssa - DEBUG - on stmt: $phi174.0 = $172get_iter.81\n", - "2024-10-16 10:10:42,666 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:42,667 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 174\n", - "2024-10-16 10:10:42,667 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,668 - numba.core.ssa - DEBUG - on stmt: $174for_iter.1 = iternext(value=$phi174.0)\n", - "2024-10-16 10:10:42,669 - numba.core.ssa - DEBUG - on stmt: $174for_iter.2 = pair_first(value=$174for_iter.1)\n", - "2024-10-16 10:10:42,670 - numba.core.ssa - DEBUG - on stmt: $174for_iter.3 = pair_second(value=$174for_iter.1)\n", - "2024-10-16 10:10:42,670 - numba.core.ssa - DEBUG - on stmt: $phi176.1 = $174for_iter.2\n", - "2024-10-16 10:10:42,671 - numba.core.ssa - DEBUG - on stmt: branch $174for_iter.3, 176, 226\n", - "2024-10-16 10:10:42,672 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 176\n", - "2024-10-16 10:10:42,673 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,674 - numba.core.ssa - DEBUG - on stmt: size = $phi176.1\n", - "2024-10-16 10:10:42,674 - numba.core.ssa - DEBUG - on stmt: current_sum = const(int, 0)\n", - "2024-10-16 10:10:42,675 - numba.core.ssa - DEBUG - on stmt: $182load_global.3 = global(range: )\n", - "2024-10-16 10:10:42,676 - numba.core.ssa - DEBUG - on stmt: $186call_function.5 = call $182load_global.3(size, func=$182load_global.3, args=[Var(size, bruker.py:292)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,677 - numba.core.ssa - DEBUG - on stmt: $188get_iter.6 = getiter(value=$186call_function.5)\n", - "2024-10-16 10:10:42,677 - numba.core.ssa - DEBUG - on stmt: $phi190.1 = $188get_iter.6\n", - "2024-10-16 10:10:42,678 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:42,679 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 190\n", - "2024-10-16 10:10:42,680 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,681 - numba.core.ssa - DEBUG - on stmt: $190for_iter.2 = iternext(value=$phi190.1)\n", - "2024-10-16 10:10:42,681 - numba.core.ssa - DEBUG - on stmt: $190for_iter.3 = pair_first(value=$190for_iter.2)\n", - "2024-10-16 10:10:42,682 - numba.core.ssa - DEBUG - on stmt: $190for_iter.4 = pair_second(value=$190for_iter.2)\n", - "2024-10-16 10:10:42,683 - numba.core.ssa - DEBUG - on stmt: $phi192.2 = $190for_iter.3\n", - "2024-10-16 10:10:42,684 - numba.core.ssa - DEBUG - on stmt: branch $190for_iter.4, 192, 224\n", - "2024-10-16 10:10:42,684 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 192\n", - "2024-10-16 10:10:42,685 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,686 - numba.core.ssa - DEBUG - on stmt: i = $phi192.2\n", - "2024-10-16 10:10:42,687 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.6 = getitem(value=tof_indices, index=index, fn=)\n", - "2024-10-16 10:10:42,688 - numba.core.ssa - DEBUG - on stmt: $202inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=current_sum, rhs=$200binary_subscr.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,688 - numba.core.ssa - DEBUG - on stmt: current_sum = $202inplace_add.7\n", - "2024-10-16 10:10:42,689 - numba.core.ssa - DEBUG - on stmt: tof_indices[index] = current_sum\n", - "2024-10-16 10:10:42,690 - numba.core.ssa - DEBUG - on stmt: $const216.12 = const(int, 1)\n", - "2024-10-16 10:10:42,691 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.13 = inplace_binop(fn=, immutable_fn=, lhs=index, rhs=$const216.12, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,692 - numba.core.ssa - DEBUG - on stmt: index = $218inplace_add.13\n", - "2024-10-16 10:10:42,693 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:42,694 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 224\n", - "2024-10-16 10:10:42,695 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,695 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:42,696 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 226\n", - "2024-10-16 10:10:42,697 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,698 - numba.core.ssa - DEBUG - on stmt: $const230.2 = const(int, 1)\n", - "2024-10-16 10:10:42,699 - numba.core.ssa - DEBUG - on stmt: $232binary_subtract.3 = tof_indices - $const230.2\n", - "2024-10-16 10:10:42,700 - numba.core.ssa - DEBUG - on stmt: $236build_tuple.5 = build_tuple(items=[Var(scan_indices, bruker.py:285), Var($232binary_subtract.3, bruker.py:298), Var(intensities, bruker.py:286)])\n", - "2024-10-16 10:10:42,700 - numba.core.ssa - DEBUG - on stmt: $238return_value.6 = cast(value=$236build_tuple.5)\n", - "2024-10-16 10:10:42,701 - numba.core.ssa - DEBUG - on stmt: return $238return_value.6\n", - "2024-10-16 10:10:42,705 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$100load_global.46': [],\n", - " '$102load_method.47': [],\n", - " '$10load_attr.4': [],\n", - " '$110build_slice.51': [],\n", - " '$110build_slice.52': [],\n", - " '$112binary_subscr.53': [],\n", - " '$114call_method.54': [],\n", - " '$126build_slice.59': [],\n", - " '$126build_slice.60': [],\n", - " '$128binary_subscr.61': [],\n", - " '$136build_slice.65': [],\n", - " '$136build_slice.66': [],\n", - " '$156build_slice.74': [],\n", - " '$156build_slice.75': [],\n", - " '$158binary_subscr.76': [],\n", - " '$160load_method.77': [],\n", - " '$172get_iter.81': [],\n", - " '$174for_iter.1': [],\n", - " '$174for_iter.2': [],\n", - " '$174for_iter.3': [],\n", - " '$182load_global.3': [],\n", - " '$186call_function.5': [],\n", - " '$188get_iter.6': [],\n", - " '$18load_global.7': [],\n", - " '$190for_iter.2': [],\n", - " '$190for_iter.3': [],\n", - " '$190for_iter.4': [],\n", - " '$200binary_subscr.6': [],\n", - " '$202inplace_add.7': [],\n", - " '$20load_attr.8': [],\n", - " '$218inplace_add.13': [],\n", - " '$232binary_subtract.3': [],\n", - " '$236build_tuple.5': [],\n", - " '$238return_value.6': [],\n", - " '$24load_method.10': [],\n", - " '$2load_global.0': [],\n", - " '$30call_method.13': [],\n", - " '$32load_attr.14': [],\n", - " '$34load_method.15': [],\n", - " '$36call_method.16': [],\n", - " '$38load_global.17': [],\n", - " '$40load_attr.18': [],\n", - " '$4load_attr.1': [],\n", - " '$62build_slice.27': [],\n", - " '$62build_slice.28': [],\n", - " '$64binary_subscr.29': [],\n", - " '$66load_method.30': [],\n", - " '$68call_method.31': [],\n", - " '$82binary_add.37': [],\n", - " '$88build_slice.40': [],\n", - " '$88build_slice.41': [],\n", - " '$8load_global.3': [],\n", - " '$94load_global.43': [],\n", - " '$98call_function.45': [],\n", - " '$const106.49': [],\n", - " '$const108.50': [],\n", - " '$const122.57': [],\n", - " '$const124.58': [],\n", - " '$const132.63': [],\n", - " '$const134.64': [],\n", - " '$const144.69': [],\n", - " '$const152.72': [],\n", - " '$const154.73': [],\n", - " '$const216.12': [],\n", - " '$const230.2': [],\n", - " '$const26.11': [],\n", - " '$const28.12': [],\n", - " '$const50.22': [],\n", - " '$const58.25': [],\n", - " '$const70.32': [],\n", - " '$const80.36': [],\n", - " '$const84.38': [],\n", - " '$const86.39': [],\n", - " '$phi174.0': [],\n", - " '$phi176.1': [],\n", - " '$phi190.1': [],\n", - " '$phi192.2': [],\n", - " 'buffer': [],\n", - " 'current_sum': [,\n", - " ],\n", - " 'decompressed_bytes': [],\n", - " 'i': [],\n", - " 'index': [,\n", - " ],\n", - " 'intensities': [],\n", - " 'last_scan': [],\n", - " 'scan_count': [],\n", - " 'scan_indices': [],\n", - " 'size': [],\n", - " 'temp': [],\n", - " 'tof_indices': []})\n", - "2024-10-16 10:10:42,706 - numba.core.ssa - DEBUG - SSA violators {'current_sum', 'index'}\n", - "2024-10-16 10:10:42,707 - numba.core.ssa - DEBUG - Fix SSA violator on var current_sum\n", - "2024-10-16 10:10:42,708 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:42,709 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,710 - numba.core.ssa - DEBUG - on stmt: decompressed_bytes = arg(0, name=decompressed_bytes)\n", - "2024-10-16 10:10:42,711 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:10:42,711 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=frombuffer)\n", - "2024-10-16 10:10:42,712 - numba.core.ssa - DEBUG - on stmt: $8load_global.3 = global(np: )\n", - "2024-10-16 10:10:42,713 - numba.core.ssa - DEBUG - on stmt: $10load_attr.4 = getattr(value=$8load_global.3, attr=uint8)\n", - "2024-10-16 10:10:42,714 - numba.core.ssa - DEBUG - on stmt: temp = call $4load_attr.1(decompressed_bytes, func=$4load_attr.1, args=[Var(decompressed_bytes, bruker.py:267)], kws=[('dtype', Var($10load_attr.4, bruker.py:282))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,715 - numba.core.ssa - DEBUG - on stmt: $18load_global.7 = global(np: )\n", - "2024-10-16 10:10:42,716 - numba.core.ssa - DEBUG - on stmt: $20load_attr.8 = getattr(value=$18load_global.7, attr=frombuffer)\n", - "2024-10-16 10:10:42,717 - numba.core.ssa - DEBUG - on stmt: $24load_method.10 = getattr(value=temp, attr=reshape)\n", - "2024-10-16 10:10:42,718 - numba.core.ssa - DEBUG - on stmt: $const26.11 = const(int, 4)\n", - "2024-10-16 10:10:42,718 - numba.core.ssa - DEBUG - on stmt: $const28.12 = const(int, -1)\n", - "2024-10-16 10:10:42,719 - numba.core.ssa - DEBUG - on stmt: $30call_method.13 = call $24load_method.10($const26.11, $const28.12, func=$24load_method.10, args=[Var($const26.11, bruker.py:283), Var($const28.12, bruker.py:283)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,720 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30call_method.13, attr=T)\n", - "2024-10-16 10:10:42,721 - numba.core.ssa - DEBUG - on stmt: $34load_method.15 = getattr(value=$32load_attr.14, attr=flatten)\n", - "2024-10-16 10:10:42,722 - numba.core.ssa - DEBUG - on stmt: $36call_method.16 = call $34load_method.15(func=$34load_method.15, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,723 - numba.core.ssa - DEBUG - on stmt: $38load_global.17 = global(np: )\n", - "2024-10-16 10:10:42,724 - numba.core.ssa - DEBUG - on stmt: $40load_attr.18 = getattr(value=$38load_global.17, attr=uint32)\n", - "2024-10-16 10:10:42,724 - numba.core.ssa - DEBUG - on stmt: buffer = call $20load_attr.8($36call_method.16, func=$20load_attr.8, args=[Var($36call_method.16, bruker.py:283)], kws=[('dtype', Var($40load_attr.18, bruker.py:283))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,725 - numba.core.ssa - DEBUG - on stmt: $const50.22 = const(int, 0)\n", - "2024-10-16 10:10:42,726 - numba.core.ssa - DEBUG - on stmt: scan_count = static_getitem(value=buffer, index=0, index_var=$const50.22, fn=)\n", - "2024-10-16 10:10:42,727 - numba.core.ssa - DEBUG - on stmt: $const58.25 = const(NoneType, None)\n", - "2024-10-16 10:10:42,728 - numba.core.ssa - DEBUG - on stmt: $62build_slice.27 = global(slice: )\n", - "2024-10-16 10:10:42,729 - numba.core.ssa - DEBUG - on stmt: $62build_slice.28 = call $62build_slice.27($const58.25, scan_count, func=$62build_slice.27, args=(Var($const58.25, bruker.py:285), Var(scan_count, bruker.py:284)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,730 - numba.core.ssa - DEBUG - on stmt: $64binary_subscr.29 = getitem(value=buffer, index=$62build_slice.28, fn=)\n", - "2024-10-16 10:10:42,730 - numba.core.ssa - DEBUG - on stmt: $66load_method.30 = getattr(value=$64binary_subscr.29, attr=copy)\n", - "2024-10-16 10:10:42,731 - numba.core.ssa - DEBUG - on stmt: $68call_method.31 = call $66load_method.30(func=$66load_method.30, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,732 - numba.core.ssa - DEBUG - on stmt: $const70.32 = const(int, 2)\n", - "2024-10-16 10:10:42,733 - numba.core.ssa - DEBUG - on stmt: scan_indices = $68call_method.31 // $const70.32\n", - "2024-10-16 10:10:42,734 - numba.core.ssa - DEBUG - on stmt: $const80.36 = const(int, 1)\n", - "2024-10-16 10:10:42,734 - numba.core.ssa - DEBUG - on stmt: $82binary_add.37 = scan_count + $const80.36\n", - "2024-10-16 10:10:42,735 - numba.core.ssa - DEBUG - on stmt: $const84.38 = const(NoneType, None)\n", - "2024-10-16 10:10:42,736 - numba.core.ssa - DEBUG - on stmt: $const86.39 = const(int, 2)\n", - "2024-10-16 10:10:42,736 - numba.core.ssa - DEBUG - on stmt: $88build_slice.40 = global(slice: )\n", - "2024-10-16 10:10:42,737 - numba.core.ssa - DEBUG - on stmt: $88build_slice.41 = call $88build_slice.40($82binary_add.37, $const84.38, $const86.39, func=$88build_slice.40, args=(Var($82binary_add.37, bruker.py:286), Var($const84.38, bruker.py:286), Var($const86.39, bruker.py:286)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,738 - numba.core.ssa - DEBUG - on stmt: intensities = getitem(value=buffer, index=$88build_slice.41, fn=)\n", - "2024-10-16 10:10:42,744 - numba.core.ssa - DEBUG - on stmt: $94load_global.43 = global(len: )\n", - "2024-10-16 10:10:42,771 - numba.core.ssa - DEBUG - on stmt: $98call_function.45 = call $94load_global.43(intensities, func=$94load_global.43, args=[Var(intensities, bruker.py:286)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,772 - numba.core.ssa - DEBUG - on stmt: $100load_global.46 = global(np: )\n", - "2024-10-16 10:10:42,772 - numba.core.ssa - DEBUG - on stmt: $102load_method.47 = getattr(value=$100load_global.46, attr=sum)\n", - "2024-10-16 10:10:42,773 - numba.core.ssa - DEBUG - on stmt: $const106.49 = const(int, 1)\n", - "2024-10-16 10:10:42,774 - numba.core.ssa - DEBUG - on stmt: $const108.50 = const(NoneType, None)\n", - "2024-10-16 10:10:42,774 - numba.core.ssa - DEBUG - on stmt: $110build_slice.51 = global(slice: )\n", - "2024-10-16 10:10:42,775 - numba.core.ssa - DEBUG - on stmt: $110build_slice.52 = call $110build_slice.51($const106.49, $const108.50, func=$110build_slice.51, args=(Var($const106.49, bruker.py:287), Var($const108.50, bruker.py:287)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,776 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.53 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$110build_slice.52, fn=)\n", - "2024-10-16 10:10:42,776 - numba.core.ssa - DEBUG - on stmt: $114call_method.54 = call $102load_method.47($112binary_subscr.53, func=$102load_method.47, args=[Var($112binary_subscr.53, bruker.py:287)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,777 - numba.core.ssa - DEBUG - on stmt: last_scan = $98call_function.45 - $114call_method.54\n", - "2024-10-16 10:10:42,777 - numba.core.ssa - DEBUG - on stmt: $const122.57 = const(int, 1)\n", - "2024-10-16 10:10:42,778 - numba.core.ssa - DEBUG - on stmt: $const124.58 = const(NoneType, None)\n", - "2024-10-16 10:10:42,779 - numba.core.ssa - DEBUG - on stmt: $126build_slice.59 = global(slice: )\n", - "2024-10-16 10:10:42,779 - numba.core.ssa - DEBUG - on stmt: $126build_slice.60 = call $126build_slice.59($const122.57, $const124.58, func=$126build_slice.59, args=(Var($const122.57, bruker.py:288), Var($const124.58, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,780 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.61 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$126build_slice.60, fn=)\n", - "2024-10-16 10:10:42,781 - numba.core.ssa - DEBUG - on stmt: $const132.63 = const(NoneType, None)\n", - "2024-10-16 10:10:42,781 - numba.core.ssa - DEBUG - on stmt: $const134.64 = const(int, -1)\n", - "2024-10-16 10:10:42,782 - numba.core.ssa - DEBUG - on stmt: $136build_slice.65 = global(slice: )\n", - "2024-10-16 10:10:42,782 - numba.core.ssa - DEBUG - on stmt: $136build_slice.66 = call $136build_slice.65($const132.63, $const134.64, func=$136build_slice.65, args=(Var($const132.63, bruker.py:288), Var($const134.64, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,783 - numba.core.ssa - DEBUG - on stmt: scan_indices[slice(None, -1, None)] = $128binary_subscr.61\n", - "2024-10-16 10:10:42,784 - numba.core.ssa - DEBUG - on stmt: $const144.69 = const(int, -1)\n", - "2024-10-16 10:10:42,784 - numba.core.ssa - DEBUG - on stmt: scan_indices[-1] = last_scan\n", - "2024-10-16 10:10:42,785 - numba.core.ssa - DEBUG - on stmt: $const152.72 = const(NoneType, None)\n", - "2024-10-16 10:10:42,786 - numba.core.ssa - DEBUG - on stmt: $const154.73 = const(int, 2)\n", - "2024-10-16 10:10:42,786 - numba.core.ssa - DEBUG - on stmt: $156build_slice.74 = global(slice: )\n", - "2024-10-16 10:10:42,790 - numba.core.ssa - DEBUG - on stmt: $156build_slice.75 = call $156build_slice.74(scan_count, $const152.72, $const154.73, func=$156build_slice.74, args=(Var(scan_count, bruker.py:284), Var($const152.72, bruker.py:290), Var($const154.73, bruker.py:290)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,790 - numba.core.ssa - DEBUG - on stmt: $158binary_subscr.76 = getitem(value=buffer, index=$156build_slice.75, fn=)\n", - "2024-10-16 10:10:42,791 - numba.core.ssa - DEBUG - on stmt: $160load_method.77 = getattr(value=$158binary_subscr.76, attr=copy)\n", - "2024-10-16 10:10:42,792 - numba.core.ssa - DEBUG - on stmt: tof_indices = call $160load_method.77(func=$160load_method.77, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,792 - numba.core.ssa - DEBUG - on stmt: index = const(int, 0)\n", - "2024-10-16 10:10:42,793 - numba.core.ssa - DEBUG - on stmt: $172get_iter.81 = getiter(value=scan_indices)\n", - "2024-10-16 10:10:42,794 - numba.core.ssa - DEBUG - on stmt: $phi174.0 = $172get_iter.81\n", - "2024-10-16 10:10:42,794 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:42,795 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 174\n", - "2024-10-16 10:10:42,795 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,796 - numba.core.ssa - DEBUG - on stmt: $174for_iter.1 = iternext(value=$phi174.0)\n", - "2024-10-16 10:10:42,797 - numba.core.ssa - DEBUG - on stmt: $174for_iter.2 = pair_first(value=$174for_iter.1)\n", - "2024-10-16 10:10:42,797 - numba.core.ssa - DEBUG - on stmt: $174for_iter.3 = pair_second(value=$174for_iter.1)\n", - "2024-10-16 10:10:42,798 - numba.core.ssa - DEBUG - on stmt: $phi176.1 = $174for_iter.2\n", - "2024-10-16 10:10:42,798 - numba.core.ssa - DEBUG - on stmt: branch $174for_iter.3, 176, 226\n", - "2024-10-16 10:10:42,799 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 176\n", - "2024-10-16 10:10:42,802 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,802 - numba.core.ssa - DEBUG - on stmt: size = $phi176.1\n", - "2024-10-16 10:10:42,803 - numba.core.ssa - DEBUG - on stmt: current_sum = const(int, 0)\n", - "2024-10-16 10:10:42,803 - numba.core.ssa - DEBUG - first assign: current_sum\n", - "2024-10-16 10:10:42,804 - numba.core.ssa - DEBUG - replaced with: current_sum = const(int, 0)\n", - "2024-10-16 10:10:42,805 - numba.core.ssa - DEBUG - on stmt: $182load_global.3 = global(range: )\n", - "2024-10-16 10:10:42,805 - numba.core.ssa - DEBUG - on stmt: $186call_function.5 = call $182load_global.3(size, func=$182load_global.3, args=[Var(size, bruker.py:292)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,806 - numba.core.ssa - DEBUG - on stmt: $188get_iter.6 = getiter(value=$186call_function.5)\n", - "2024-10-16 10:10:42,807 - numba.core.ssa - DEBUG - on stmt: $phi190.1 = $188get_iter.6\n", - "2024-10-16 10:10:42,807 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:42,808 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 190\n", - "2024-10-16 10:10:42,809 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,809 - numba.core.ssa - DEBUG - on stmt: $190for_iter.2 = iternext(value=$phi190.1)\n", - "2024-10-16 10:10:42,810 - numba.core.ssa - DEBUG - on stmt: $190for_iter.3 = pair_first(value=$190for_iter.2)\n", - "2024-10-16 10:10:42,810 - numba.core.ssa - DEBUG - on stmt: $190for_iter.4 = pair_second(value=$190for_iter.2)\n", - "2024-10-16 10:10:42,811 - numba.core.ssa - DEBUG - on stmt: $phi192.2 = $190for_iter.3\n", - "2024-10-16 10:10:42,811 - numba.core.ssa - DEBUG - on stmt: branch $190for_iter.4, 192, 224\n", - "2024-10-16 10:10:42,812 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:10:42,813 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,813 - numba.core.ssa - DEBUG - on stmt: i = $phi192.2\n", - "2024-10-16 10:10:42,814 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.6 = getitem(value=tof_indices, index=index, fn=)\n", - "2024-10-16 10:10:42,815 - numba.core.ssa - DEBUG - on stmt: $202inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=current_sum, rhs=$200binary_subscr.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,815 - numba.core.ssa - DEBUG - on stmt: current_sum = $202inplace_add.7\n", - "2024-10-16 10:10:42,816 - numba.core.ssa - DEBUG - replaced with: current_sum.1 = $202inplace_add.7\n", - "2024-10-16 10:10:42,816 - numba.core.ssa - DEBUG - on stmt: tof_indices[index] = current_sum\n", - "2024-10-16 10:10:42,817 - numba.core.ssa - DEBUG - on stmt: $const216.12 = const(int, 1)\n", - "2024-10-16 10:10:42,818 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.13 = inplace_binop(fn=, immutable_fn=, lhs=index, rhs=$const216.12, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,818 - numba.core.ssa - DEBUG - on stmt: index = $218inplace_add.13\n", - "2024-10-16 10:10:42,819 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:42,819 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 224\n", - "2024-10-16 10:10:42,820 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,821 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:42,821 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 226\n", - "2024-10-16 10:10:42,822 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,822 - numba.core.ssa - DEBUG - on stmt: $const230.2 = const(int, 1)\n", - "2024-10-16 10:10:42,823 - numba.core.ssa - DEBUG - on stmt: $232binary_subtract.3 = tof_indices - $const230.2\n", - "2024-10-16 10:10:42,823 - numba.core.ssa - DEBUG - on stmt: $236build_tuple.5 = build_tuple(items=[Var(scan_indices, bruker.py:285), Var($232binary_subtract.3, bruker.py:298), Var(intensities, bruker.py:286)])\n", - "2024-10-16 10:10:42,824 - numba.core.ssa - DEBUG - on stmt: $238return_value.6 = cast(value=$236build_tuple.5)\n", - "2024-10-16 10:10:42,825 - numba.core.ssa - DEBUG - on stmt: return $238return_value.6\n", - "2024-10-16 10:10:42,825 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {176: [],\n", - " 192: []})\n", - "2024-10-16 10:10:42,826 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:42,827 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,828 - numba.core.ssa - DEBUG - on stmt: decompressed_bytes = arg(0, name=decompressed_bytes)\n", - "2024-10-16 10:10:42,828 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:10:42,829 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=frombuffer)\n", - "2024-10-16 10:10:42,829 - numba.core.ssa - DEBUG - on stmt: $8load_global.3 = global(np: )\n", - "2024-10-16 10:10:42,830 - numba.core.ssa - DEBUG - on stmt: $10load_attr.4 = getattr(value=$8load_global.3, attr=uint8)\n", - "2024-10-16 10:10:42,831 - numba.core.ssa - DEBUG - on stmt: temp = call $4load_attr.1(decompressed_bytes, func=$4load_attr.1, args=[Var(decompressed_bytes, bruker.py:267)], kws=[('dtype', Var($10load_attr.4, bruker.py:282))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,831 - numba.core.ssa - DEBUG - on stmt: $18load_global.7 = global(np: )\n", - "2024-10-16 10:10:42,838 - numba.core.ssa - DEBUG - on stmt: $20load_attr.8 = getattr(value=$18load_global.7, attr=frombuffer)\n", - "2024-10-16 10:10:42,839 - numba.core.ssa - DEBUG - on stmt: $24load_method.10 = getattr(value=temp, attr=reshape)\n", - "2024-10-16 10:10:42,840 - numba.core.ssa - DEBUG - on stmt: $const26.11 = const(int, 4)\n", - "2024-10-16 10:10:42,840 - numba.core.ssa - DEBUG - on stmt: $const28.12 = const(int, -1)\n", - "2024-10-16 10:10:42,841 - numba.core.ssa - DEBUG - on stmt: $30call_method.13 = call $24load_method.10($const26.11, $const28.12, func=$24load_method.10, args=[Var($const26.11, bruker.py:283), Var($const28.12, bruker.py:283)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,841 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30call_method.13, attr=T)\n", - "2024-10-16 10:10:42,842 - numba.core.ssa - DEBUG - on stmt: $34load_method.15 = getattr(value=$32load_attr.14, attr=flatten)\n", - "2024-10-16 10:10:42,843 - numba.core.ssa - DEBUG - on stmt: $36call_method.16 = call $34load_method.15(func=$34load_method.15, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,843 - numba.core.ssa - DEBUG - on stmt: $38load_global.17 = global(np: )\n", - "2024-10-16 10:10:42,845 - numba.core.ssa - DEBUG - on stmt: $40load_attr.18 = getattr(value=$38load_global.17, attr=uint32)\n", - "2024-10-16 10:10:42,846 - numba.core.ssa - DEBUG - on stmt: buffer = call $20load_attr.8($36call_method.16, func=$20load_attr.8, args=[Var($36call_method.16, bruker.py:283)], kws=[('dtype', Var($40load_attr.18, bruker.py:283))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,846 - numba.core.ssa - DEBUG - on stmt: $const50.22 = const(int, 0)\n", - "2024-10-16 10:10:42,847 - numba.core.ssa - DEBUG - on stmt: scan_count = static_getitem(value=buffer, index=0, index_var=$const50.22, fn=)\n", - "2024-10-16 10:10:42,847 - numba.core.ssa - DEBUG - on stmt: $const58.25 = const(NoneType, None)\n", - "2024-10-16 10:10:42,848 - numba.core.ssa - DEBUG - on stmt: $62build_slice.27 = global(slice: )\n", - "2024-10-16 10:10:42,849 - numba.core.ssa - DEBUG - on stmt: $62build_slice.28 = call $62build_slice.27($const58.25, scan_count, func=$62build_slice.27, args=(Var($const58.25, bruker.py:285), Var(scan_count, bruker.py:284)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,849 - numba.core.ssa - DEBUG - on stmt: $64binary_subscr.29 = getitem(value=buffer, index=$62build_slice.28, fn=)\n", - "2024-10-16 10:10:42,850 - numba.core.ssa - DEBUG - on stmt: $66load_method.30 = getattr(value=$64binary_subscr.29, attr=copy)\n", - "2024-10-16 10:10:42,850 - numba.core.ssa - DEBUG - on stmt: $68call_method.31 = call $66load_method.30(func=$66load_method.30, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,851 - numba.core.ssa - DEBUG - on stmt: $const70.32 = const(int, 2)\n", - "2024-10-16 10:10:42,852 - numba.core.ssa - DEBUG - on stmt: scan_indices = $68call_method.31 // $const70.32\n", - "2024-10-16 10:10:42,852 - numba.core.ssa - DEBUG - on stmt: $const80.36 = const(int, 1)\n", - "2024-10-16 10:10:42,853 - numba.core.ssa - DEBUG - on stmt: $82binary_add.37 = scan_count + $const80.36\n", - "2024-10-16 10:10:42,854 - numba.core.ssa - DEBUG - on stmt: $const84.38 = const(NoneType, None)\n", - "2024-10-16 10:10:42,854 - numba.core.ssa - DEBUG - on stmt: $const86.39 = const(int, 2)\n", - "2024-10-16 10:10:42,855 - numba.core.ssa - DEBUG - on stmt: $88build_slice.40 = global(slice: )\n", - "2024-10-16 10:10:42,855 - numba.core.ssa - DEBUG - on stmt: $88build_slice.41 = call $88build_slice.40($82binary_add.37, $const84.38, $const86.39, func=$88build_slice.40, args=(Var($82binary_add.37, bruker.py:286), Var($const84.38, bruker.py:286), Var($const86.39, bruker.py:286)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,856 - numba.core.ssa - DEBUG - on stmt: intensities = getitem(value=buffer, index=$88build_slice.41, fn=)\n", - "2024-10-16 10:10:42,857 - numba.core.ssa - DEBUG - on stmt: $94load_global.43 = global(len: )\n", - "2024-10-16 10:10:42,857 - numba.core.ssa - DEBUG - on stmt: $98call_function.45 = call $94load_global.43(intensities, func=$94load_global.43, args=[Var(intensities, bruker.py:286)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,858 - numba.core.ssa - DEBUG - on stmt: $100load_global.46 = global(np: )\n", - "2024-10-16 10:10:42,858 - numba.core.ssa - DEBUG - on stmt: $102load_method.47 = getattr(value=$100load_global.46, attr=sum)\n", - "2024-10-16 10:10:42,859 - numba.core.ssa - DEBUG - on stmt: $const106.49 = const(int, 1)\n", - "2024-10-16 10:10:42,859 - numba.core.ssa - DEBUG - on stmt: $const108.50 = const(NoneType, None)\n", - "2024-10-16 10:10:42,860 - numba.core.ssa - DEBUG - on stmt: $110build_slice.51 = global(slice: )\n", - "2024-10-16 10:10:42,861 - numba.core.ssa - DEBUG - on stmt: $110build_slice.52 = call $110build_slice.51($const106.49, $const108.50, func=$110build_slice.51, args=(Var($const106.49, bruker.py:287), Var($const108.50, bruker.py:287)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,861 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.53 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$110build_slice.52, fn=)\n", - "2024-10-16 10:10:42,862 - numba.core.ssa - DEBUG - on stmt: $114call_method.54 = call $102load_method.47($112binary_subscr.53, func=$102load_method.47, args=[Var($112binary_subscr.53, bruker.py:287)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,862 - numba.core.ssa - DEBUG - on stmt: last_scan = $98call_function.45 - $114call_method.54\n", - "2024-10-16 10:10:42,863 - numba.core.ssa - DEBUG - on stmt: $const122.57 = const(int, 1)\n", - "2024-10-16 10:10:42,864 - numba.core.ssa - DEBUG - on stmt: $const124.58 = const(NoneType, None)\n", - "2024-10-16 10:10:42,864 - numba.core.ssa - DEBUG - on stmt: $126build_slice.59 = global(slice: )\n", - "2024-10-16 10:10:42,865 - numba.core.ssa - DEBUG - on stmt: $126build_slice.60 = call $126build_slice.59($const122.57, $const124.58, func=$126build_slice.59, args=(Var($const122.57, bruker.py:288), Var($const124.58, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,865 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.61 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$126build_slice.60, fn=)\n", - "2024-10-16 10:10:42,866 - numba.core.ssa - DEBUG - on stmt: $const132.63 = const(NoneType, None)\n", - "2024-10-16 10:10:42,867 - numba.core.ssa - DEBUG - on stmt: $const134.64 = const(int, -1)\n", - "2024-10-16 10:10:42,867 - numba.core.ssa - DEBUG - on stmt: $136build_slice.65 = global(slice: )\n", - "2024-10-16 10:10:42,868 - numba.core.ssa - DEBUG - on stmt: $136build_slice.66 = call $136build_slice.65($const132.63, $const134.64, func=$136build_slice.65, args=(Var($const132.63, bruker.py:288), Var($const134.64, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,869 - numba.core.ssa - DEBUG - on stmt: scan_indices[slice(None, -1, None)] = $128binary_subscr.61\n", - "2024-10-16 10:10:42,869 - numba.core.ssa - DEBUG - on stmt: $const144.69 = const(int, -1)\n", - "2024-10-16 10:10:42,870 - numba.core.ssa - DEBUG - on stmt: scan_indices[-1] = last_scan\n", - "2024-10-16 10:10:42,870 - numba.core.ssa - DEBUG - on stmt: $const152.72 = const(NoneType, None)\n", - "2024-10-16 10:10:42,871 - numba.core.ssa - DEBUG - on stmt: $const154.73 = const(int, 2)\n", - "2024-10-16 10:10:42,871 - numba.core.ssa - DEBUG - on stmt: $156build_slice.74 = global(slice: )\n", - "2024-10-16 10:10:42,872 - numba.core.ssa - DEBUG - on stmt: $156build_slice.75 = call $156build_slice.74(scan_count, $const152.72, $const154.73, func=$156build_slice.74, args=(Var(scan_count, bruker.py:284), Var($const152.72, bruker.py:290), Var($const154.73, bruker.py:290)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,873 - numba.core.ssa - DEBUG - on stmt: $158binary_subscr.76 = getitem(value=buffer, index=$156build_slice.75, fn=)\n", - "2024-10-16 10:10:42,873 - numba.core.ssa - DEBUG - on stmt: $160load_method.77 = getattr(value=$158binary_subscr.76, attr=copy)\n", - "2024-10-16 10:10:42,874 - numba.core.ssa - DEBUG - on stmt: tof_indices = call $160load_method.77(func=$160load_method.77, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,875 - numba.core.ssa - DEBUG - on stmt: index = const(int, 0)\n", - "2024-10-16 10:10:42,875 - numba.core.ssa - DEBUG - on stmt: $172get_iter.81 = getiter(value=scan_indices)\n", - "2024-10-16 10:10:42,876 - numba.core.ssa - DEBUG - on stmt: $phi174.0 = $172get_iter.81\n", - "2024-10-16 10:10:42,876 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:42,877 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 174\n", - "2024-10-16 10:10:42,877 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,878 - numba.core.ssa - DEBUG - on stmt: $174for_iter.1 = iternext(value=$phi174.0)\n", - "2024-10-16 10:10:42,879 - numba.core.ssa - DEBUG - on stmt: $174for_iter.2 = pair_first(value=$174for_iter.1)\n", - "2024-10-16 10:10:42,879 - numba.core.ssa - DEBUG - on stmt: $174for_iter.3 = pair_second(value=$174for_iter.1)\n", - "2024-10-16 10:10:42,880 - numba.core.ssa - DEBUG - on stmt: $phi176.1 = $174for_iter.2\n", - "2024-10-16 10:10:42,880 - numba.core.ssa - DEBUG - on stmt: branch $174for_iter.3, 176, 226\n", - "2024-10-16 10:10:42,881 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 176\n", - "2024-10-16 10:10:42,882 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,882 - numba.core.ssa - DEBUG - on stmt: size = $phi176.1\n", - "2024-10-16 10:10:42,883 - numba.core.ssa - DEBUG - on stmt: current_sum = const(int, 0)\n", - "2024-10-16 10:10:42,883 - numba.core.ssa - DEBUG - on stmt: $182load_global.3 = global(range: )\n", - "2024-10-16 10:10:42,884 - numba.core.ssa - DEBUG - on stmt: $186call_function.5 = call $182load_global.3(size, func=$182load_global.3, args=[Var(size, bruker.py:292)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,884 - numba.core.ssa - DEBUG - on stmt: $188get_iter.6 = getiter(value=$186call_function.5)\n", - "2024-10-16 10:10:42,885 - numba.core.ssa - DEBUG - on stmt: $phi190.1 = $188get_iter.6\n", - "2024-10-16 10:10:42,894 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:42,895 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 190\n", - "2024-10-16 10:10:42,896 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,896 - numba.core.ssa - DEBUG - on stmt: $190for_iter.2 = iternext(value=$phi190.1)\n", - "2024-10-16 10:10:42,897 - numba.core.ssa - DEBUG - on stmt: $190for_iter.3 = pair_first(value=$190for_iter.2)\n", - "2024-10-16 10:10:42,898 - numba.core.ssa - DEBUG - on stmt: $190for_iter.4 = pair_second(value=$190for_iter.2)\n", - "2024-10-16 10:10:42,898 - numba.core.ssa - DEBUG - on stmt: $phi192.2 = $190for_iter.3\n", - "2024-10-16 10:10:42,899 - numba.core.ssa - DEBUG - on stmt: branch $190for_iter.4, 192, 224\n", - "2024-10-16 10:10:42,900 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:10:42,901 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,901 - numba.core.ssa - DEBUG - on stmt: i = $phi192.2\n", - "2024-10-16 10:10:42,902 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.6 = getitem(value=tof_indices, index=index, fn=)\n", - "2024-10-16 10:10:42,903 - numba.core.ssa - DEBUG - on stmt: $202inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=current_sum, rhs=$200binary_subscr.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,903 - numba.core.ssa - DEBUG - find_def var='current_sum' stmt=$202inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=current_sum, rhs=$200binary_subscr.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,904 - numba.core.ssa - DEBUG - find_def_from_top label 192\n", - "2024-10-16 10:10:42,905 - numba.core.ssa - DEBUG - idom 190 from label 192\n", - "2024-10-16 10:10:42,905 - numba.core.ssa - DEBUG - find_def_from_bottom label 190\n", - "2024-10-16 10:10:42,906 - numba.core.ssa - DEBUG - find_def_from_top label 190\n", - "2024-10-16 10:10:42,906 - numba.core.ssa - DEBUG - insert phi node current_sum.2 = phi(incoming_values=[], incoming_blocks=[]) at 190\n", - "2024-10-16 10:10:42,907 - numba.core.ssa - DEBUG - find_def_from_bottom label 176\n", - "2024-10-16 10:10:42,907 - numba.core.ssa - DEBUG - incoming_def current_sum = const(int, 0)\n", - "2024-10-16 10:10:42,908 - numba.core.ssa - DEBUG - find_def_from_bottom label 192\n", - "2024-10-16 10:10:42,908 - numba.core.ssa - DEBUG - incoming_def current_sum.1 = $202inplace_add.7\n", - "2024-10-16 10:10:42,909 - numba.core.ssa - DEBUG - replaced with: $202inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=current_sum.2, rhs=$200binary_subscr.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,911 - numba.core.ssa - DEBUG - on stmt: current_sum.1 = $202inplace_add.7\n", - "2024-10-16 10:10:42,912 - numba.core.ssa - DEBUG - on stmt: tof_indices[index] = current_sum\n", - "2024-10-16 10:10:42,912 - numba.core.ssa - DEBUG - find_def var='current_sum' stmt=tof_indices[index] = current_sum\n", - "2024-10-16 10:10:42,913 - numba.core.ssa - DEBUG - replaced with: tof_indices[index] = current_sum.1\n", - "2024-10-16 10:10:42,913 - numba.core.ssa - DEBUG - on stmt: $const216.12 = const(int, 1)\n", - "2024-10-16 10:10:42,914 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.13 = inplace_binop(fn=, immutable_fn=, lhs=index, rhs=$const216.12, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,915 - numba.core.ssa - DEBUG - on stmt: index = $218inplace_add.13\n", - "2024-10-16 10:10:42,915 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:42,916 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 224\n", - "2024-10-16 10:10:42,916 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,917 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:42,917 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 226\n", - "2024-10-16 10:10:42,920 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,920 - numba.core.ssa - DEBUG - on stmt: $const230.2 = const(int, 1)\n", - "2024-10-16 10:10:42,921 - numba.core.ssa - DEBUG - on stmt: $232binary_subtract.3 = tof_indices - $const230.2\n", - "2024-10-16 10:10:42,922 - numba.core.ssa - DEBUG - on stmt: $236build_tuple.5 = build_tuple(items=[Var(scan_indices, bruker.py:285), Var($232binary_subtract.3, bruker.py:298), Var(intensities, bruker.py:286)])\n", - "2024-10-16 10:10:42,922 - numba.core.ssa - DEBUG - on stmt: $238return_value.6 = cast(value=$236build_tuple.5)\n", - "2024-10-16 10:10:42,923 - numba.core.ssa - DEBUG - on stmt: return $238return_value.6\n", - "2024-10-16 10:10:42,923 - numba.core.ssa - DEBUG - Fix SSA violator on var index\n", - "2024-10-16 10:10:42,924 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:42,924 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,925 - numba.core.ssa - DEBUG - on stmt: decompressed_bytes = arg(0, name=decompressed_bytes)\n", - "2024-10-16 10:10:42,926 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:10:42,926 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=frombuffer)\n", - "2024-10-16 10:10:42,927 - numba.core.ssa - DEBUG - on stmt: $8load_global.3 = global(np: )\n", - "2024-10-16 10:10:42,927 - numba.core.ssa - DEBUG - on stmt: $10load_attr.4 = getattr(value=$8load_global.3, attr=uint8)\n", - "2024-10-16 10:10:42,928 - numba.core.ssa - DEBUG - on stmt: temp = call $4load_attr.1(decompressed_bytes, func=$4load_attr.1, args=[Var(decompressed_bytes, bruker.py:267)], kws=[('dtype', Var($10load_attr.4, bruker.py:282))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,928 - numba.core.ssa - DEBUG - on stmt: $18load_global.7 = global(np: )\n", - "2024-10-16 10:10:42,929 - numba.core.ssa - DEBUG - on stmt: $20load_attr.8 = getattr(value=$18load_global.7, attr=frombuffer)\n", - "2024-10-16 10:10:42,929 - numba.core.ssa - DEBUG - on stmt: $24load_method.10 = getattr(value=temp, attr=reshape)\n", - "2024-10-16 10:10:42,930 - numba.core.ssa - DEBUG - on stmt: $const26.11 = const(int, 4)\n", - "2024-10-16 10:10:42,931 - numba.core.ssa - DEBUG - on stmt: $const28.12 = const(int, -1)\n", - "2024-10-16 10:10:42,931 - numba.core.ssa - DEBUG - on stmt: $30call_method.13 = call $24load_method.10($const26.11, $const28.12, func=$24load_method.10, args=[Var($const26.11, bruker.py:283), Var($const28.12, bruker.py:283)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,932 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30call_method.13, attr=T)\n", - "2024-10-16 10:10:42,932 - numba.core.ssa - DEBUG - on stmt: $34load_method.15 = getattr(value=$32load_attr.14, attr=flatten)\n", - "2024-10-16 10:10:42,933 - numba.core.ssa - DEBUG - on stmt: $36call_method.16 = call $34load_method.15(func=$34load_method.15, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,933 - numba.core.ssa - DEBUG - on stmt: $38load_global.17 = global(np: )\n", - "2024-10-16 10:10:42,934 - numba.core.ssa - DEBUG - on stmt: $40load_attr.18 = getattr(value=$38load_global.17, attr=uint32)\n", - "2024-10-16 10:10:42,935 - numba.core.ssa - DEBUG - on stmt: buffer = call $20load_attr.8($36call_method.16, func=$20load_attr.8, args=[Var($36call_method.16, bruker.py:283)], kws=[('dtype', Var($40load_attr.18, bruker.py:283))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,938 - numba.core.ssa - DEBUG - on stmt: $const50.22 = const(int, 0)\n", - "2024-10-16 10:10:42,939 - numba.core.ssa - DEBUG - on stmt: scan_count = static_getitem(value=buffer, index=0, index_var=$const50.22, fn=)\n", - "2024-10-16 10:10:42,939 - numba.core.ssa - DEBUG - on stmt: $const58.25 = const(NoneType, None)\n", - "2024-10-16 10:10:42,940 - numba.core.ssa - DEBUG - on stmt: $62build_slice.27 = global(slice: )\n", - "2024-10-16 10:10:42,940 - numba.core.ssa - DEBUG - on stmt: $62build_slice.28 = call $62build_slice.27($const58.25, scan_count, func=$62build_slice.27, args=(Var($const58.25, bruker.py:285), Var(scan_count, bruker.py:284)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,941 - numba.core.ssa - DEBUG - on stmt: $64binary_subscr.29 = getitem(value=buffer, index=$62build_slice.28, fn=)\n", - "2024-10-16 10:10:42,942 - numba.core.ssa - DEBUG - on stmt: $66load_method.30 = getattr(value=$64binary_subscr.29, attr=copy)\n", - "2024-10-16 10:10:42,943 - numba.core.ssa - DEBUG - on stmt: $68call_method.31 = call $66load_method.30(func=$66load_method.30, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,943 - numba.core.ssa - DEBUG - on stmt: $const70.32 = const(int, 2)\n", - "2024-10-16 10:10:42,944 - numba.core.ssa - DEBUG - on stmt: scan_indices = $68call_method.31 // $const70.32\n", - "2024-10-16 10:10:42,945 - numba.core.ssa - DEBUG - on stmt: $const80.36 = const(int, 1)\n", - "2024-10-16 10:10:42,945 - numba.core.ssa - DEBUG - on stmt: $82binary_add.37 = scan_count + $const80.36\n", - "2024-10-16 10:10:42,946 - numba.core.ssa - DEBUG - on stmt: $const84.38 = const(NoneType, None)\n", - "2024-10-16 10:10:42,947 - numba.core.ssa - DEBUG - on stmt: $const86.39 = const(int, 2)\n", - "2024-10-16 10:10:42,947 - numba.core.ssa - DEBUG - on stmt: $88build_slice.40 = global(slice: )\n", - "2024-10-16 10:10:42,948 - numba.core.ssa - DEBUG - on stmt: $88build_slice.41 = call $88build_slice.40($82binary_add.37, $const84.38, $const86.39, func=$88build_slice.40, args=(Var($82binary_add.37, bruker.py:286), Var($const84.38, bruker.py:286), Var($const86.39, bruker.py:286)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,948 - numba.core.ssa - DEBUG - on stmt: intensities = getitem(value=buffer, index=$88build_slice.41, fn=)\n", - "2024-10-16 10:10:42,949 - numba.core.ssa - DEBUG - on stmt: $94load_global.43 = global(len: )\n", - "2024-10-16 10:10:42,950 - numba.core.ssa - DEBUG - on stmt: $98call_function.45 = call $94load_global.43(intensities, func=$94load_global.43, args=[Var(intensities, bruker.py:286)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,951 - numba.core.ssa - DEBUG - on stmt: $100load_global.46 = global(np: )\n", - "2024-10-16 10:10:42,951 - numba.core.ssa - DEBUG - on stmt: $102load_method.47 = getattr(value=$100load_global.46, attr=sum)\n", - "2024-10-16 10:10:42,952 - numba.core.ssa - DEBUG - on stmt: $const106.49 = const(int, 1)\n", - "2024-10-16 10:10:42,952 - numba.core.ssa - DEBUG - on stmt: $const108.50 = const(NoneType, None)\n", - "2024-10-16 10:10:42,953 - numba.core.ssa - DEBUG - on stmt: $110build_slice.51 = global(slice: )\n", - "2024-10-16 10:10:42,953 - numba.core.ssa - DEBUG - on stmt: $110build_slice.52 = call $110build_slice.51($const106.49, $const108.50, func=$110build_slice.51, args=(Var($const106.49, bruker.py:287), Var($const108.50, bruker.py:287)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,954 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.53 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$110build_slice.52, fn=)\n", - "2024-10-16 10:10:42,955 - numba.core.ssa - DEBUG - on stmt: $114call_method.54 = call $102load_method.47($112binary_subscr.53, func=$102load_method.47, args=[Var($112binary_subscr.53, bruker.py:287)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,956 - numba.core.ssa - DEBUG - on stmt: last_scan = $98call_function.45 - $114call_method.54\n", - "2024-10-16 10:10:42,956 - numba.core.ssa - DEBUG - on stmt: $const122.57 = const(int, 1)\n", - "2024-10-16 10:10:42,957 - numba.core.ssa - DEBUG - on stmt: $const124.58 = const(NoneType, None)\n", - "2024-10-16 10:10:42,958 - numba.core.ssa - DEBUG - on stmt: $126build_slice.59 = global(slice: )\n", - "2024-10-16 10:10:42,958 - numba.core.ssa - DEBUG - on stmt: $126build_slice.60 = call $126build_slice.59($const122.57, $const124.58, func=$126build_slice.59, args=(Var($const122.57, bruker.py:288), Var($const124.58, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,959 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.61 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$126build_slice.60, fn=)\n", - "2024-10-16 10:10:42,960 - numba.core.ssa - DEBUG - on stmt: $const132.63 = const(NoneType, None)\n", - "2024-10-16 10:10:42,960 - numba.core.ssa - DEBUG - on stmt: $const134.64 = const(int, -1)\n", - "2024-10-16 10:10:42,961 - numba.core.ssa - DEBUG - on stmt: $136build_slice.65 = global(slice: )\n", - "2024-10-16 10:10:42,961 - numba.core.ssa - DEBUG - on stmt: $136build_slice.66 = call $136build_slice.65($const132.63, $const134.64, func=$136build_slice.65, args=(Var($const132.63, bruker.py:288), Var($const134.64, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,962 - numba.core.ssa - DEBUG - on stmt: scan_indices[slice(None, -1, None)] = $128binary_subscr.61\n", - "2024-10-16 10:10:42,963 - numba.core.ssa - DEBUG - on stmt: $const144.69 = const(int, -1)\n", - "2024-10-16 10:10:42,964 - numba.core.ssa - DEBUG - on stmt: scan_indices[-1] = last_scan\n", - "2024-10-16 10:10:42,964 - numba.core.ssa - DEBUG - on stmt: $const152.72 = const(NoneType, None)\n", - "2024-10-16 10:10:42,965 - numba.core.ssa - DEBUG - on stmt: $const154.73 = const(int, 2)\n", - "2024-10-16 10:10:42,965 - numba.core.ssa - DEBUG - on stmt: $156build_slice.74 = global(slice: )\n", - "2024-10-16 10:10:42,966 - numba.core.ssa - DEBUG - on stmt: $156build_slice.75 = call $156build_slice.74(scan_count, $const152.72, $const154.73, func=$156build_slice.74, args=(Var(scan_count, bruker.py:284), Var($const152.72, bruker.py:290), Var($const154.73, bruker.py:290)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,966 - numba.core.ssa - DEBUG - on stmt: $158binary_subscr.76 = getitem(value=buffer, index=$156build_slice.75, fn=)\n", - "2024-10-16 10:10:42,967 - numba.core.ssa - DEBUG - on stmt: $160load_method.77 = getattr(value=$158binary_subscr.76, attr=copy)\n", - "2024-10-16 10:10:42,968 - numba.core.ssa - DEBUG - on stmt: tof_indices = call $160load_method.77(func=$160load_method.77, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,968 - numba.core.ssa - DEBUG - on stmt: index = const(int, 0)\n", - "2024-10-16 10:10:42,969 - numba.core.ssa - DEBUG - first assign: index\n", - "2024-10-16 10:10:42,969 - numba.core.ssa - DEBUG - replaced with: index = const(int, 0)\n", - "2024-10-16 10:10:42,970 - numba.core.ssa - DEBUG - on stmt: $172get_iter.81 = getiter(value=scan_indices)\n", - "2024-10-16 10:10:42,970 - numba.core.ssa - DEBUG - on stmt: $phi174.0 = $172get_iter.81\n", - "2024-10-16 10:10:42,971 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:42,971 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 174\n", - "2024-10-16 10:10:42,972 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,972 - numba.core.ssa - DEBUG - on stmt: $174for_iter.1 = iternext(value=$phi174.0)\n", - "2024-10-16 10:10:42,973 - numba.core.ssa - DEBUG - on stmt: $174for_iter.2 = pair_first(value=$174for_iter.1)\n", - "2024-10-16 10:10:42,973 - numba.core.ssa - DEBUG - on stmt: $174for_iter.3 = pair_second(value=$174for_iter.1)\n", - "2024-10-16 10:10:42,974 - numba.core.ssa - DEBUG - on stmt: $phi176.1 = $174for_iter.2\n", - "2024-10-16 10:10:42,975 - numba.core.ssa - DEBUG - on stmt: branch $174for_iter.3, 176, 226\n", - "2024-10-16 10:10:42,975 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 176\n", - "2024-10-16 10:10:42,976 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,976 - numba.core.ssa - DEBUG - on stmt: size = $phi176.1\n", - "2024-10-16 10:10:42,976 - numba.core.ssa - DEBUG - on stmt: current_sum = const(int, 0)\n", - "2024-10-16 10:10:42,977 - numba.core.ssa - DEBUG - on stmt: $182load_global.3 = global(range: )\n", - "2024-10-16 10:10:42,978 - numba.core.ssa - DEBUG - on stmt: $186call_function.5 = call $182load_global.3(size, func=$182load_global.3, args=[Var(size, bruker.py:292)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:42,978 - numba.core.ssa - DEBUG - on stmt: $188get_iter.6 = getiter(value=$186call_function.5)\n", - "2024-10-16 10:10:42,982 - numba.core.ssa - DEBUG - on stmt: $phi190.1 = $188get_iter.6\n", - "2024-10-16 10:10:42,982 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:42,983 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 190\n", - "2024-10-16 10:10:42,983 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,984 - numba.core.ssa - DEBUG - on stmt: current_sum.2 = phi(incoming_values=[Var(current_sum, bruker.py:293), Var(current_sum.1, bruker.py:295)], incoming_blocks=[176, 192])\n", - "2024-10-16 10:10:42,985 - numba.core.ssa - DEBUG - on stmt: $190for_iter.2 = iternext(value=$phi190.1)\n", - "2024-10-16 10:10:42,985 - numba.core.ssa - DEBUG - on stmt: $190for_iter.3 = pair_first(value=$190for_iter.2)\n", - "2024-10-16 10:10:42,986 - numba.core.ssa - DEBUG - on stmt: $190for_iter.4 = pair_second(value=$190for_iter.2)\n", - "2024-10-16 10:10:42,986 - numba.core.ssa - DEBUG - on stmt: $phi192.2 = $190for_iter.3\n", - "2024-10-16 10:10:42,988 - numba.core.ssa - DEBUG - on stmt: branch $190for_iter.4, 192, 224\n", - "2024-10-16 10:10:42,988 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:10:42,989 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,989 - numba.core.ssa - DEBUG - on stmt: i = $phi192.2\n", - "2024-10-16 10:10:42,990 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.6 = getitem(value=tof_indices, index=index, fn=)\n", - "2024-10-16 10:10:42,990 - numba.core.ssa - DEBUG - on stmt: $202inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=current_sum.2, rhs=$200binary_subscr.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,991 - numba.core.ssa - DEBUG - on stmt: current_sum.1 = $202inplace_add.7\n", - "2024-10-16 10:10:42,991 - numba.core.ssa - DEBUG - on stmt: tof_indices[index] = current_sum.1\n", - "2024-10-16 10:10:42,992 - numba.core.ssa - DEBUG - on stmt: $const216.12 = const(int, 1)\n", - "2024-10-16 10:10:42,993 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.13 = inplace_binop(fn=, immutable_fn=, lhs=index, rhs=$const216.12, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:42,994 - numba.core.ssa - DEBUG - on stmt: index = $218inplace_add.13\n", - "2024-10-16 10:10:42,994 - numba.core.ssa - DEBUG - replaced with: index.1 = $218inplace_add.13\n", - "2024-10-16 10:10:42,995 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:42,996 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 224\n", - "2024-10-16 10:10:42,997 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,997 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:42,998 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 226\n", - "2024-10-16 10:10:42,999 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:42,999 - numba.core.ssa - DEBUG - on stmt: $const230.2 = const(int, 1)\n", - "2024-10-16 10:10:43,000 - numba.core.ssa - DEBUG - on stmt: $232binary_subtract.3 = tof_indices - $const230.2\n", - "2024-10-16 10:10:43,001 - numba.core.ssa - DEBUG - on stmt: $236build_tuple.5 = build_tuple(items=[Var(scan_indices, bruker.py:285), Var($232binary_subtract.3, bruker.py:298), Var(intensities, bruker.py:286)])\n", - "2024-10-16 10:10:43,001 - numba.core.ssa - DEBUG - on stmt: $238return_value.6 = cast(value=$236build_tuple.5)\n", - "2024-10-16 10:10:43,002 - numba.core.ssa - DEBUG - on stmt: return $238return_value.6\n", - "2024-10-16 10:10:43,003 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 192: []})\n", - "2024-10-16 10:10:43,003 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:43,004 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,004 - numba.core.ssa - DEBUG - on stmt: decompressed_bytes = arg(0, name=decompressed_bytes)\n", - "2024-10-16 10:10:43,005 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:10:43,005 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=frombuffer)\n", - "2024-10-16 10:10:43,007 - numba.core.ssa - DEBUG - on stmt: $8load_global.3 = global(np: )\n", - "2024-10-16 10:10:43,007 - numba.core.ssa - DEBUG - on stmt: $10load_attr.4 = getattr(value=$8load_global.3, attr=uint8)\n", - "2024-10-16 10:10:43,008 - numba.core.ssa - DEBUG - on stmt: temp = call $4load_attr.1(decompressed_bytes, func=$4load_attr.1, args=[Var(decompressed_bytes, bruker.py:267)], kws=[('dtype', Var($10load_attr.4, bruker.py:282))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,008 - numba.core.ssa - DEBUG - on stmt: $18load_global.7 = global(np: )\n", - "2024-10-16 10:10:43,009 - numba.core.ssa - DEBUG - on stmt: $20load_attr.8 = getattr(value=$18load_global.7, attr=frombuffer)\n", - "2024-10-16 10:10:43,010 - numba.core.ssa - DEBUG - on stmt: $24load_method.10 = getattr(value=temp, attr=reshape)\n", - "2024-10-16 10:10:43,011 - numba.core.ssa - DEBUG - on stmt: $const26.11 = const(int, 4)\n", - "2024-10-16 10:10:43,011 - numba.core.ssa - DEBUG - on stmt: $const28.12 = const(int, -1)\n", - "2024-10-16 10:10:43,012 - numba.core.ssa - DEBUG - on stmt: $30call_method.13 = call $24load_method.10($const26.11, $const28.12, func=$24load_method.10, args=[Var($const26.11, bruker.py:283), Var($const28.12, bruker.py:283)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,013 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30call_method.13, attr=T)\n", - "2024-10-16 10:10:43,013 - numba.core.ssa - DEBUG - on stmt: $34load_method.15 = getattr(value=$32load_attr.14, attr=flatten)\n", - "2024-10-16 10:10:43,014 - numba.core.ssa - DEBUG - on stmt: $36call_method.16 = call $34load_method.15(func=$34load_method.15, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,014 - numba.core.ssa - DEBUG - on stmt: $38load_global.17 = global(np: )\n", - "2024-10-16 10:10:43,015 - numba.core.ssa - DEBUG - on stmt: $40load_attr.18 = getattr(value=$38load_global.17, attr=uint32)\n", - "2024-10-16 10:10:43,015 - numba.core.ssa - DEBUG - on stmt: buffer = call $20load_attr.8($36call_method.16, func=$20load_attr.8, args=[Var($36call_method.16, bruker.py:283)], kws=[('dtype', Var($40load_attr.18, bruker.py:283))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,016 - numba.core.ssa - DEBUG - on stmt: $const50.22 = const(int, 0)\n", - "2024-10-16 10:10:43,017 - numba.core.ssa - DEBUG - on stmt: scan_count = static_getitem(value=buffer, index=0, index_var=$const50.22, fn=)\n", - "2024-10-16 10:10:43,017 - numba.core.ssa - DEBUG - on stmt: $const58.25 = const(NoneType, None)\n", - "2024-10-16 10:10:43,018 - numba.core.ssa - DEBUG - on stmt: $62build_slice.27 = global(slice: )\n", - "2024-10-16 10:10:43,018 - numba.core.ssa - DEBUG - on stmt: $62build_slice.28 = call $62build_slice.27($const58.25, scan_count, func=$62build_slice.27, args=(Var($const58.25, bruker.py:285), Var(scan_count, bruker.py:284)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,019 - numba.core.ssa - DEBUG - on stmt: $64binary_subscr.29 = getitem(value=buffer, index=$62build_slice.28, fn=)\n", - "2024-10-16 10:10:43,019 - numba.core.ssa - DEBUG - on stmt: $66load_method.30 = getattr(value=$64binary_subscr.29, attr=copy)\n", - "2024-10-16 10:10:43,020 - numba.core.ssa - DEBUG - on stmt: $68call_method.31 = call $66load_method.30(func=$66load_method.30, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,020 - numba.core.ssa - DEBUG - on stmt: $const70.32 = const(int, 2)\n", - "2024-10-16 10:10:43,023 - numba.core.ssa - DEBUG - on stmt: scan_indices = $68call_method.31 // $const70.32\n", - "2024-10-16 10:10:43,023 - numba.core.ssa - DEBUG - on stmt: $const80.36 = const(int, 1)\n", - "2024-10-16 10:10:43,024 - numba.core.ssa - DEBUG - on stmt: $82binary_add.37 = scan_count + $const80.36\n", - "2024-10-16 10:10:43,024 - numba.core.ssa - DEBUG - on stmt: $const84.38 = const(NoneType, None)\n", - "2024-10-16 10:10:43,025 - numba.core.ssa - DEBUG - on stmt: $const86.39 = const(int, 2)\n", - "2024-10-16 10:10:43,025 - numba.core.ssa - DEBUG - on stmt: $88build_slice.40 = global(slice: )\n", - "2024-10-16 10:10:43,026 - numba.core.ssa - DEBUG - on stmt: $88build_slice.41 = call $88build_slice.40($82binary_add.37, $const84.38, $const86.39, func=$88build_slice.40, args=(Var($82binary_add.37, bruker.py:286), Var($const84.38, bruker.py:286), Var($const86.39, bruker.py:286)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,027 - numba.core.ssa - DEBUG - on stmt: intensities = getitem(value=buffer, index=$88build_slice.41, fn=)\n", - "2024-10-16 10:10:43,028 - numba.core.ssa - DEBUG - on stmt: $94load_global.43 = global(len: )\n", - "2024-10-16 10:10:43,028 - numba.core.ssa - DEBUG - on stmt: $98call_function.45 = call $94load_global.43(intensities, func=$94load_global.43, args=[Var(intensities, bruker.py:286)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,029 - numba.core.ssa - DEBUG - on stmt: $100load_global.46 = global(np: )\n", - "2024-10-16 10:10:43,030 - numba.core.ssa - DEBUG - on stmt: $102load_method.47 = getattr(value=$100load_global.46, attr=sum)\n", - "2024-10-16 10:10:43,030 - numba.core.ssa - DEBUG - on stmt: $const106.49 = const(int, 1)\n", - "2024-10-16 10:10:43,031 - numba.core.ssa - DEBUG - on stmt: $const108.50 = const(NoneType, None)\n", - "2024-10-16 10:10:43,032 - numba.core.ssa - DEBUG - on stmt: $110build_slice.51 = global(slice: )\n", - "2024-10-16 10:10:43,032 - numba.core.ssa - DEBUG - on stmt: $110build_slice.52 = call $110build_slice.51($const106.49, $const108.50, func=$110build_slice.51, args=(Var($const106.49, bruker.py:287), Var($const108.50, bruker.py:287)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,033 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.53 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$110build_slice.52, fn=)\n", - "2024-10-16 10:10:43,033 - numba.core.ssa - DEBUG - on stmt: $114call_method.54 = call $102load_method.47($112binary_subscr.53, func=$102load_method.47, args=[Var($112binary_subscr.53, bruker.py:287)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,034 - numba.core.ssa - DEBUG - on stmt: last_scan = $98call_function.45 - $114call_method.54\n", - "2024-10-16 10:10:43,034 - numba.core.ssa - DEBUG - on stmt: $const122.57 = const(int, 1)\n", - "2024-10-16 10:10:43,036 - numba.core.ssa - DEBUG - on stmt: $const124.58 = const(NoneType, None)\n", - "2024-10-16 10:10:43,036 - numba.core.ssa - DEBUG - on stmt: $126build_slice.59 = global(slice: )\n", - "2024-10-16 10:10:43,037 - numba.core.ssa - DEBUG - on stmt: $126build_slice.60 = call $126build_slice.59($const122.57, $const124.58, func=$126build_slice.59, args=(Var($const122.57, bruker.py:288), Var($const124.58, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,038 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.61 = static_getitem(value=scan_indices, index=slice(1, None, None), index_var=$126build_slice.60, fn=)\n", - "2024-10-16 10:10:43,038 - numba.core.ssa - DEBUG - on stmt: $const132.63 = const(NoneType, None)\n", - "2024-10-16 10:10:43,039 - numba.core.ssa - DEBUG - on stmt: $const134.64 = const(int, -1)\n", - "2024-10-16 10:10:43,039 - numba.core.ssa - DEBUG - on stmt: $136build_slice.65 = global(slice: )\n", - "2024-10-16 10:10:43,040 - numba.core.ssa - DEBUG - on stmt: $136build_slice.66 = call $136build_slice.65($const132.63, $const134.64, func=$136build_slice.65, args=(Var($const132.63, bruker.py:288), Var($const134.64, bruker.py:288)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,041 - numba.core.ssa - DEBUG - on stmt: scan_indices[slice(None, -1, None)] = $128binary_subscr.61\n", - "2024-10-16 10:10:43,041 - numba.core.ssa - DEBUG - on stmt: $const144.69 = const(int, -1)\n", - "2024-10-16 10:10:43,042 - numba.core.ssa - DEBUG - on stmt: scan_indices[-1] = last_scan\n", - "2024-10-16 10:10:43,042 - numba.core.ssa - DEBUG - on stmt: $const152.72 = const(NoneType, None)\n", - "2024-10-16 10:10:43,043 - numba.core.ssa - DEBUG - on stmt: $const154.73 = const(int, 2)\n", - "2024-10-16 10:10:43,044 - numba.core.ssa - DEBUG - on stmt: $156build_slice.74 = global(slice: )\n", - "2024-10-16 10:10:43,044 - numba.core.ssa - DEBUG - on stmt: $156build_slice.75 = call $156build_slice.74(scan_count, $const152.72, $const154.73, func=$156build_slice.74, args=(Var(scan_count, bruker.py:284), Var($const152.72, bruker.py:290), Var($const154.73, bruker.py:290)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,045 - numba.core.ssa - DEBUG - on stmt: $158binary_subscr.76 = getitem(value=buffer, index=$156build_slice.75, fn=)\n", - "2024-10-16 10:10:43,046 - numba.core.ssa - DEBUG - on stmt: $160load_method.77 = getattr(value=$158binary_subscr.76, attr=copy)\n", - "2024-10-16 10:10:43,047 - numba.core.ssa - DEBUG - on stmt: tof_indices = call $160load_method.77(func=$160load_method.77, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,047 - numba.core.ssa - DEBUG - on stmt: index = const(int, 0)\n", - "2024-10-16 10:10:43,048 - numba.core.ssa - DEBUG - on stmt: $172get_iter.81 = getiter(value=scan_indices)\n", - "2024-10-16 10:10:43,049 - numba.core.ssa - DEBUG - on stmt: $phi174.0 = $172get_iter.81\n", - "2024-10-16 10:10:43,049 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:43,050 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 174\n", - "2024-10-16 10:10:43,050 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,051 - numba.core.ssa - DEBUG - on stmt: $174for_iter.1 = iternext(value=$phi174.0)\n", - "2024-10-16 10:10:43,052 - numba.core.ssa - DEBUG - on stmt: $174for_iter.2 = pair_first(value=$174for_iter.1)\n", - "2024-10-16 10:10:43,053 - numba.core.ssa - DEBUG - on stmt: $174for_iter.3 = pair_second(value=$174for_iter.1)\n", - "2024-10-16 10:10:43,053 - numba.core.ssa - DEBUG - on stmt: $phi176.1 = $174for_iter.2\n", - "2024-10-16 10:10:43,054 - numba.core.ssa - DEBUG - on stmt: branch $174for_iter.3, 176, 226\n", - "2024-10-16 10:10:43,054 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 176\n", - "2024-10-16 10:10:43,055 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,055 - numba.core.ssa - DEBUG - on stmt: size = $phi176.1\n", - "2024-10-16 10:10:43,056 - numba.core.ssa - DEBUG - on stmt: current_sum = const(int, 0)\n", - "2024-10-16 10:10:43,057 - numba.core.ssa - DEBUG - on stmt: $182load_global.3 = global(range: )\n", - "2024-10-16 10:10:43,057 - numba.core.ssa - DEBUG - on stmt: $186call_function.5 = call $182load_global.3(size, func=$182load_global.3, args=[Var(size, bruker.py:292)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,058 - numba.core.ssa - DEBUG - on stmt: $188get_iter.6 = getiter(value=$186call_function.5)\n", - "2024-10-16 10:10:43,059 - numba.core.ssa - DEBUG - on stmt: $phi190.1 = $188get_iter.6\n", - "2024-10-16 10:10:43,059 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:43,060 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 190\n", - "2024-10-16 10:10:43,060 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,061 - numba.core.ssa - DEBUG - on stmt: current_sum.2 = phi(incoming_values=[Var(current_sum, bruker.py:293), Var(current_sum.1, bruker.py:295)], incoming_blocks=[176, 192])\n", - "2024-10-16 10:10:43,062 - numba.core.ssa - DEBUG - on stmt: $190for_iter.2 = iternext(value=$phi190.1)\n", - "2024-10-16 10:10:43,063 - numba.core.ssa - DEBUG - on stmt: $190for_iter.3 = pair_first(value=$190for_iter.2)\n", - "2024-10-16 10:10:43,063 - numba.core.ssa - DEBUG - on stmt: $190for_iter.4 = pair_second(value=$190for_iter.2)\n", - "2024-10-16 10:10:43,064 - numba.core.ssa - DEBUG - on stmt: $phi192.2 = $190for_iter.3\n", - "2024-10-16 10:10:43,065 - numba.core.ssa - DEBUG - on stmt: branch $190for_iter.4, 192, 224\n", - "2024-10-16 10:10:43,066 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:10:43,066 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,067 - numba.core.ssa - DEBUG - on stmt: i = $phi192.2\n", - "2024-10-16 10:10:43,067 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.6 = getitem(value=tof_indices, index=index, fn=)\n", - "2024-10-16 10:10:43,067 - numba.core.ssa - DEBUG - find_def var='index' stmt=$200binary_subscr.6 = getitem(value=tof_indices, index=index, fn=)\n", - "2024-10-16 10:10:43,068 - numba.core.ssa - DEBUG - find_def_from_top label 192\n", - "2024-10-16 10:10:43,069 - numba.core.ssa - DEBUG - idom 190 from label 192\n", - "2024-10-16 10:10:43,069 - numba.core.ssa - DEBUG - find_def_from_bottom label 190\n", - "2024-10-16 10:10:43,069 - numba.core.ssa - DEBUG - find_def_from_top label 190\n", - "2024-10-16 10:10:43,070 - numba.core.ssa - DEBUG - insert phi node index.2 = phi(incoming_values=[], incoming_blocks=[]) at 190\n", - "2024-10-16 10:10:43,071 - numba.core.ssa - DEBUG - find_def_from_bottom label 176\n", - "2024-10-16 10:10:43,071 - numba.core.ssa - DEBUG - find_def_from_top label 176\n", - "2024-10-16 10:10:43,072 - numba.core.ssa - DEBUG - idom 174 from label 176\n", - "2024-10-16 10:10:43,072 - numba.core.ssa - DEBUG - find_def_from_bottom label 174\n", - "2024-10-16 10:10:43,074 - numba.core.ssa - DEBUG - find_def_from_top label 174\n", - "2024-10-16 10:10:43,075 - numba.core.ssa - DEBUG - insert phi node index.3 = phi(incoming_values=[], incoming_blocks=[]) at 174\n", - "2024-10-16 10:10:43,075 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:10:43,076 - numba.core.ssa - DEBUG - incoming_def index = const(int, 0)\n", - "2024-10-16 10:10:43,076 - numba.core.ssa - DEBUG - find_def_from_bottom label 224\n", - "2024-10-16 10:10:43,077 - numba.core.ssa - DEBUG - find_def_from_top label 224\n", - "2024-10-16 10:10:43,077 - numba.core.ssa - DEBUG - idom 190 from label 224\n", - "2024-10-16 10:10:43,078 - numba.core.ssa - DEBUG - find_def_from_bottom label 190\n", - "2024-10-16 10:10:43,079 - numba.core.ssa - DEBUG - incoming_def index.2 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:10:43,079 - numba.core.ssa - DEBUG - incoming_def index.3 = phi(incoming_values=[Var(index, bruker.py:291), Var(index.2, bruker.py:294)], incoming_blocks=[0, 224])\n", - "2024-10-16 10:10:43,080 - numba.core.ssa - DEBUG - find_def_from_bottom label 192\n", - "2024-10-16 10:10:43,080 - numba.core.ssa - DEBUG - incoming_def index.1 = $218inplace_add.13\n", - "2024-10-16 10:10:43,081 - numba.core.ssa - DEBUG - replaced with: $200binary_subscr.6 = getitem(value=tof_indices, index=index.2, fn=)\n", - "2024-10-16 10:10:43,081 - numba.core.ssa - DEBUG - on stmt: $202inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=current_sum.2, rhs=$200binary_subscr.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:43,083 - numba.core.ssa - DEBUG - on stmt: current_sum.1 = $202inplace_add.7\n", - "2024-10-16 10:10:43,083 - numba.core.ssa - DEBUG - on stmt: tof_indices[index] = current_sum.1\n", - "2024-10-16 10:10:43,084 - numba.core.ssa - DEBUG - find_def var='index' stmt=tof_indices[index] = current_sum.1\n", - "2024-10-16 10:10:43,084 - numba.core.ssa - DEBUG - find_def_from_top label 192\n", - "2024-10-16 10:10:43,085 - numba.core.ssa - DEBUG - idom 190 from label 192\n", - "2024-10-16 10:10:43,085 - numba.core.ssa - DEBUG - find_def_from_bottom label 190\n", - "2024-10-16 10:10:43,086 - numba.core.ssa - DEBUG - replaced with: tof_indices[index.2] = current_sum.1\n", - "2024-10-16 10:10:43,086 - numba.core.ssa - DEBUG - on stmt: $const216.12 = const(int, 1)\n", - "2024-10-16 10:10:43,087 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.13 = inplace_binop(fn=, immutable_fn=, lhs=index, rhs=$const216.12, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:43,087 - numba.core.ssa - DEBUG - find_def var='index' stmt=$218inplace_add.13 = inplace_binop(fn=, immutable_fn=, lhs=index, rhs=$const216.12, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:43,089 - numba.core.ssa - DEBUG - find_def_from_top label 192\n", - "2024-10-16 10:10:43,089 - numba.core.ssa - DEBUG - idom 190 from label 192\n", - "2024-10-16 10:10:43,090 - numba.core.ssa - DEBUG - find_def_from_bottom label 190\n", - "2024-10-16 10:10:43,090 - numba.core.ssa - DEBUG - replaced with: $218inplace_add.13 = inplace_binop(fn=, immutable_fn=, lhs=index.2, rhs=$const216.12, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:43,091 - numba.core.ssa - DEBUG - on stmt: index.1 = $218inplace_add.13\n", - "2024-10-16 10:10:43,091 - numba.core.ssa - DEBUG - on stmt: jump 190\n", - "2024-10-16 10:10:43,092 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 224\n", - "2024-10-16 10:10:43,092 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,093 - numba.core.ssa - DEBUG - on stmt: jump 174\n", - "2024-10-16 10:10:43,093 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 226\n", - "2024-10-16 10:10:43,094 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,094 - numba.core.ssa - DEBUG - on stmt: $const230.2 = const(int, 1)\n", - "2024-10-16 10:10:43,095 - numba.core.ssa - DEBUG - on stmt: $232binary_subtract.3 = tof_indices - $const230.2\n", - "2024-10-16 10:10:43,095 - numba.core.ssa - DEBUG - on stmt: $236build_tuple.5 = build_tuple(items=[Var(scan_indices, bruker.py:285), Var($232binary_subtract.3, bruker.py:298), Var(intensities, bruker.py:286)])\n", - "2024-10-16 10:10:43,096 - numba.core.ssa - DEBUG - on stmt: $238return_value.6 = cast(value=$236build_tuple.5)\n", - "2024-10-16 10:10:43,096 - numba.core.ssa - DEBUG - on stmt: return $238return_value.6\n", - "2024-10-16 10:10:43,116 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=5083)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=5084)\n", - " 4\tLOAD_FAST(arg=0, lineno=5084)\n", - " 6\tLOAD_FAST(arg=1, lineno=5084)\n", - " 8\tLOAD_DEREF(arg=0, lineno=5084)\n", - " 10\tCALL_FUNCTION(arg=3, lineno=5084)\n", - " 12\tRETURN_VALUE(arg=None, lineno=5084)\n", - "2024-10-16 10:10:43,117 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:43,118 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,118 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:43,119 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=5083)\n", - "2024-10-16 10:10:43,119 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,120 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=5084)\n", - "2024-10-16 10:10:43,120 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,121 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=5084)\n", - "2024-10-16 10:10:43,121 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:10:43,122 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=5084)\n", - "2024-10-16 10:10:43,122 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$buffer4.1']\n", - "2024-10-16 10:10:43,124 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_DEREF(arg=0, lineno=5084)\n", - "2024-10-16 10:10:43,124 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$buffer4.1', '$dtype6.2']\n", - "2024-10-16 10:10:43,125 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=CALL_FUNCTION(arg=3, lineno=5084)\n", - "2024-10-16 10:10:43,125 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$buffer4.1', '$dtype6.2', '$8load_deref.3']\n", - "2024-10-16 10:10:43,126 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=RETURN_VALUE(arg=None, lineno=5084)\n", - "2024-10-16 10:10:43,127 - numba.core.byteflow - DEBUG - stack ['$10call_function.4']\n", - "2024-10-16 10:10:43,127 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:43,128 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:43,128 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:10:43,129 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:10:43,130 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:10:43,130 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:10:43,131 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:10:43,132 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:10:43,132 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:43,133 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$buffer4.1'}), (6, {'res': '$dtype6.2'}), (8, {'res': '$8load_deref.3'}), (10, {'func': '$2load_global.0', 'args': ['$buffer4.1', '$dtype6.2', '$8load_deref.3'], 'res': '$10call_function.4'}), (12, {'retval': '$10call_function.4', 'castval': '$12return_value.5'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:43,134 - numba.core.interpreter - DEBUG - label 0:\n", - " buffer = arg(0, name=buffer) ['buffer']\n", - " dtype = arg(1, name=dtype) ['dtype']\n", - " $2load_global.0 = global(np_frombuffer: ) ['$2load_global.0']\n", - " $8load_deref.3 = freevar(retty: readonly array(uint8, 1d, C)) ['$8load_deref.3']\n", - " $10call_function.4 = call $2load_global.0(buffer, dtype, $8load_deref.3, func=$2load_global.0, args=[Var(buffer, arrayobj.py:5083), Var(dtype, arrayobj.py:5083), Var($8load_deref.3, arrayobj.py:5084)], kws=(), vararg=None, varkwarg=None, target=None) ['$10call_function.4', '$2load_global.0', '$8load_deref.3', 'buffer', 'dtype']\n", - " $12return_value.5 = cast(value=$10call_function.4) ['$10call_function.4', '$12return_value.5']\n", - " return $12return_value.5 ['$12return_value.5']\n", - "\n", - "2024-10-16 10:10:43,148 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:43,149 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,150 - numba.core.ssa - DEBUG - on stmt: buffer = arg(0, name=buffer)\n", - "2024-10-16 10:10:43,150 - numba.core.ssa - DEBUG - on stmt: dtype = arg(1, name=dtype)\n", - "2024-10-16 10:10:43,151 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np_frombuffer: )\n", - "2024-10-16 10:10:43,152 - numba.core.ssa - DEBUG - on stmt: $8load_deref.3 = freevar(retty: readonly array(uint8, 1d, C))\n", - "2024-10-16 10:10:43,152 - numba.core.ssa - DEBUG - on stmt: $10call_function.4 = call $2load_global.0(buffer, dtype, $8load_deref.3, func=$2load_global.0, args=[Var(buffer, arrayobj.py:5083), Var(dtype, arrayobj.py:5083), Var($8load_deref.3, arrayobj.py:5084)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,153 - numba.core.ssa - DEBUG - on stmt: $12return_value.5 = cast(value=$10call_function.4)\n", - "2024-10-16 10:10:43,153 - numba.core.ssa - DEBUG - on stmt: return $12return_value.5\n", - "2024-10-16 10:10:43,154 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10call_function.4': [],\n", - " '$12return_value.5': [],\n", - " '$2load_global.0': [],\n", - " '$8load_deref.3': [],\n", - " 'buffer': [],\n", - " 'dtype': []})\n", - "2024-10-16 10:10:43,155 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:10:43,318 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=5083)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=5084)\n", - " 4\tLOAD_FAST(arg=0, lineno=5084)\n", - " 6\tLOAD_FAST(arg=1, lineno=5084)\n", - " 8\tLOAD_DEREF(arg=0, lineno=5084)\n", - " 10\tCALL_FUNCTION(arg=3, lineno=5084)\n", - " 12\tRETURN_VALUE(arg=None, lineno=5084)\n", - "2024-10-16 10:10:43,319 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:43,320 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,320 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:43,321 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=5083)\n", - "2024-10-16 10:10:43,322 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,322 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=5084)\n", - "2024-10-16 10:10:43,323 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,324 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=5084)\n", - "2024-10-16 10:10:43,325 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:10:43,325 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=5084)\n", - "2024-10-16 10:10:43,326 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$buffer4.1']\n", - "2024-10-16 10:10:43,327 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_DEREF(arg=0, lineno=5084)\n", - "2024-10-16 10:10:43,327 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$buffer4.1', '$dtype6.2']\n", - "2024-10-16 10:10:43,328 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=CALL_FUNCTION(arg=3, lineno=5084)\n", - "2024-10-16 10:10:43,329 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$buffer4.1', '$dtype6.2', '$8load_deref.3']\n", - "2024-10-16 10:10:43,330 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=RETURN_VALUE(arg=None, lineno=5084)\n", - "2024-10-16 10:10:43,330 - numba.core.byteflow - DEBUG - stack ['$10call_function.4']\n", - "2024-10-16 10:10:43,331 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:43,332 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:43,333 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:10:43,333 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:10:43,334 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:10:43,335 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:10:43,335 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:10:43,336 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:10:43,337 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:43,338 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$buffer4.1'}), (6, {'res': '$dtype6.2'}), (8, {'res': '$8load_deref.3'}), (10, {'func': '$2load_global.0', 'args': ['$buffer4.1', '$dtype6.2', '$8load_deref.3'], 'res': '$10call_function.4'}), (12, {'retval': '$10call_function.4', 'castval': '$12return_value.5'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:43,339 - numba.core.interpreter - DEBUG - label 0:\n", - " buffer = arg(0, name=buffer) ['buffer']\n", - " dtype = arg(1, name=dtype) ['dtype']\n", - " $2load_global.0 = global(np_frombuffer: ) ['$2load_global.0']\n", - " $8load_deref.3 = freevar(retty: array(uint32, 1d, C)) ['$8load_deref.3']\n", - " $10call_function.4 = call $2load_global.0(buffer, dtype, $8load_deref.3, func=$2load_global.0, args=[Var(buffer, arrayobj.py:5083), Var(dtype, arrayobj.py:5083), Var($8load_deref.3, arrayobj.py:5084)], kws=(), vararg=None, varkwarg=None, target=None) ['$10call_function.4', '$2load_global.0', '$8load_deref.3', 'buffer', 'dtype']\n", - " $12return_value.5 = cast(value=$10call_function.4) ['$10call_function.4', '$12return_value.5']\n", - " return $12return_value.5 ['$12return_value.5']\n", - "\n", - "2024-10-16 10:10:43,349 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:43,350 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,351 - numba.core.ssa - DEBUG - on stmt: buffer = arg(0, name=buffer)\n", - "2024-10-16 10:10:43,352 - numba.core.ssa - DEBUG - on stmt: dtype = arg(1, name=dtype)\n", - "2024-10-16 10:10:43,352 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np_frombuffer: )\n", - "2024-10-16 10:10:43,353 - numba.core.ssa - DEBUG - on stmt: $8load_deref.3 = freevar(retty: array(uint32, 1d, C))\n", - "2024-10-16 10:10:43,354 - numba.core.ssa - DEBUG - on stmt: $10call_function.4 = call $2load_global.0(buffer, dtype, $8load_deref.3, func=$2load_global.0, args=[Var(buffer, arrayobj.py:5083), Var(dtype, arrayobj.py:5083), Var($8load_deref.3, arrayobj.py:5084)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,354 - numba.core.ssa - DEBUG - on stmt: $12return_value.5 = cast(value=$10call_function.4)\n", - "2024-10-16 10:10:43,355 - numba.core.ssa - DEBUG - on stmt: return $12return_value.5\n", - "2024-10-16 10:10:43,356 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10call_function.4': [],\n", - " '$12return_value.5': [],\n", - " '$2load_global.0': [],\n", - " '$8load_deref.3': [],\n", - " 'buffer': [],\n", - " 'dtype': []})\n", - "2024-10-16 10:10:43,357 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:10:43,515 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=2044)\n", - " 2\tLOAD_CONST(arg=1, lineno=2045)\n", - " 4\tSTORE_FAST(arg=2, lineno=2045)\n", - " 6\tLOAD_CONST(arg=2, lineno=2046)\n", - " 8\tSTORE_FAST(arg=3, lineno=2046)\n", - " 10\tLOAD_GLOBAL(arg=0, lineno=2047)\n", - " 12\tLOAD_FAST(arg=1, lineno=2047)\n", - " 14\tCALL_FUNCTION(arg=1, lineno=2047)\n", - " 16\tGET_ITER(arg=None, lineno=2047)\n", - "> 18\tFOR_ITER(arg=19, lineno=2047)\n", - " 20\tUNPACK_SEQUENCE(arg=2, lineno=2047)\n", - " 22\tSTORE_FAST(arg=4, lineno=2047)\n", - " 24\tSTORE_FAST(arg=5, lineno=2047)\n", - " 26\tLOAD_FAST(arg=5, lineno=2048)\n", - " 28\tLOAD_CONST(arg=1, lineno=2048)\n", - " 30\tCOMPARE_OP(arg=0, lineno=2048)\n", - " 32\tPOP_JUMP_IF_FALSE(arg=25, lineno=2048)\n", - " 34\tLOAD_FAST(arg=2, lineno=2049)\n", - " 36\tLOAD_CONST(arg=2, lineno=2049)\n", - " 38\tINPLACE_ADD(arg=None, lineno=2049)\n", - " 40\tSTORE_FAST(arg=2, lineno=2049)\n", - " 42\tLOAD_FAST(arg=4, lineno=2050)\n", - " 44\tSTORE_FAST(arg=6, lineno=2050)\n", - " 46\tJUMP_ABSOLUTE(arg=10, lineno=2050)\n", - "> 48\tLOAD_FAST(arg=3, lineno=2052)\n", - " 50\tLOAD_FAST(arg=5, lineno=2052)\n", - " 52\tINPLACE_MULTIPLY(arg=None, lineno=2052)\n", - " 54\tSTORE_FAST(arg=3, lineno=2052)\n", - " 56\tJUMP_ABSOLUTE(arg=10, lineno=2052)\n", - "> 58\tLOAD_FAST(arg=2, lineno=2054)\n", - " 60\tLOAD_CONST(arg=1, lineno=2054)\n", - " 62\tCOMPARE_OP(arg=2, lineno=2054)\n", - " 64\tPOP_JUMP_IF_FALSE(arg=44, lineno=2054)\n", - " 66\tLOAD_FAST(arg=0, lineno=2055)\n", - " 68\tLOAD_FAST(arg=3, lineno=2055)\n", - " 70\tCOMPARE_OP(arg=3, lineno=2055)\n", - " 72\tPOP_JUMP_IF_FALSE(arg=42, lineno=2055)\n", - " 74\tLOAD_GLOBAL(arg=1, lineno=2056)\n", - " 76\tLOAD_CONST(arg=3, lineno=2056)\n", - " 78\tCALL_FUNCTION(arg=1, lineno=2056)\n", - " 80\tRAISE_VARARGS(arg=1, lineno=2056)\n", - "> 82\tLOAD_CONST(arg=0, lineno=2055)\n", - " 84\tRETURN_VALUE(arg=None, lineno=2055)\n", - "> 86\tLOAD_FAST(arg=2, lineno=2058)\n", - " 88\tLOAD_CONST(arg=2, lineno=2058)\n", - " 90\tCOMPARE_OP(arg=2, lineno=2058)\n", - " 92\tPOP_JUMP_IF_FALSE(arg=81, lineno=2058)\n", - " 94\tLOAD_FAST(arg=3, lineno=2060)\n", - " 96\tLOAD_CONST(arg=1, lineno=2060)\n", - " 98\tCOMPARE_OP(arg=2, lineno=2060)\n", - " 100\tPOP_JUMP_IF_FALSE(arg=59, lineno=2060)\n", - " 102\tLOAD_CONST(arg=1, lineno=2061)\n", - " 104\tSTORE_FAST(arg=7, lineno=2061)\n", - " 106\tLOAD_FAST(arg=0, lineno=2062)\n", - " 108\tLOAD_CONST(arg=1, lineno=2062)\n", - " 110\tCOMPARE_OP(arg=2, lineno=2062)\n", - " 112\tSTORE_FAST(arg=8, lineno=2062)\n", - " 114\tJUMP_FORWARD(arg=10, lineno=2062)\n", - "> 116\tLOAD_FAST(arg=0, lineno=2064)\n", - " 118\tLOAD_FAST(arg=3, lineno=2064)\n", - " 120\tBINARY_FLOOR_DIVIDE(arg=None, lineno=2064)\n", - " 122\tSTORE_FAST(arg=7, lineno=2064)\n", - " 124\tLOAD_FAST(arg=0, lineno=2065)\n", - " 126\tLOAD_FAST(arg=3, lineno=2065)\n", - " 128\tBINARY_MODULO(arg=None, lineno=2065)\n", - " 130\tLOAD_CONST(arg=1, lineno=2065)\n", - " 132\tCOMPARE_OP(arg=2, lineno=2065)\n", - " 134\tSTORE_FAST(arg=8, lineno=2065)\n", - "> 136\tLOAD_FAST(arg=8, lineno=2066)\n", - " 138\tPOP_JUMP_IF_TRUE(arg=75, lineno=2066)\n", - " 140\tLOAD_GLOBAL(arg=1, lineno=2067)\n", - " 142\tLOAD_CONST(arg=3, lineno=2067)\n", - " 144\tCALL_FUNCTION(arg=1, lineno=2067)\n", - " 146\tRAISE_VARARGS(arg=1, lineno=2067)\n", - "> 148\tLOAD_FAST(arg=7, lineno=2068)\n", - " 150\tLOAD_FAST(arg=1, lineno=2068)\n", - " 152\tLOAD_FAST(arg=6, lineno=2068)\n", - " 154\tSTORE_SUBSCR(arg=None, lineno=2068)\n", - " 156\tLOAD_CONST(arg=0, lineno=2068)\n", - " 158\tRETURN_VALUE(arg=None, lineno=2068)\n", - "> 160\tLOAD_GLOBAL(arg=1, lineno=2071)\n", - " 162\tLOAD_CONST(arg=4, lineno=2071)\n", - " 164\tCALL_FUNCTION(arg=1, lineno=2071)\n", - " 166\tRAISE_VARARGS(arg=1, lineno=2071)\n", - "2024-10-16 10:10:43,516 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:43,517 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,517 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:43,518 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=2044)\n", - "2024-10-16 10:10:43,519 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,519 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_CONST(arg=1, lineno=2045)\n", - "2024-10-16 10:10:43,520 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,521 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=STORE_FAST(arg=2, lineno=2045)\n", - "2024-10-16 10:10:43,521 - numba.core.byteflow - DEBUG - stack ['$const2.0']\n", - "2024-10-16 10:10:43,522 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_CONST(arg=2, lineno=2046)\n", - "2024-10-16 10:10:43,523 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,523 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=3, lineno=2046)\n", - "2024-10-16 10:10:43,524 - numba.core.byteflow - DEBUG - stack ['$const6.1']\n", - "2024-10-16 10:10:43,525 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=0, lineno=2047)\n", - "2024-10-16 10:10:43,525 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,526 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=1, lineno=2047)\n", - "2024-10-16 10:10:43,527 - numba.core.byteflow - DEBUG - stack ['$10load_global.2']\n", - "2024-10-16 10:10:43,527 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=CALL_FUNCTION(arg=1, lineno=2047)\n", - "2024-10-16 10:10:43,528 - numba.core.byteflow - DEBUG - stack ['$10load_global.2', '$shape12.3']\n", - "2024-10-16 10:10:43,529 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=GET_ITER(arg=None, lineno=2047)\n", - "2024-10-16 10:10:43,529 - numba.core.byteflow - DEBUG - stack ['$14call_function.4']\n", - "2024-10-16 10:10:43,530 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=18, stack=('$16get_iter.5',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,531 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=18 nstack_initial=1)])\n", - "2024-10-16 10:10:43,531 - numba.core.byteflow - DEBUG - stack: ['$phi18.0']\n", - "2024-10-16 10:10:43,532 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=18 nstack_initial=1)\n", - "2024-10-16 10:10:43,533 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=FOR_ITER(arg=19, lineno=2047)\n", - "2024-10-16 10:10:43,533 - numba.core.byteflow - DEBUG - stack ['$phi18.0']\n", - "2024-10-16 10:10:43,534 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=58, stack=(), blockstack=(), npush=0), Edge(pc=20, stack=('$phi18.0', '$18for_iter.2'), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,535 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=58 nstack_initial=0), State(pc_initial=20 nstack_initial=2)])\n", - "2024-10-16 10:10:43,535 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,536 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=58 nstack_initial=0)\n", - "2024-10-16 10:10:43,537 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_FAST(arg=2, lineno=2054)\n", - "2024-10-16 10:10:43,537 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,538 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_CONST(arg=1, lineno=2054)\n", - "2024-10-16 10:10:43,539 - numba.core.byteflow - DEBUG - stack ['$num_neg_value58.0']\n", - "2024-10-16 10:10:43,539 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=COMPARE_OP(arg=2, lineno=2054)\n", - "2024-10-16 10:10:43,540 - numba.core.byteflow - DEBUG - stack ['$num_neg_value58.0', '$const60.1']\n", - "2024-10-16 10:10:43,541 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=POP_JUMP_IF_FALSE(arg=44, lineno=2054)\n", - "2024-10-16 10:10:43,542 - numba.core.byteflow - DEBUG - stack ['$62compare_op.2']\n", - "2024-10-16 10:10:43,542 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=66, stack=(), blockstack=(), npush=0), Edge(pc=86, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,543 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=20 nstack_initial=2), State(pc_initial=66 nstack_initial=0), State(pc_initial=86 nstack_initial=0)])\n", - "2024-10-16 10:10:43,544 - numba.core.byteflow - DEBUG - stack: ['$phi20.0', '$phi20.1']\n", - "2024-10-16 10:10:43,545 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=20 nstack_initial=2)\n", - "2024-10-16 10:10:43,545 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=UNPACK_SEQUENCE(arg=2, lineno=2047)\n", - "2024-10-16 10:10:43,546 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$phi20.1']\n", - "2024-10-16 10:10:43,547 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=STORE_FAST(arg=4, lineno=2047)\n", - "2024-10-16 10:10:43,548 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$20unpack_sequence.3', '$20unpack_sequence.2']\n", - "2024-10-16 10:10:43,548 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=STORE_FAST(arg=5, lineno=2047)\n", - "2024-10-16 10:10:43,549 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$20unpack_sequence.3']\n", - "2024-10-16 10:10:43,550 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_FAST(arg=5, lineno=2048)\n", - "2024-10-16 10:10:43,550 - numba.core.byteflow - DEBUG - stack ['$phi20.0']\n", - "2024-10-16 10:10:43,551 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_CONST(arg=1, lineno=2048)\n", - "2024-10-16 10:10:43,552 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$s26.5']\n", - "2024-10-16 10:10:43,553 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=COMPARE_OP(arg=0, lineno=2048)\n", - "2024-10-16 10:10:43,553 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$s26.5', '$const28.6']\n", - "2024-10-16 10:10:43,554 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=POP_JUMP_IF_FALSE(arg=25, lineno=2048)\n", - "2024-10-16 10:10:43,555 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$30compare_op.7']\n", - "2024-10-16 10:10:43,555 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=34, stack=('$phi20.0',), blockstack=(), npush=0), Edge(pc=48, stack=('$phi20.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,556 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=66 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=34 nstack_initial=1), State(pc_initial=48 nstack_initial=1)])\n", - "2024-10-16 10:10:43,557 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,558 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=66 nstack_initial=0)\n", - "2024-10-16 10:10:43,558 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_FAST(arg=0, lineno=2055)\n", - "2024-10-16 10:10:43,559 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,560 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_FAST(arg=3, lineno=2055)\n", - "2024-10-16 10:10:43,561 - numba.core.byteflow - DEBUG - stack ['$origsize66.0']\n", - "2024-10-16 10:10:43,561 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=COMPARE_OP(arg=3, lineno=2055)\n", - "2024-10-16 10:10:43,562 - numba.core.byteflow - DEBUG - stack ['$origsize66.0', '$known_size68.1']\n", - "2024-10-16 10:10:43,563 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=POP_JUMP_IF_FALSE(arg=42, lineno=2055)\n", - "2024-10-16 10:10:43,564 - numba.core.byteflow - DEBUG - stack ['$70compare_op.2']\n", - "2024-10-16 10:10:43,565 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=74, stack=(), blockstack=(), npush=0), Edge(pc=82, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,565 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=0), State(pc_initial=34 nstack_initial=1), State(pc_initial=48 nstack_initial=1), State(pc_initial=74 nstack_initial=0), State(pc_initial=82 nstack_initial=0)])\n", - "2024-10-16 10:10:43,566 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,567 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=86 nstack_initial=0)\n", - "2024-10-16 10:10:43,568 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=2, lineno=2058)\n", - "2024-10-16 10:10:43,568 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,569 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_CONST(arg=2, lineno=2058)\n", - "2024-10-16 10:10:43,570 - numba.core.byteflow - DEBUG - stack ['$num_neg_value86.0']\n", - "2024-10-16 10:10:43,571 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=COMPARE_OP(arg=2, lineno=2058)\n", - "2024-10-16 10:10:43,572 - numba.core.byteflow - DEBUG - stack ['$num_neg_value86.0', '$const88.1']\n", - "2024-10-16 10:10:43,582 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=POP_JUMP_IF_FALSE(arg=81, lineno=2058)\n", - "2024-10-16 10:10:43,582 - numba.core.byteflow - DEBUG - stack ['$90compare_op.2']\n", - "2024-10-16 10:10:43,583 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=94, stack=(), blockstack=(), npush=0), Edge(pc=160, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,584 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=34 nstack_initial=1), State(pc_initial=48 nstack_initial=1), State(pc_initial=74 nstack_initial=0), State(pc_initial=82 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=160 nstack_initial=0)])\n", - "2024-10-16 10:10:43,585 - numba.core.byteflow - DEBUG - stack: ['$phi34.0']\n", - "2024-10-16 10:10:43,585 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=34 nstack_initial=1)\n", - "2024-10-16 10:10:43,586 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=2, lineno=2049)\n", - "2024-10-16 10:10:43,587 - numba.core.byteflow - DEBUG - stack ['$phi34.0']\n", - "2024-10-16 10:10:43,588 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_CONST(arg=2, lineno=2049)\n", - "2024-10-16 10:10:43,589 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$num_neg_value34.1']\n", - "2024-10-16 10:10:43,590 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=INPLACE_ADD(arg=None, lineno=2049)\n", - "2024-10-16 10:10:43,601 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$num_neg_value34.1', '$const36.2']\n", - "2024-10-16 10:10:43,602 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=STORE_FAST(arg=2, lineno=2049)\n", - "2024-10-16 10:10:43,603 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$38inplace_add.3']\n", - "2024-10-16 10:10:43,604 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_FAST(arg=4, lineno=2050)\n", - "2024-10-16 10:10:43,604 - numba.core.byteflow - DEBUG - stack ['$phi34.0']\n", - "2024-10-16 10:10:43,605 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=STORE_FAST(arg=6, lineno=2050)\n", - "2024-10-16 10:10:43,606 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$ax42.4']\n", - "2024-10-16 10:10:43,607 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=JUMP_ABSOLUTE(arg=10, lineno=2050)\n", - "2024-10-16 10:10:43,607 - numba.core.byteflow - DEBUG - stack ['$phi34.0']\n", - "2024-10-16 10:10:43,608 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=18, stack=('$phi34.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,609 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=48 nstack_initial=1), State(pc_initial=74 nstack_initial=0), State(pc_initial=82 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=160 nstack_initial=0), State(pc_initial=18 nstack_initial=1)])\n", - "2024-10-16 10:10:43,610 - numba.core.byteflow - DEBUG - stack: ['$phi48.0']\n", - "2024-10-16 10:10:43,610 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=48 nstack_initial=1)\n", - "2024-10-16 10:10:43,611 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_FAST(arg=3, lineno=2052)\n", - "2024-10-16 10:10:43,614 - numba.core.byteflow - DEBUG - stack ['$phi48.0']\n", - "2024-10-16 10:10:43,615 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_FAST(arg=5, lineno=2052)\n", - "2024-10-16 10:10:43,615 - numba.core.byteflow - DEBUG - stack ['$phi48.0', '$known_size48.1']\n", - "2024-10-16 10:10:43,616 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=INPLACE_MULTIPLY(arg=None, lineno=2052)\n", - "2024-10-16 10:10:43,617 - numba.core.byteflow - DEBUG - stack ['$phi48.0', '$known_size48.1', '$s50.2']\n", - "2024-10-16 10:10:43,618 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=STORE_FAST(arg=3, lineno=2052)\n", - "2024-10-16 10:10:43,618 - numba.core.byteflow - DEBUG - stack ['$phi48.0', '$52inplace_multiply.3']\n", - "2024-10-16 10:10:43,619 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=JUMP_ABSOLUTE(arg=10, lineno=2052)\n", - "2024-10-16 10:10:43,620 - numba.core.byteflow - DEBUG - stack ['$phi48.0']\n", - "2024-10-16 10:10:43,620 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=18, stack=('$phi48.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,621 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=0), State(pc_initial=82 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=160 nstack_initial=0), State(pc_initial=18 nstack_initial=1), State(pc_initial=18 nstack_initial=1)])\n", - "2024-10-16 10:10:43,622 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,625 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=0)\n", - "2024-10-16 10:10:43,625 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_GLOBAL(arg=1, lineno=2056)\n", - "2024-10-16 10:10:43,626 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,627 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=LOAD_CONST(arg=3, lineno=2056)\n", - "2024-10-16 10:10:43,627 - numba.core.byteflow - DEBUG - stack ['$74load_global.0']\n", - "2024-10-16 10:10:43,628 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=CALL_FUNCTION(arg=1, lineno=2056)\n", - "2024-10-16 10:10:43,629 - numba.core.byteflow - DEBUG - stack ['$74load_global.0', '$const76.1']\n", - "2024-10-16 10:10:43,630 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=RAISE_VARARGS(arg=1, lineno=2056)\n", - "2024-10-16 10:10:43,630 - numba.core.byteflow - DEBUG - stack ['$78call_function.2']\n", - "2024-10-16 10:10:43,631 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:43,632 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=82 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=160 nstack_initial=0), State(pc_initial=18 nstack_initial=1), State(pc_initial=18 nstack_initial=1)])\n", - "2024-10-16 10:10:43,633 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,633 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=82 nstack_initial=0)\n", - "2024-10-16 10:10:43,634 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=LOAD_CONST(arg=0, lineno=2055)\n", - "2024-10-16 10:10:43,635 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,635 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=RETURN_VALUE(arg=None, lineno=2055)\n", - "2024-10-16 10:10:43,639 - numba.core.byteflow - DEBUG - stack ['$const82.0']\n", - "2024-10-16 10:10:43,639 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:43,640 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=94 nstack_initial=0), State(pc_initial=160 nstack_initial=0), State(pc_initial=18 nstack_initial=1), State(pc_initial=18 nstack_initial=1)])\n", - "2024-10-16 10:10:43,641 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,641 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=94 nstack_initial=0)\n", - "2024-10-16 10:10:43,642 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_FAST(arg=3, lineno=2060)\n", - "2024-10-16 10:10:43,643 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,644 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=LOAD_CONST(arg=1, lineno=2060)\n", - "2024-10-16 10:10:43,644 - numba.core.byteflow - DEBUG - stack ['$known_size94.0']\n", - "2024-10-16 10:10:43,645 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=COMPARE_OP(arg=2, lineno=2060)\n", - "2024-10-16 10:10:43,646 - numba.core.byteflow - DEBUG - stack ['$known_size94.0', '$const96.1']\n", - "2024-10-16 10:10:43,646 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=POP_JUMP_IF_FALSE(arg=59, lineno=2060)\n", - "2024-10-16 10:10:43,647 - numba.core.byteflow - DEBUG - stack ['$98compare_op.2']\n", - "2024-10-16 10:10:43,648 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=102, stack=(), blockstack=(), npush=0), Edge(pc=116, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,648 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=160 nstack_initial=0), State(pc_initial=18 nstack_initial=1), State(pc_initial=18 nstack_initial=1), State(pc_initial=102 nstack_initial=0), State(pc_initial=116 nstack_initial=0)])\n", - "2024-10-16 10:10:43,649 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,650 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=160 nstack_initial=0)\n", - "2024-10-16 10:10:43,651 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=LOAD_GLOBAL(arg=1, lineno=2071)\n", - "2024-10-16 10:10:43,651 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,652 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=LOAD_CONST(arg=4, lineno=2071)\n", - "2024-10-16 10:10:43,653 - numba.core.byteflow - DEBUG - stack ['$160load_global.0']\n", - "2024-10-16 10:10:43,653 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=CALL_FUNCTION(arg=1, lineno=2071)\n", - "2024-10-16 10:10:43,654 - numba.core.byteflow - DEBUG - stack ['$160load_global.0', '$const162.1']\n", - "2024-10-16 10:10:43,655 - numba.core.byteflow - DEBUG - dispatch pc=166, inst=RAISE_VARARGS(arg=1, lineno=2071)\n", - "2024-10-16 10:10:43,655 - numba.core.byteflow - DEBUG - stack ['$164call_function.2']\n", - "2024-10-16 10:10:43,656 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:43,657 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=18 nstack_initial=1), State(pc_initial=18 nstack_initial=1), State(pc_initial=102 nstack_initial=0), State(pc_initial=116 nstack_initial=0)])\n", - "2024-10-16 10:10:43,657 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=18 nstack_initial=1), State(pc_initial=102 nstack_initial=0), State(pc_initial=116 nstack_initial=0)])\n", - "2024-10-16 10:10:43,658 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=102 nstack_initial=0), State(pc_initial=116 nstack_initial=0)])\n", - "2024-10-16 10:10:43,659 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,660 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=102 nstack_initial=0)\n", - "2024-10-16 10:10:43,660 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=LOAD_CONST(arg=1, lineno=2061)\n", - "2024-10-16 10:10:43,661 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,662 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=STORE_FAST(arg=7, lineno=2061)\n", - "2024-10-16 10:10:43,662 - numba.core.byteflow - DEBUG - stack ['$const102.0']\n", - "2024-10-16 10:10:43,663 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_FAST(arg=0, lineno=2062)\n", - "2024-10-16 10:10:43,664 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,664 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_CONST(arg=1, lineno=2062)\n", - "2024-10-16 10:10:43,665 - numba.core.byteflow - DEBUG - stack ['$origsize106.1']\n", - "2024-10-16 10:10:43,666 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=COMPARE_OP(arg=2, lineno=2062)\n", - "2024-10-16 10:10:43,666 - numba.core.byteflow - DEBUG - stack ['$origsize106.1', '$const108.2']\n", - "2024-10-16 10:10:43,667 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=STORE_FAST(arg=8, lineno=2062)\n", - "2024-10-16 10:10:43,668 - numba.core.byteflow - DEBUG - stack ['$110compare_op.3']\n", - "2024-10-16 10:10:43,669 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=JUMP_FORWARD(arg=10, lineno=2062)\n", - "2024-10-16 10:10:43,669 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,670 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=136, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,671 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=116 nstack_initial=0), State(pc_initial=136 nstack_initial=0)])\n", - "2024-10-16 10:10:43,671 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,672 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=116 nstack_initial=0)\n", - "2024-10-16 10:10:43,673 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=LOAD_FAST(arg=0, lineno=2064)\n", - "2024-10-16 10:10:43,673 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,674 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_FAST(arg=3, lineno=2064)\n", - "2024-10-16 10:10:43,675 - numba.core.byteflow - DEBUG - stack ['$origsize116.0']\n", - "2024-10-16 10:10:43,675 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=BINARY_FLOOR_DIVIDE(arg=None, lineno=2064)\n", - "2024-10-16 10:10:43,676 - numba.core.byteflow - DEBUG - stack ['$origsize116.0', '$known_size118.1']\n", - "2024-10-16 10:10:43,677 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=STORE_FAST(arg=7, lineno=2064)\n", - "2024-10-16 10:10:43,678 - numba.core.byteflow - DEBUG - stack ['$120binary_floor_divide.2']\n", - "2024-10-16 10:10:43,678 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=LOAD_FAST(arg=0, lineno=2065)\n", - "2024-10-16 10:10:43,679 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,680 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_FAST(arg=3, lineno=2065)\n", - "2024-10-16 10:10:43,680 - numba.core.byteflow - DEBUG - stack ['$origsize124.3']\n", - "2024-10-16 10:10:43,681 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=BINARY_MODULO(arg=None, lineno=2065)\n", - "2024-10-16 10:10:43,682 - numba.core.byteflow - DEBUG - stack ['$origsize124.3', '$known_size126.4']\n", - "2024-10-16 10:10:43,683 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=LOAD_CONST(arg=1, lineno=2065)\n", - "2024-10-16 10:10:43,683 - numba.core.byteflow - DEBUG - stack ['$128binary_modulo.5']\n", - "2024-10-16 10:10:43,684 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=COMPARE_OP(arg=2, lineno=2065)\n", - "2024-10-16 10:10:43,684 - numba.core.byteflow - DEBUG - stack ['$128binary_modulo.5', '$const130.6']\n", - "2024-10-16 10:10:43,685 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=STORE_FAST(arg=8, lineno=2065)\n", - "2024-10-16 10:10:43,686 - numba.core.byteflow - DEBUG - stack ['$132compare_op.7']\n", - "2024-10-16 10:10:43,686 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=136, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,687 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=136 nstack_initial=0), State(pc_initial=136 nstack_initial=0)])\n", - "2024-10-16 10:10:43,688 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,688 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=136 nstack_initial=0)\n", - "2024-10-16 10:10:43,689 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=LOAD_FAST(arg=8, lineno=2066)\n", - "2024-10-16 10:10:43,690 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,690 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=POP_JUMP_IF_TRUE(arg=75, lineno=2066)\n", - "2024-10-16 10:10:43,691 - numba.core.byteflow - DEBUG - stack ['$ok136.0']\n", - "2024-10-16 10:10:43,692 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=140, stack=(), blockstack=(), npush=0), Edge(pc=148, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:43,692 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=136 nstack_initial=0), State(pc_initial=140 nstack_initial=0), State(pc_initial=148 nstack_initial=0)])\n", - "2024-10-16 10:10:43,693 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=140 nstack_initial=0), State(pc_initial=148 nstack_initial=0)])\n", - "2024-10-16 10:10:43,694 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,694 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=140 nstack_initial=0)\n", - "2024-10-16 10:10:43,695 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=LOAD_GLOBAL(arg=1, lineno=2067)\n", - "2024-10-16 10:10:43,696 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,696 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_CONST(arg=3, lineno=2067)\n", - "2024-10-16 10:10:43,697 - numba.core.byteflow - DEBUG - stack ['$140load_global.0']\n", - "2024-10-16 10:10:43,698 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=CALL_FUNCTION(arg=1, lineno=2067)\n", - "2024-10-16 10:10:43,698 - numba.core.byteflow - DEBUG - stack ['$140load_global.0', '$const142.1']\n", - "2024-10-16 10:10:43,699 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=RAISE_VARARGS(arg=1, lineno=2067)\n", - "2024-10-16 10:10:43,700 - numba.core.byteflow - DEBUG - stack ['$144call_function.2']\n", - "2024-10-16 10:10:43,700 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:43,701 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=148 nstack_initial=0)])\n", - "2024-10-16 10:10:43,702 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:43,702 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=148 nstack_initial=0)\n", - "2024-10-16 10:10:43,715 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=7, lineno=2068)\n", - "2024-10-16 10:10:43,716 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,716 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=LOAD_FAST(arg=1, lineno=2068)\n", - "2024-10-16 10:10:43,717 - numba.core.byteflow - DEBUG - stack ['$inferred148.0']\n", - "2024-10-16 10:10:43,718 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=LOAD_FAST(arg=6, lineno=2068)\n", - "2024-10-16 10:10:43,718 - numba.core.byteflow - DEBUG - stack ['$inferred148.0', '$shape150.1']\n", - "2024-10-16 10:10:43,719 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=STORE_SUBSCR(arg=None, lineno=2068)\n", - "2024-10-16 10:10:43,719 - numba.core.byteflow - DEBUG - stack ['$inferred148.0', '$shape150.1', '$neg_ax152.2']\n", - "2024-10-16 10:10:43,720 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=LOAD_CONST(arg=0, lineno=2068)\n", - "2024-10-16 10:10:43,721 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:43,721 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=RETURN_VALUE(arg=None, lineno=2068)\n", - "2024-10-16 10:10:43,722 - numba.core.byteflow - DEBUG - stack ['$const156.3']\n", - "2024-10-16 10:10:43,722 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:43,723 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:43,724 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=18 nstack_initial=1): {'$phi18.0'},\n", - " State(pc_initial=20 nstack_initial=2): {'$phi20.1'},\n", - " State(pc_initial=34 nstack_initial=1): set(),\n", - " State(pc_initial=48 nstack_initial=1): set(),\n", - " State(pc_initial=58 nstack_initial=0): set(),\n", - " State(pc_initial=66 nstack_initial=0): set(),\n", - " State(pc_initial=74 nstack_initial=0): set(),\n", - " State(pc_initial=82 nstack_initial=0): set(),\n", - " State(pc_initial=86 nstack_initial=0): set(),\n", - " State(pc_initial=94 nstack_initial=0): set(),\n", - " State(pc_initial=102 nstack_initial=0): set(),\n", - " State(pc_initial=116 nstack_initial=0): set(),\n", - " State(pc_initial=136 nstack_initial=0): set(),\n", - " State(pc_initial=140 nstack_initial=0): set(),\n", - " State(pc_initial=148 nstack_initial=0): set(),\n", - " State(pc_initial=160 nstack_initial=0): set()})\n", - "2024-10-16 10:10:43,725 - numba.core.byteflow - DEBUG - defmap: {'$phi18.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi20.1': State(pc_initial=18 nstack_initial=1)}\n", - "2024-10-16 10:10:43,725 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi18.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=1)),\n", - " ('$phi48.0', State(pc_initial=48 nstack_initial=1))},\n", - " '$phi20.0': {('$phi18.0', State(pc_initial=18 nstack_initial=1))},\n", - " '$phi20.1': {('$18for_iter.2',\n", - " State(pc_initial=18 nstack_initial=1))},\n", - " '$phi34.0': {('$phi20.0', State(pc_initial=20 nstack_initial=2))},\n", - " '$phi48.0': {('$phi20.0', State(pc_initial=20 nstack_initial=2))}})\n", - "2024-10-16 10:10:43,726 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi18.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi20.0', State(pc_initial=20 nstack_initial=2))},\n", - " '$phi20.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi20.0', State(pc_initial=20 nstack_initial=2))},\n", - " '$phi20.1': {('$18for_iter.2',\n", - " State(pc_initial=18 nstack_initial=1))},\n", - " '$phi34.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi48.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))}})\n", - "2024-10-16 10:10:43,727 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi18.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.1': {('$18for_iter.2',\n", - " State(pc_initial=18 nstack_initial=1))},\n", - " '$phi34.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi48.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))}})\n", - "2024-10-16 10:10:43,728 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi18.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.1': {('$18for_iter.2',\n", - " State(pc_initial=18 nstack_initial=1))},\n", - " '$phi34.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi48.0': {('$16get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))}})\n", - "2024-10-16 10:10:43,729 - numba.core.byteflow - DEBUG - keep phismap: {'$phi18.0': {('$16get_iter.5', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.1': {('$18for_iter.2', State(pc_initial=18 nstack_initial=1))}}\n", - "2024-10-16 10:10:43,730 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi18.0': '$16get_iter.5'},\n", - " State(pc_initial=18 nstack_initial=1): {'$phi20.1': '$18for_iter.2'}})\n", - "2024-10-16 10:10:43,731 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:43,731 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$const2.0'}), (4, {'value': '$const2.0'}), (6, {'res': '$const6.1'}), (8, {'value': '$const6.1'}), (10, {'res': '$10load_global.2'}), (12, {'res': '$shape12.3'}), (14, {'func': '$10load_global.2', 'args': ['$shape12.3'], 'res': '$14call_function.4'}), (16, {'value': '$14call_function.4', 'res': '$16get_iter.5'})), outgoing_phis={'$phi18.0': '$16get_iter.5'}, blockstack=(), active_try_block=None, outgoing_edgepushed={18: ('$16get_iter.5',)})\n", - "2024-10-16 10:10:43,732 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=18 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((18, {'iterator': '$phi18.0', 'pair': '$18for_iter.1', 'indval': '$18for_iter.2', 'pred': '$18for_iter.3'}),), outgoing_phis={'$phi20.1': '$18for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={58: (), 20: ('$phi18.0', '$18for_iter.2')})\n", - "2024-10-16 10:10:43,732 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=20 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((20, {'iterable': '$phi20.1', 'stores': ['$20unpack_sequence.2', '$20unpack_sequence.3'], 'tupleobj': '$20unpack_sequence.4'}), (22, {'value': '$20unpack_sequence.2'}), (24, {'value': '$20unpack_sequence.3'}), (26, {'res': '$s26.5'}), (28, {'res': '$const28.6'}), (30, {'lhs': '$s26.5', 'rhs': '$const28.6', 'res': '$30compare_op.7'}), (32, {'pred': '$30compare_op.7'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={34: ('$phi20.0',), 48: ('$phi20.0',)})\n", - "2024-10-16 10:10:43,733 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=34 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((34, {'res': '$num_neg_value34.1'}), (36, {'res': '$const36.2'}), (38, {'lhs': '$num_neg_value34.1', 'rhs': '$const36.2', 'res': '$38inplace_add.3'}), (40, {'value': '$38inplace_add.3'}), (42, {'res': '$ax42.4'}), (44, {'value': '$ax42.4'}), (46, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={18: ('$phi34.0',)})\n", - "2024-10-16 10:10:43,733 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=48 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((48, {'res': '$known_size48.1'}), (50, {'res': '$s50.2'}), (52, {'lhs': '$known_size48.1', 'rhs': '$s50.2', 'res': '$52inplace_multiply.3'}), (54, {'value': '$52inplace_multiply.3'}), (56, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={18: ('$phi48.0',)})\n", - "2024-10-16 10:10:43,734 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=58 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((58, {'res': '$num_neg_value58.0'}), (60, {'res': '$const60.1'}), (62, {'lhs': '$num_neg_value58.0', 'rhs': '$const60.1', 'res': '$62compare_op.2'}), (64, {'pred': '$62compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={66: (), 86: ()})\n", - "2024-10-16 10:10:43,735 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=66 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((66, {'res': '$origsize66.0'}), (68, {'res': '$known_size68.1'}), (70, {'lhs': '$origsize66.0', 'rhs': '$known_size68.1', 'res': '$70compare_op.2'}), (72, {'pred': '$70compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={74: (), 82: ()})\n", - "2024-10-16 10:10:43,735 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((74, {'res': '$74load_global.0'}), (76, {'res': '$const76.1'}), (78, {'func': '$74load_global.0', 'args': ['$const76.1'], 'res': '$78call_function.2'}), (80, {'exc': '$78call_function.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:43,736 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=82 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((82, {'res': '$const82.0'}), (84, {'retval': '$const82.0', 'castval': '$84return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:43,736 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=86 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((86, {'res': '$num_neg_value86.0'}), (88, {'res': '$const88.1'}), (90, {'lhs': '$num_neg_value86.0', 'rhs': '$const88.1', 'res': '$90compare_op.2'}), (92, {'pred': '$90compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={94: (), 160: ()})\n", - "2024-10-16 10:10:43,737 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=94 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((94, {'res': '$known_size94.0'}), (96, {'res': '$const96.1'}), (98, {'lhs': '$known_size94.0', 'rhs': '$const96.1', 'res': '$98compare_op.2'}), (100, {'pred': '$98compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={102: (), 116: ()})\n", - "2024-10-16 10:10:43,738 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=102 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((102, {'res': '$const102.0'}), (104, {'value': '$const102.0'}), (106, {'res': '$origsize106.1'}), (108, {'res': '$const108.2'}), (110, {'lhs': '$origsize106.1', 'rhs': '$const108.2', 'res': '$110compare_op.3'}), (112, {'value': '$110compare_op.3'}), (114, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={136: ()})\n", - "2024-10-16 10:10:43,738 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=116 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((116, {'res': '$origsize116.0'}), (118, {'res': '$known_size118.1'}), (120, {'lhs': '$origsize116.0', 'rhs': '$known_size118.1', 'res': '$120binary_floor_divide.2'}), (122, {'value': '$120binary_floor_divide.2'}), (124, {'res': '$origsize124.3'}), (126, {'res': '$known_size126.4'}), (128, {'lhs': '$origsize124.3', 'rhs': '$known_size126.4', 'res': '$128binary_modulo.5'}), (130, {'res': '$const130.6'}), (132, {'lhs': '$128binary_modulo.5', 'rhs': '$const130.6', 'res': '$132compare_op.7'}), (134, {'value': '$132compare_op.7'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={136: ()})\n", - "2024-10-16 10:10:43,739 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=136 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((136, {'res': '$ok136.0'}), (138, {'pred': '$ok136.0'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={140: (), 148: ()})\n", - "2024-10-16 10:10:43,740 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=140 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((140, {'res': '$140load_global.0'}), (142, {'res': '$const142.1'}), (144, {'func': '$140load_global.0', 'args': ['$const142.1'], 'res': '$144call_function.2'}), (146, {'exc': '$144call_function.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:43,740 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=148 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((148, {'res': '$inferred148.0'}), (150, {'res': '$shape150.1'}), (152, {'res': '$neg_ax152.2'}), (154, {'target': '$shape150.1', 'index': '$neg_ax152.2', 'value': '$inferred148.0'}), (156, {'res': '$const156.3'}), (158, {'retval': '$const156.3', 'castval': '$158return_value.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:43,741 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=160 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((160, {'res': '$160load_global.0'}), (162, {'res': '$const162.1'}), (164, {'func': '$160load_global.0', 'args': ['$const162.1'], 'res': '$164call_function.2'}), (166, {'exc': '$164call_function.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:43,753 - numba.core.interpreter - DEBUG - label 0:\n", - " origsize = arg(0, name=origsize) ['origsize']\n", - " shape = arg(1, name=shape) ['shape']\n", - " num_neg_value = const(int, 0) ['num_neg_value']\n", - " known_size = const(int, 1) ['known_size']\n", - " $10load_global.2 = global(enumerate: ) ['$10load_global.2']\n", - " $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_global.2', '$14call_function.4', 'shape']\n", - " $16get_iter.5 = getiter(value=$14call_function.4) ['$14call_function.4', '$16get_iter.5']\n", - " $phi18.0 = $16get_iter.5 ['$16get_iter.5', '$phi18.0']\n", - " jump 18 []\n", - "label 18:\n", - " $18for_iter.1 = iternext(value=$phi18.0) ['$18for_iter.1', '$phi18.0']\n", - " $18for_iter.2 = pair_first(value=$18for_iter.1) ['$18for_iter.1', '$18for_iter.2']\n", - " $18for_iter.3 = pair_second(value=$18for_iter.1) ['$18for_iter.1', '$18for_iter.3']\n", - " $phi20.1 = $18for_iter.2 ['$18for_iter.2', '$phi20.1']\n", - " branch $18for_iter.3, 20, 58 ['$18for_iter.3']\n", - "label 20:\n", - " $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2) ['$20unpack_sequence.4', '$phi20.1']\n", - " $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=) ['$20unpack_sequence.2', '$20unpack_sequence.4']\n", - " $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=) ['$20unpack_sequence.3', '$20unpack_sequence.4']\n", - " ax = $20unpack_sequence.2 ['$20unpack_sequence.2', 'ax']\n", - " s = $20unpack_sequence.3 ['$20unpack_sequence.3', 's']\n", - " $const28.6 = const(int, 0) ['$const28.6']\n", - " $30compare_op.7 = s < $const28.6 ['$30compare_op.7', '$const28.6', 's']\n", - " bool32 = global(bool: ) ['bool32']\n", - " $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None) ['$30compare_op.7', '$32pred', 'bool32']\n", - " branch $32pred, 34, 48 ['$32pred']\n", - "label 34:\n", - " $const36.2 = const(int, 1) ['$const36.2']\n", - " $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined) ['$38inplace_add.3', '$const36.2', 'num_neg_value']\n", - " num_neg_value = $38inplace_add.3 ['$38inplace_add.3', 'num_neg_value']\n", - " neg_ax = ax ['ax', 'neg_ax']\n", - " jump 18 []\n", - "label 48:\n", - " $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size, rhs=s, static_lhs=Undefined, static_rhs=Undefined) ['$52inplace_multiply.3', 'known_size', 's']\n", - " known_size = $52inplace_multiply.3 ['$52inplace_multiply.3', 'known_size']\n", - " jump 18 []\n", - "label 58:\n", - " $const60.1 = const(int, 0) ['$const60.1']\n", - " $62compare_op.2 = num_neg_value == $const60.1 ['$62compare_op.2', '$const60.1', 'num_neg_value']\n", - " bool64 = global(bool: ) ['bool64']\n", - " $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None) ['$62compare_op.2', '$64pred', 'bool64']\n", - " branch $64pred, 66, 86 ['$64pred']\n", - "label 66:\n", - " $70compare_op.2 = origsize != known_size ['$70compare_op.2', 'known_size', 'origsize']\n", - " bool72 = global(bool: ) ['bool72']\n", - " $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None) ['$70compare_op.2', '$72pred', 'bool72']\n", - " branch $72pred, 74, 82 ['$72pred']\n", - "label 74:\n", - " $74load_global.0 = global(ValueError: ) ['$74load_global.0']\n", - " $const76.1 = const(str, total size of new array must be unchanged) ['$const76.1']\n", - " $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None) ['$74load_global.0', '$78call_function.2', '$const76.1']\n", - " raise $78call_function.2 ['$78call_function.2']\n", - "label 82:\n", - " $const82.0 = const(NoneType, None) ['$const82.0']\n", - " $84return_value.1 = cast(value=$const82.0) ['$84return_value.1', '$const82.0']\n", - " return $84return_value.1 ['$84return_value.1']\n", - "label 86:\n", - " $const88.1 = const(int, 1) ['$const88.1']\n", - " $90compare_op.2 = num_neg_value == $const88.1 ['$90compare_op.2', '$const88.1', 'num_neg_value']\n", - " bool92 = global(bool: ) ['bool92']\n", - " $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None) ['$90compare_op.2', '$92pred', 'bool92']\n", - " branch $92pred, 94, 160 ['$92pred']\n", - "label 94:\n", - " $const96.1 = const(int, 0) ['$const96.1']\n", - " $98compare_op.2 = known_size == $const96.1 ['$98compare_op.2', '$const96.1', 'known_size']\n", - " bool100 = global(bool: ) ['bool100']\n", - " $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None) ['$100pred', '$98compare_op.2', 'bool100']\n", - " branch $100pred, 102, 116 ['$100pred']\n", - "label 102:\n", - " inferred = const(int, 0) ['inferred']\n", - " $const108.2 = const(int, 0) ['$const108.2']\n", - " ok = origsize == $const108.2 ['$const108.2', 'ok', 'origsize']\n", - " jump 136 []\n", - "label 116:\n", - " inferred = origsize // known_size ['inferred', 'known_size', 'origsize']\n", - " $128binary_modulo.5 = origsize % known_size ['$128binary_modulo.5', 'known_size', 'origsize']\n", - " $const130.6 = const(int, 0) ['$const130.6']\n", - " ok = $128binary_modulo.5 == $const130.6 ['$128binary_modulo.5', '$const130.6', 'ok']\n", - " jump 136 []\n", - "label 136:\n", - " bool138 = global(bool: ) ['bool138']\n", - " $138pred = call bool138(ok, func=bool138, args=(Var(ok, arrayobj.py:2062),), kws=(), vararg=None, varkwarg=None, target=None) ['$138pred', 'bool138', 'ok']\n", - " branch $138pred, 148, 140 ['$138pred']\n", - "label 140:\n", - " $140load_global.0 = global(ValueError: ) ['$140load_global.0']\n", - " $const142.1 = const(str, total size of new array must be unchanged) ['$const142.1']\n", - " $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None) ['$140load_global.0', '$144call_function.2', '$const142.1']\n", - " raise $144call_function.2 ['$144call_function.2']\n", - "label 148:\n", - " shape[neg_ax] = inferred ['inferred', 'neg_ax', 'shape']\n", - " $const156.3 = const(NoneType, None) ['$const156.3']\n", - " $158return_value.4 = cast(value=$const156.3) ['$158return_value.4', '$const156.3']\n", - " return $158return_value.4 ['$158return_value.4']\n", - "label 160:\n", - " $160load_global.0 = global(ValueError: ) ['$160load_global.0']\n", - " $const162.1 = const(str, multiple negative shape values) ['$const162.1']\n", - " $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None) ['$160load_global.0', '$164call_function.2', '$const162.1']\n", - " raise $164call_function.2 ['$164call_function.2']\n", - "\n", - "2024-10-16 10:10:43,810 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:43,812 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,812 - numba.core.ssa - DEBUG - on stmt: origsize = arg(0, name=origsize)\n", - "2024-10-16 10:10:43,813 - numba.core.ssa - DEBUG - on stmt: shape = arg(1, name=shape)\n", - "2024-10-16 10:10:43,814 - numba.core.ssa - DEBUG - on stmt: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:43,815 - numba.core.ssa - DEBUG - on stmt: known_size = const(int, 1)\n", - "2024-10-16 10:10:43,816 - numba.core.ssa - DEBUG - on stmt: $10load_global.2 = global(enumerate: )\n", - "2024-10-16 10:10:43,817 - numba.core.ssa - DEBUG - on stmt: $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,817 - numba.core.ssa - DEBUG - on stmt: $16get_iter.5 = getiter(value=$14call_function.4)\n", - "2024-10-16 10:10:43,818 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.5\n", - "2024-10-16 10:10:43,819 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:43,820 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 18\n", - "2024-10-16 10:10:43,820 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,821 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:43,822 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:43,823 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:43,824 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:43,824 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 58\n", - "2024-10-16 10:10:43,825 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 20\n", - "2024-10-16 10:10:43,826 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,827 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2)\n", - "2024-10-16 10:10:43,828 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=)\n", - "2024-10-16 10:10:43,828 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=)\n", - "2024-10-16 10:10:43,829 - numba.core.ssa - DEBUG - on stmt: ax = $20unpack_sequence.2\n", - "2024-10-16 10:10:43,830 - numba.core.ssa - DEBUG - on stmt: s = $20unpack_sequence.3\n", - "2024-10-16 10:10:43,831 - numba.core.ssa - DEBUG - on stmt: $const28.6 = const(int, 0)\n", - "2024-10-16 10:10:43,831 - numba.core.ssa - DEBUG - on stmt: $30compare_op.7 = s < $const28.6\n", - "2024-10-16 10:10:43,832 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:43,833 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,834 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 48\n", - "2024-10-16 10:10:43,834 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 34\n", - "2024-10-16 10:10:43,835 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,836 - numba.core.ssa - DEBUG - on stmt: $const36.2 = const(int, 1)\n", - "2024-10-16 10:10:43,837 - numba.core.ssa - DEBUG - on stmt: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:43,837 - numba.core.ssa - DEBUG - on stmt: num_neg_value = $38inplace_add.3\n", - "2024-10-16 10:10:43,838 - numba.core.ssa - DEBUG - on stmt: neg_ax = ax\n", - "2024-10-16 10:10:43,839 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:43,840 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 48\n", - "2024-10-16 10:10:43,841 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,841 - numba.core.ssa - DEBUG - on stmt: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:43,842 - numba.core.ssa - DEBUG - on stmt: known_size = $52inplace_multiply.3\n", - "2024-10-16 10:10:43,843 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:43,844 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 58\n", - "2024-10-16 10:10:43,844 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,845 - numba.core.ssa - DEBUG - on stmt: $const60.1 = const(int, 0)\n", - "2024-10-16 10:10:43,846 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = num_neg_value == $const60.1\n", - "2024-10-16 10:10:43,847 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:43,847 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,848 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 86\n", - "2024-10-16 10:10:43,849 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 66\n", - "2024-10-16 10:10:43,850 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,850 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = origsize != known_size\n", - "2024-10-16 10:10:43,851 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:43,852 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,853 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 82\n", - "2024-10-16 10:10:43,854 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-10-16 10:10:43,854 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,855 - numba.core.ssa - DEBUG - on stmt: $74load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:43,856 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:43,857 - numba.core.ssa - DEBUG - on stmt: $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,857 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:43,859 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 82\n", - "2024-10-16 10:10:43,860 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,861 - numba.core.ssa - DEBUG - on stmt: $const82.0 = const(NoneType, None)\n", - "2024-10-16 10:10:43,861 - numba.core.ssa - DEBUG - on stmt: $84return_value.1 = cast(value=$const82.0)\n", - "2024-10-16 10:10:43,862 - numba.core.ssa - DEBUG - on stmt: return $84return_value.1\n", - "2024-10-16 10:10:43,863 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 86\n", - "2024-10-16 10:10:43,864 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,864 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:43,865 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = num_neg_value == $const88.1\n", - "2024-10-16 10:10:43,866 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:43,867 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,867 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 160\n", - "2024-10-16 10:10:43,868 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 94\n", - "2024-10-16 10:10:43,869 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,870 - numba.core.ssa - DEBUG - on stmt: $const96.1 = const(int, 0)\n", - "2024-10-16 10:10:43,870 - numba.core.ssa - DEBUG - on stmt: $98compare_op.2 = known_size == $const96.1\n", - "2024-10-16 10:10:43,871 - numba.core.ssa - DEBUG - on stmt: bool100 = global(bool: )\n", - "2024-10-16 10:10:43,872 - numba.core.ssa - DEBUG - on stmt: $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,873 - numba.core.ssa - DEBUG - on stmt: branch $100pred, 102, 116\n", - "2024-10-16 10:10:43,873 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 102\n", - "2024-10-16 10:10:43,874 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,875 - numba.core.ssa - DEBUG - on stmt: inferred = const(int, 0)\n", - "2024-10-16 10:10:43,876 - numba.core.ssa - DEBUG - on stmt: $const108.2 = const(int, 0)\n", - "2024-10-16 10:10:43,876 - numba.core.ssa - DEBUG - on stmt: ok = origsize == $const108.2\n", - "2024-10-16 10:10:43,877 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:43,878 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 116\n", - "2024-10-16 10:10:43,879 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,879 - numba.core.ssa - DEBUG - on stmt: inferred = origsize // known_size\n", - "2024-10-16 10:10:43,880 - numba.core.ssa - DEBUG - on stmt: $128binary_modulo.5 = origsize % known_size\n", - "2024-10-16 10:10:43,881 - numba.core.ssa - DEBUG - on stmt: $const130.6 = const(int, 0)\n", - "2024-10-16 10:10:43,882 - numba.core.ssa - DEBUG - on stmt: ok = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:43,882 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:43,883 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 136\n", - "2024-10-16 10:10:43,884 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,885 - numba.core.ssa - DEBUG - on stmt: bool138 = global(bool: )\n", - "2024-10-16 10:10:43,885 - numba.core.ssa - DEBUG - on stmt: $138pred = call bool138(ok, func=bool138, args=(Var(ok, arrayobj.py:2062),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,886 - numba.core.ssa - DEBUG - on stmt: branch $138pred, 148, 140\n", - "2024-10-16 10:10:43,887 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 140\n", - "2024-10-16 10:10:43,888 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,889 - numba.core.ssa - DEBUG - on stmt: $140load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:43,889 - numba.core.ssa - DEBUG - on stmt: $const142.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:43,890 - numba.core.ssa - DEBUG - on stmt: $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,891 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:43,892 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 148\n", - "2024-10-16 10:10:43,892 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,893 - numba.core.ssa - DEBUG - on stmt: shape[neg_ax] = inferred\n", - "2024-10-16 10:10:43,894 - numba.core.ssa - DEBUG - on stmt: $const156.3 = const(NoneType, None)\n", - "2024-10-16 10:10:43,895 - numba.core.ssa - DEBUG - on stmt: $158return_value.4 = cast(value=$const156.3)\n", - "2024-10-16 10:10:43,895 - numba.core.ssa - DEBUG - on stmt: return $158return_value.4\n", - "2024-10-16 10:10:43,896 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 160\n", - "2024-10-16 10:10:43,897 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,898 - numba.core.ssa - DEBUG - on stmt: $160load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:43,898 - numba.core.ssa - DEBUG - on stmt: $const162.1 = const(str, multiple negative shape values)\n", - "2024-10-16 10:10:43,899 - numba.core.ssa - DEBUG - on stmt: $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,900 - numba.core.ssa - DEBUG - on stmt: raise ('multiple negative shape values')\n", - "2024-10-16 10:10:43,901 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 161\n", - "2024-10-16 10:10:43,901 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,902 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:43,904 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$100pred': [],\n", - " '$10load_global.2': [],\n", - " '$128binary_modulo.5': [],\n", - " '$138pred': [],\n", - " '$140load_global.0': [],\n", - " '$144call_function.2': [],\n", - " '$14call_function.4': [],\n", - " '$158return_value.4': [],\n", - " '$160load_global.0': [],\n", - " '$164call_function.2': [],\n", - " '$16get_iter.5': [],\n", - " '$18for_iter.1': [],\n", - " '$18for_iter.2': [],\n", - " '$18for_iter.3': [],\n", - " '$20unpack_sequence.2': [],\n", - " '$20unpack_sequence.3': [],\n", - " '$20unpack_sequence.4': [],\n", - " '$30compare_op.7': [],\n", - " '$32pred': [],\n", - " '$38inplace_add.3': [],\n", - " '$52inplace_multiply.3': [],\n", - " '$62compare_op.2': [],\n", - " '$64pred': [],\n", - " '$70compare_op.2': [],\n", - " '$72pred': [],\n", - " '$74load_global.0': [],\n", - " '$78call_function.2': [],\n", - " '$84return_value.1': [],\n", - " '$90compare_op.2': [],\n", - " '$92pred': [],\n", - " '$98compare_op.2': [],\n", - " '$const108.2': [],\n", - " '$const130.6': [],\n", - " '$const142.1': [],\n", - " '$const156.3': [],\n", - " '$const162.1': [],\n", - " '$const28.6': [],\n", - " '$const36.2': [],\n", - " '$const60.1': [],\n", - " '$const76.1': [],\n", - " '$const82.0': [],\n", - " '$const88.1': [],\n", - " '$const96.1': [],\n", - " '$phi18.0': [],\n", - " '$phi20.1': [],\n", - " 'ax': [],\n", - " 'bool100': [],\n", - " 'bool138': [],\n", - " 'bool32': [],\n", - " 'bool64': [],\n", - " 'bool72': [],\n", - " 'bool92': [],\n", - " 'inferred': [,\n", - " ],\n", - " 'known_size': [,\n", - " ],\n", - " 'neg_ax': [],\n", - " 'num_neg_value': [,\n", - " ],\n", - " 'ok': [,\n", - " ],\n", - " 'origsize': [],\n", - " 's': [],\n", - " 'shape': []})\n", - "2024-10-16 10:10:43,905 - numba.core.ssa - DEBUG - SSA violators {'num_neg_value', 'known_size', 'ok', 'inferred'}\n", - "2024-10-16 10:10:43,906 - numba.core.ssa - DEBUG - Fix SSA violator on var num_neg_value\n", - "2024-10-16 10:10:43,907 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:43,907 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,908 - numba.core.ssa - DEBUG - on stmt: origsize = arg(0, name=origsize)\n", - "2024-10-16 10:10:43,909 - numba.core.ssa - DEBUG - on stmt: shape = arg(1, name=shape)\n", - "2024-10-16 10:10:43,910 - numba.core.ssa - DEBUG - on stmt: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:43,911 - numba.core.ssa - DEBUG - first assign: num_neg_value\n", - "2024-10-16 10:10:43,912 - numba.core.ssa - DEBUG - replaced with: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:43,912 - numba.core.ssa - DEBUG - on stmt: known_size = const(int, 1)\n", - "2024-10-16 10:10:43,913 - numba.core.ssa - DEBUG - on stmt: $10load_global.2 = global(enumerate: )\n", - "2024-10-16 10:10:43,914 - numba.core.ssa - DEBUG - on stmt: $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,915 - numba.core.ssa - DEBUG - on stmt: $16get_iter.5 = getiter(value=$14call_function.4)\n", - "2024-10-16 10:10:43,916 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.5\n", - "2024-10-16 10:10:43,916 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:43,917 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:43,918 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,918 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:43,919 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:43,920 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:43,921 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:43,921 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 58\n", - "2024-10-16 10:10:43,922 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 20\n", - "2024-10-16 10:10:43,923 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,923 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2)\n", - "2024-10-16 10:10:43,924 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=)\n", - "2024-10-16 10:10:43,925 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=)\n", - "2024-10-16 10:10:43,926 - numba.core.ssa - DEBUG - on stmt: ax = $20unpack_sequence.2\n", - "2024-10-16 10:10:43,926 - numba.core.ssa - DEBUG - on stmt: s = $20unpack_sequence.3\n", - "2024-10-16 10:10:43,927 - numba.core.ssa - DEBUG - on stmt: $const28.6 = const(int, 0)\n", - "2024-10-16 10:10:43,928 - numba.core.ssa - DEBUG - on stmt: $30compare_op.7 = s < $const28.6\n", - "2024-10-16 10:10:43,929 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:43,930 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,930 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 48\n", - "2024-10-16 10:10:43,931 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:43,932 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,933 - numba.core.ssa - DEBUG - on stmt: $const36.2 = const(int, 1)\n", - "2024-10-16 10:10:43,933 - numba.core.ssa - DEBUG - on stmt: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:43,934 - numba.core.ssa - DEBUG - on stmt: num_neg_value = $38inplace_add.3\n", - "2024-10-16 10:10:43,935 - numba.core.ssa - DEBUG - replaced with: num_neg_value.1 = $38inplace_add.3\n", - "2024-10-16 10:10:43,936 - numba.core.ssa - DEBUG - on stmt: neg_ax = ax\n", - "2024-10-16 10:10:43,936 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:43,937 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 48\n", - "2024-10-16 10:10:43,938 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,938 - numba.core.ssa - DEBUG - on stmt: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:43,939 - numba.core.ssa - DEBUG - on stmt: known_size = $52inplace_multiply.3\n", - "2024-10-16 10:10:43,940 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:43,940 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:43,941 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,942 - numba.core.ssa - DEBUG - on stmt: $const60.1 = const(int, 0)\n", - "2024-10-16 10:10:43,943 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = num_neg_value == $const60.1\n", - "2024-10-16 10:10:43,943 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:43,944 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,945 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 86\n", - "2024-10-16 10:10:43,946 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:43,946 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,947 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = origsize != known_size\n", - "2024-10-16 10:10:43,948 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:43,949 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,950 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 82\n", - "2024-10-16 10:10:43,950 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:43,951 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,952 - numba.core.ssa - DEBUG - on stmt: $74load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:43,953 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:43,953 - numba.core.ssa - DEBUG - on stmt: $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,954 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:43,955 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 82\n", - "2024-10-16 10:10:43,956 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,957 - numba.core.ssa - DEBUG - on stmt: $const82.0 = const(NoneType, None)\n", - "2024-10-16 10:10:43,957 - numba.core.ssa - DEBUG - on stmt: $84return_value.1 = cast(value=$const82.0)\n", - "2024-10-16 10:10:43,958 - numba.core.ssa - DEBUG - on stmt: return $84return_value.1\n", - "2024-10-16 10:10:43,959 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:43,960 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,960 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:43,961 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = num_neg_value == $const88.1\n", - "2024-10-16 10:10:43,962 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:43,963 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,963 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 160\n", - "2024-10-16 10:10:43,964 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:43,965 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,966 - numba.core.ssa - DEBUG - on stmt: $const96.1 = const(int, 0)\n", - "2024-10-16 10:10:43,967 - numba.core.ssa - DEBUG - on stmt: $98compare_op.2 = known_size == $const96.1\n", - "2024-10-16 10:10:43,967 - numba.core.ssa - DEBUG - on stmt: bool100 = global(bool: )\n", - "2024-10-16 10:10:43,968 - numba.core.ssa - DEBUG - on stmt: $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,969 - numba.core.ssa - DEBUG - on stmt: branch $100pred, 102, 116\n", - "2024-10-16 10:10:43,970 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:43,970 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,971 - numba.core.ssa - DEBUG - on stmt: inferred = const(int, 0)\n", - "2024-10-16 10:10:43,972 - numba.core.ssa - DEBUG - on stmt: $const108.2 = const(int, 0)\n", - "2024-10-16 10:10:43,972 - numba.core.ssa - DEBUG - on stmt: ok = origsize == $const108.2\n", - "2024-10-16 10:10:43,973 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:43,974 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 116\n", - "2024-10-16 10:10:43,975 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,975 - numba.core.ssa - DEBUG - on stmt: inferred = origsize // known_size\n", - "2024-10-16 10:10:43,976 - numba.core.ssa - DEBUG - on stmt: $128binary_modulo.5 = origsize % known_size\n", - "2024-10-16 10:10:43,977 - numba.core.ssa - DEBUG - on stmt: $const130.6 = const(int, 0)\n", - "2024-10-16 10:10:43,978 - numba.core.ssa - DEBUG - on stmt: ok = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:43,978 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:43,979 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-10-16 10:10:43,980 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,981 - numba.core.ssa - DEBUG - on stmt: bool138 = global(bool: )\n", - "2024-10-16 10:10:43,981 - numba.core.ssa - DEBUG - on stmt: $138pred = call bool138(ok, func=bool138, args=(Var(ok, arrayobj.py:2062),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,982 - numba.core.ssa - DEBUG - on stmt: branch $138pred, 148, 140\n", - "2024-10-16 10:10:43,983 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 140\n", - "2024-10-16 10:10:43,983 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,984 - numba.core.ssa - DEBUG - on stmt: $140load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:43,985 - numba.core.ssa - DEBUG - on stmt: $const142.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:43,986 - numba.core.ssa - DEBUG - on stmt: $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,986 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:43,987 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 148\n", - "2024-10-16 10:10:43,988 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,989 - numba.core.ssa - DEBUG - on stmt: shape[neg_ax] = inferred\n", - "2024-10-16 10:10:43,989 - numba.core.ssa - DEBUG - on stmt: $const156.3 = const(NoneType, None)\n", - "2024-10-16 10:10:43,990 - numba.core.ssa - DEBUG - on stmt: $158return_value.4 = cast(value=$const156.3)\n", - "2024-10-16 10:10:43,991 - numba.core.ssa - DEBUG - on stmt: return $158return_value.4\n", - "2024-10-16 10:10:43,992 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 160\n", - "2024-10-16 10:10:43,992 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,993 - numba.core.ssa - DEBUG - on stmt: $160load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:43,994 - numba.core.ssa - DEBUG - on stmt: $const162.1 = const(str, multiple negative shape values)\n", - "2024-10-16 10:10:43,994 - numba.core.ssa - DEBUG - on stmt: $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:43,995 - numba.core.ssa - DEBUG - on stmt: raise ('multiple negative shape values')\n", - "2024-10-16 10:10:43,996 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 161\n", - "2024-10-16 10:10:43,997 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:43,997 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:43,998 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 34: []})\n", - "2024-10-16 10:10:43,999 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:44,000 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,000 - numba.core.ssa - DEBUG - on stmt: origsize = arg(0, name=origsize)\n", - "2024-10-16 10:10:44,001 - numba.core.ssa - DEBUG - on stmt: shape = arg(1, name=shape)\n", - "2024-10-16 10:10:44,002 - numba.core.ssa - DEBUG - on stmt: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:44,003 - numba.core.ssa - DEBUG - on stmt: known_size = const(int, 1)\n", - "2024-10-16 10:10:44,003 - numba.core.ssa - DEBUG - on stmt: $10load_global.2 = global(enumerate: )\n", - "2024-10-16 10:10:44,004 - numba.core.ssa - DEBUG - on stmt: $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,005 - numba.core.ssa - DEBUG - on stmt: $16get_iter.5 = getiter(value=$14call_function.4)\n", - "2024-10-16 10:10:44,005 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.5\n", - "2024-10-16 10:10:44,006 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,007 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:44,008 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,008 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:44,009 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,010 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,010 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:44,011 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 58\n", - "2024-10-16 10:10:44,012 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 20\n", - "2024-10-16 10:10:44,013 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,013 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2)\n", - "2024-10-16 10:10:44,014 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=)\n", - "2024-10-16 10:10:44,014 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=)\n", - "2024-10-16 10:10:44,015 - numba.core.ssa - DEBUG - on stmt: ax = $20unpack_sequence.2\n", - "2024-10-16 10:10:44,016 - numba.core.ssa - DEBUG - on stmt: s = $20unpack_sequence.3\n", - "2024-10-16 10:10:44,017 - numba.core.ssa - DEBUG - on stmt: $const28.6 = const(int, 0)\n", - "2024-10-16 10:10:44,017 - numba.core.ssa - DEBUG - on stmt: $30compare_op.7 = s < $const28.6\n", - "2024-10-16 10:10:44,018 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:44,019 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,020 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 48\n", - "2024-10-16 10:10:44,020 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:44,021 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,022 - numba.core.ssa - DEBUG - on stmt: $const36.2 = const(int, 1)\n", - "2024-10-16 10:10:44,023 - numba.core.ssa - DEBUG - on stmt: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,023 - numba.core.ssa - DEBUG - find_def var='num_neg_value' stmt=$38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,024 - numba.core.ssa - DEBUG - find_def_from_top label 34\n", - "2024-10-16 10:10:44,025 - numba.core.ssa - DEBUG - idom 20 from label 34\n", - "2024-10-16 10:10:44,025 - numba.core.ssa - DEBUG - find_def_from_bottom label 20\n", - "2024-10-16 10:10:44,026 - numba.core.ssa - DEBUG - find_def_from_top label 20\n", - "2024-10-16 10:10:44,027 - numba.core.ssa - DEBUG - idom 18 from label 20\n", - "2024-10-16 10:10:44,027 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,028 - numba.core.ssa - DEBUG - find_def_from_top label 18\n", - "2024-10-16 10:10:44,029 - numba.core.ssa - DEBUG - insert phi node num_neg_value.2 = phi(incoming_values=[], incoming_blocks=[]) at 18\n", - "2024-10-16 10:10:44,030 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:10:44,030 - numba.core.ssa - DEBUG - incoming_def num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:44,031 - numba.core.ssa - DEBUG - find_def_from_bottom label 161\n", - "2024-10-16 10:10:44,032 - numba.core.ssa - DEBUG - find_def_from_top label 161\n", - "2024-10-16 10:10:44,032 - numba.core.ssa - DEBUG - insert phi node num_neg_value.3 = phi(incoming_values=[], incoming_blocks=[]) at 161\n", - "2024-10-16 10:10:44,033 - numba.core.ssa - DEBUG - find_def_from_bottom label 48\n", - "2024-10-16 10:10:44,034 - numba.core.ssa - DEBUG - find_def_from_top label 48\n", - "2024-10-16 10:10:44,034 - numba.core.ssa - DEBUG - idom 20 from label 48\n", - "2024-10-16 10:10:44,035 - numba.core.ssa - DEBUG - find_def_from_bottom label 20\n", - "2024-10-16 10:10:44,036 - numba.core.ssa - DEBUG - find_def_from_top label 20\n", - "2024-10-16 10:10:44,036 - numba.core.ssa - DEBUG - idom 18 from label 20\n", - "2024-10-16 10:10:44,037 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,038 - numba.core.ssa - DEBUG - incoming_def num_neg_value.2 = phi(incoming_values=[Var(num_neg_value, arrayobj.py:2045)], incoming_blocks=[0])\n", - "2024-10-16 10:10:44,038 - numba.core.ssa - DEBUG - find_def_from_bottom label 34\n", - "2024-10-16 10:10:44,039 - numba.core.ssa - DEBUG - incoming_def num_neg_value.1 = $38inplace_add.3\n", - "2024-10-16 10:10:44,040 - numba.core.ssa - DEBUG - incoming_def num_neg_value.3 = phi(incoming_values=[Var(num_neg_value.2, arrayobj.py:2049), Var(num_neg_value.1, arrayobj.py:2049)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,040 - numba.core.ssa - DEBUG - replaced with: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value.2, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,041 - numba.core.ssa - DEBUG - on stmt: num_neg_value.1 = $38inplace_add.3\n", - "2024-10-16 10:10:44,042 - numba.core.ssa - DEBUG - on stmt: neg_ax = ax\n", - "2024-10-16 10:10:44,043 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,043 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 48\n", - "2024-10-16 10:10:44,044 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,045 - numba.core.ssa - DEBUG - on stmt: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,045 - numba.core.ssa - DEBUG - on stmt: known_size = $52inplace_multiply.3\n", - "2024-10-16 10:10:44,046 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,047 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:44,047 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,048 - numba.core.ssa - DEBUG - on stmt: $const60.1 = const(int, 0)\n", - "2024-10-16 10:10:44,049 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = num_neg_value == $const60.1\n", - "2024-10-16 10:10:44,049 - numba.core.ssa - DEBUG - find_def var='num_neg_value' stmt=$62compare_op.2 = num_neg_value == $const60.1\n", - "2024-10-16 10:10:44,050 - numba.core.ssa - DEBUG - find_def_from_top label 58\n", - "2024-10-16 10:10:44,051 - numba.core.ssa - DEBUG - idom 18 from label 58\n", - "2024-10-16 10:10:44,051 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,052 - numba.core.ssa - DEBUG - replaced with: $62compare_op.2 = num_neg_value.2 == $const60.1\n", - "2024-10-16 10:10:44,053 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:44,053 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,054 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 86\n", - "2024-10-16 10:10:44,055 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:44,056 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,056 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = origsize != known_size\n", - "2024-10-16 10:10:44,057 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:44,058 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,058 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 82\n", - "2024-10-16 10:10:44,059 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:44,060 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,060 - numba.core.ssa - DEBUG - on stmt: $74load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,061 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,062 - numba.core.ssa - DEBUG - on stmt: $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,063 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,063 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 82\n", - "2024-10-16 10:10:44,064 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,064 - numba.core.ssa - DEBUG - on stmt: $const82.0 = const(NoneType, None)\n", - "2024-10-16 10:10:44,065 - numba.core.ssa - DEBUG - on stmt: $84return_value.1 = cast(value=$const82.0)\n", - "2024-10-16 10:10:44,066 - numba.core.ssa - DEBUG - on stmt: return $84return_value.1\n", - "2024-10-16 10:10:44,067 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:44,067 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,068 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:44,069 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = num_neg_value == $const88.1\n", - "2024-10-16 10:10:44,069 - numba.core.ssa - DEBUG - find_def var='num_neg_value' stmt=$90compare_op.2 = num_neg_value == $const88.1\n", - "2024-10-16 10:10:44,070 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-10-16 10:10:44,071 - numba.core.ssa - DEBUG - idom 58 from label 86\n", - "2024-10-16 10:10:44,072 - numba.core.ssa - DEBUG - find_def_from_bottom label 58\n", - "2024-10-16 10:10:44,072 - numba.core.ssa - DEBUG - find_def_from_top label 58\n", - "2024-10-16 10:10:44,073 - numba.core.ssa - DEBUG - idom 18 from label 58\n", - "2024-10-16 10:10:44,073 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,074 - numba.core.ssa - DEBUG - replaced with: $90compare_op.2 = num_neg_value.2 == $const88.1\n", - "2024-10-16 10:10:44,075 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:44,076 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,076 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 160\n", - "2024-10-16 10:10:44,077 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:44,078 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,078 - numba.core.ssa - DEBUG - on stmt: $const96.1 = const(int, 0)\n", - "2024-10-16 10:10:44,079 - numba.core.ssa - DEBUG - on stmt: $98compare_op.2 = known_size == $const96.1\n", - "2024-10-16 10:10:44,080 - numba.core.ssa - DEBUG - on stmt: bool100 = global(bool: )\n", - "2024-10-16 10:10:44,081 - numba.core.ssa - DEBUG - on stmt: $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,081 - numba.core.ssa - DEBUG - on stmt: branch $100pred, 102, 116\n", - "2024-10-16 10:10:44,082 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:44,083 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,083 - numba.core.ssa - DEBUG - on stmt: inferred = const(int, 0)\n", - "2024-10-16 10:10:44,084 - numba.core.ssa - DEBUG - on stmt: $const108.2 = const(int, 0)\n", - "2024-10-16 10:10:44,085 - numba.core.ssa - DEBUG - on stmt: ok = origsize == $const108.2\n", - "2024-10-16 10:10:44,085 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,086 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 116\n", - "2024-10-16 10:10:44,087 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,087 - numba.core.ssa - DEBUG - on stmt: inferred = origsize // known_size\n", - "2024-10-16 10:10:44,088 - numba.core.ssa - DEBUG - on stmt: $128binary_modulo.5 = origsize % known_size\n", - "2024-10-16 10:10:44,088 - numba.core.ssa - DEBUG - on stmt: $const130.6 = const(int, 0)\n", - "2024-10-16 10:10:44,089 - numba.core.ssa - DEBUG - on stmt: ok = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:44,090 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,091 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-10-16 10:10:44,091 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,092 - numba.core.ssa - DEBUG - on stmt: bool138 = global(bool: )\n", - "2024-10-16 10:10:44,092 - numba.core.ssa - DEBUG - on stmt: $138pred = call bool138(ok, func=bool138, args=(Var(ok, arrayobj.py:2062),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,093 - numba.core.ssa - DEBUG - on stmt: branch $138pred, 148, 140\n", - "2024-10-16 10:10:44,094 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 140\n", - "2024-10-16 10:10:44,094 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,095 - numba.core.ssa - DEBUG - on stmt: $140load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,096 - numba.core.ssa - DEBUG - on stmt: $const142.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,096 - numba.core.ssa - DEBUG - on stmt: $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,097 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,098 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 148\n", - "2024-10-16 10:10:44,098 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,099 - numba.core.ssa - DEBUG - on stmt: shape[neg_ax] = inferred\n", - "2024-10-16 10:10:44,100 - numba.core.ssa - DEBUG - on stmt: $const156.3 = const(NoneType, None)\n", - "2024-10-16 10:10:44,100 - numba.core.ssa - DEBUG - on stmt: $158return_value.4 = cast(value=$const156.3)\n", - "2024-10-16 10:10:44,101 - numba.core.ssa - DEBUG - on stmt: return $158return_value.4\n", - "2024-10-16 10:10:44,102 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 160\n", - "2024-10-16 10:10:44,102 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,103 - numba.core.ssa - DEBUG - on stmt: $160load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,104 - numba.core.ssa - DEBUG - on stmt: $const162.1 = const(str, multiple negative shape values)\n", - "2024-10-16 10:10:44,104 - numba.core.ssa - DEBUG - on stmt: $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,105 - numba.core.ssa - DEBUG - on stmt: raise ('multiple negative shape values')\n", - "2024-10-16 10:10:44,106 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 161\n", - "2024-10-16 10:10:44,106 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,107 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,108 - numba.core.ssa - DEBUG - Fix SSA violator on var known_size\n", - "2024-10-16 10:10:44,108 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:44,109 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,110 - numba.core.ssa - DEBUG - on stmt: origsize = arg(0, name=origsize)\n", - "2024-10-16 10:10:44,110 - numba.core.ssa - DEBUG - on stmt: shape = arg(1, name=shape)\n", - "2024-10-16 10:10:44,111 - numba.core.ssa - DEBUG - on stmt: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:44,112 - numba.core.ssa - DEBUG - on stmt: known_size = const(int, 1)\n", - "2024-10-16 10:10:44,112 - numba.core.ssa - DEBUG - first assign: known_size\n", - "2024-10-16 10:10:44,113 - numba.core.ssa - DEBUG - replaced with: known_size = const(int, 1)\n", - "2024-10-16 10:10:44,113 - numba.core.ssa - DEBUG - on stmt: $10load_global.2 = global(enumerate: )\n", - "2024-10-16 10:10:44,114 - numba.core.ssa - DEBUG - on stmt: $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,115 - numba.core.ssa - DEBUG - on stmt: $16get_iter.5 = getiter(value=$14call_function.4)\n", - "2024-10-16 10:10:44,115 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.5\n", - "2024-10-16 10:10:44,116 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,117 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:44,117 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,118 - numba.core.ssa - DEBUG - on stmt: num_neg_value.2 = phi(incoming_values=[Var(num_neg_value, arrayobj.py:2045), Var(num_neg_value.3, arrayobj.py:2049)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,119 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:44,119 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,120 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,120 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:44,121 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 58\n", - "2024-10-16 10:10:44,122 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 20\n", - "2024-10-16 10:10:44,122 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,123 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2)\n", - "2024-10-16 10:10:44,124 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=)\n", - "2024-10-16 10:10:44,124 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=)\n", - "2024-10-16 10:10:44,125 - numba.core.ssa - DEBUG - on stmt: ax = $20unpack_sequence.2\n", - "2024-10-16 10:10:44,126 - numba.core.ssa - DEBUG - on stmt: s = $20unpack_sequence.3\n", - "2024-10-16 10:10:44,126 - numba.core.ssa - DEBUG - on stmt: $const28.6 = const(int, 0)\n", - "2024-10-16 10:10:44,127 - numba.core.ssa - DEBUG - on stmt: $30compare_op.7 = s < $const28.6\n", - "2024-10-16 10:10:44,128 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:44,128 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,129 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 48\n", - "2024-10-16 10:10:44,130 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:44,130 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,131 - numba.core.ssa - DEBUG - on stmt: $const36.2 = const(int, 1)\n", - "2024-10-16 10:10:44,131 - numba.core.ssa - DEBUG - on stmt: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value.2, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,132 - numba.core.ssa - DEBUG - on stmt: num_neg_value.1 = $38inplace_add.3\n", - "2024-10-16 10:10:44,133 - numba.core.ssa - DEBUG - on stmt: neg_ax = ax\n", - "2024-10-16 10:10:44,133 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,134 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 48\n", - "2024-10-16 10:10:44,135 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,135 - numba.core.ssa - DEBUG - on stmt: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,136 - numba.core.ssa - DEBUG - on stmt: known_size = $52inplace_multiply.3\n", - "2024-10-16 10:10:44,137 - numba.core.ssa - DEBUG - replaced with: known_size.1 = $52inplace_multiply.3\n", - "2024-10-16 10:10:44,137 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,138 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:44,138 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,139 - numba.core.ssa - DEBUG - on stmt: $const60.1 = const(int, 0)\n", - "2024-10-16 10:10:44,140 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = num_neg_value.2 == $const60.1\n", - "2024-10-16 10:10:44,140 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:44,141 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,142 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 86\n", - "2024-10-16 10:10:44,142 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:44,143 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,143 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = origsize != known_size\n", - "2024-10-16 10:10:44,144 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:44,145 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,145 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 82\n", - "2024-10-16 10:10:44,146 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:44,146 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,147 - numba.core.ssa - DEBUG - on stmt: $74load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,148 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,148 - numba.core.ssa - DEBUG - on stmt: $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,149 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,149 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 82\n", - "2024-10-16 10:10:44,150 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,151 - numba.core.ssa - DEBUG - on stmt: $const82.0 = const(NoneType, None)\n", - "2024-10-16 10:10:44,151 - numba.core.ssa - DEBUG - on stmt: $84return_value.1 = cast(value=$const82.0)\n", - "2024-10-16 10:10:44,152 - numba.core.ssa - DEBUG - on stmt: return $84return_value.1\n", - "2024-10-16 10:10:44,153 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:44,153 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,154 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:44,154 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = num_neg_value.2 == $const88.1\n", - "2024-10-16 10:10:44,155 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:44,156 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,156 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 160\n", - "2024-10-16 10:10:44,157 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:44,158 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,158 - numba.core.ssa - DEBUG - on stmt: $const96.1 = const(int, 0)\n", - "2024-10-16 10:10:44,159 - numba.core.ssa - DEBUG - on stmt: $98compare_op.2 = known_size == $const96.1\n", - "2024-10-16 10:10:44,160 - numba.core.ssa - DEBUG - on stmt: bool100 = global(bool: )\n", - "2024-10-16 10:10:44,160 - numba.core.ssa - DEBUG - on stmt: $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,161 - numba.core.ssa - DEBUG - on stmt: branch $100pred, 102, 116\n", - "2024-10-16 10:10:44,161 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:44,162 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,163 - numba.core.ssa - DEBUG - on stmt: inferred = const(int, 0)\n", - "2024-10-16 10:10:44,163 - numba.core.ssa - DEBUG - on stmt: $const108.2 = const(int, 0)\n", - "2024-10-16 10:10:44,164 - numba.core.ssa - DEBUG - on stmt: ok = origsize == $const108.2\n", - "2024-10-16 10:10:44,165 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,165 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 116\n", - "2024-10-16 10:10:44,166 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,166 - numba.core.ssa - DEBUG - on stmt: inferred = origsize // known_size\n", - "2024-10-16 10:10:44,167 - numba.core.ssa - DEBUG - on stmt: $128binary_modulo.5 = origsize % known_size\n", - "2024-10-16 10:10:44,168 - numba.core.ssa - DEBUG - on stmt: $const130.6 = const(int, 0)\n", - "2024-10-16 10:10:44,168 - numba.core.ssa - DEBUG - on stmt: ok = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:44,169 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,169 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-10-16 10:10:44,170 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,171 - numba.core.ssa - DEBUG - on stmt: bool138 = global(bool: )\n", - "2024-10-16 10:10:44,171 - numba.core.ssa - DEBUG - on stmt: $138pred = call bool138(ok, func=bool138, args=(Var(ok, arrayobj.py:2062),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,172 - numba.core.ssa - DEBUG - on stmt: branch $138pred, 148, 140\n", - "2024-10-16 10:10:44,173 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 140\n", - "2024-10-16 10:10:44,173 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,174 - numba.core.ssa - DEBUG - on stmt: $140load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,174 - numba.core.ssa - DEBUG - on stmt: $const142.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,175 - numba.core.ssa - DEBUG - on stmt: $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,176 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,176 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 148\n", - "2024-10-16 10:10:44,177 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,178 - numba.core.ssa - DEBUG - on stmt: shape[neg_ax] = inferred\n", - "2024-10-16 10:10:44,178 - numba.core.ssa - DEBUG - on stmt: $const156.3 = const(NoneType, None)\n", - "2024-10-16 10:10:44,179 - numba.core.ssa - DEBUG - on stmt: $158return_value.4 = cast(value=$const156.3)\n", - "2024-10-16 10:10:44,179 - numba.core.ssa - DEBUG - on stmt: return $158return_value.4\n", - "2024-10-16 10:10:44,180 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 160\n", - "2024-10-16 10:10:44,181 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,181 - numba.core.ssa - DEBUG - on stmt: $160load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,182 - numba.core.ssa - DEBUG - on stmt: $const162.1 = const(str, multiple negative shape values)\n", - "2024-10-16 10:10:44,182 - numba.core.ssa - DEBUG - on stmt: $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,183 - numba.core.ssa - DEBUG - on stmt: raise ('multiple negative shape values')\n", - "2024-10-16 10:10:44,184 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 161\n", - "2024-10-16 10:10:44,184 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,185 - numba.core.ssa - DEBUG - on stmt: num_neg_value.3 = phi(incoming_values=[Var(num_neg_value.2, arrayobj.py:2049), Var(num_neg_value.1, arrayobj.py:2049)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,186 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,186 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 48: []})\n", - "2024-10-16 10:10:44,187 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:44,188 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,188 - numba.core.ssa - DEBUG - on stmt: origsize = arg(0, name=origsize)\n", - "2024-10-16 10:10:44,189 - numba.core.ssa - DEBUG - on stmt: shape = arg(1, name=shape)\n", - "2024-10-16 10:10:44,189 - numba.core.ssa - DEBUG - on stmt: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:44,190 - numba.core.ssa - DEBUG - on stmt: known_size = const(int, 1)\n", - "2024-10-16 10:10:44,191 - numba.core.ssa - DEBUG - on stmt: $10load_global.2 = global(enumerate: )\n", - "2024-10-16 10:10:44,191 - numba.core.ssa - DEBUG - on stmt: $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,192 - numba.core.ssa - DEBUG - on stmt: $16get_iter.5 = getiter(value=$14call_function.4)\n", - "2024-10-16 10:10:44,193 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.5\n", - "2024-10-16 10:10:44,193 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,194 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:44,195 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,195 - numba.core.ssa - DEBUG - on stmt: num_neg_value.2 = phi(incoming_values=[Var(num_neg_value, arrayobj.py:2045), Var(num_neg_value.3, arrayobj.py:2049)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,196 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:44,196 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,197 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,198 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:44,198 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 58\n", - "2024-10-16 10:10:44,199 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 20\n", - "2024-10-16 10:10:44,199 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,263 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2)\n", - "2024-10-16 10:10:44,263 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=)\n", - "2024-10-16 10:10:44,264 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=)\n", - "2024-10-16 10:10:44,264 - numba.core.ssa - DEBUG - on stmt: ax = $20unpack_sequence.2\n", - "2024-10-16 10:10:44,265 - numba.core.ssa - DEBUG - on stmt: s = $20unpack_sequence.3\n", - "2024-10-16 10:10:44,265 - numba.core.ssa - DEBUG - on stmt: $const28.6 = const(int, 0)\n", - "2024-10-16 10:10:44,266 - numba.core.ssa - DEBUG - on stmt: $30compare_op.7 = s < $const28.6\n", - "2024-10-16 10:10:44,267 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:44,268 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,268 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 48\n", - "2024-10-16 10:10:44,269 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:44,269 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,270 - numba.core.ssa - DEBUG - on stmt: $const36.2 = const(int, 1)\n", - "2024-10-16 10:10:44,270 - numba.core.ssa - DEBUG - on stmt: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value.2, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,271 - numba.core.ssa - DEBUG - on stmt: num_neg_value.1 = $38inplace_add.3\n", - "2024-10-16 10:10:44,272 - numba.core.ssa - DEBUG - on stmt: neg_ax = ax\n", - "2024-10-16 10:10:44,272 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,273 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 48\n", - "2024-10-16 10:10:44,274 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,274 - numba.core.ssa - DEBUG - on stmt: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,274 - numba.core.ssa - DEBUG - find_def var='known_size' stmt=$52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,276 - numba.core.ssa - DEBUG - find_def_from_top label 48\n", - "2024-10-16 10:10:44,276 - numba.core.ssa - DEBUG - idom 20 from label 48\n", - "2024-10-16 10:10:44,277 - numba.core.ssa - DEBUG - find_def_from_bottom label 20\n", - "2024-10-16 10:10:44,277 - numba.core.ssa - DEBUG - find_def_from_top label 20\n", - "2024-10-16 10:10:44,278 - numba.core.ssa - DEBUG - idom 18 from label 20\n", - "2024-10-16 10:10:44,278 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,279 - numba.core.ssa - DEBUG - find_def_from_top label 18\n", - "2024-10-16 10:10:44,279 - numba.core.ssa - DEBUG - insert phi node known_size.2 = phi(incoming_values=[], incoming_blocks=[]) at 18\n", - "2024-10-16 10:10:44,280 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:10:44,280 - numba.core.ssa - DEBUG - incoming_def known_size = const(int, 1)\n", - "2024-10-16 10:10:44,281 - numba.core.ssa - DEBUG - find_def_from_bottom label 161\n", - "2024-10-16 10:10:44,281 - numba.core.ssa - DEBUG - find_def_from_top label 161\n", - "2024-10-16 10:10:44,281 - numba.core.ssa - DEBUG - insert phi node known_size.3 = phi(incoming_values=[], incoming_blocks=[]) at 161\n", - "2024-10-16 10:10:44,282 - numba.core.ssa - DEBUG - find_def_from_bottom label 48\n", - "2024-10-16 10:10:44,282 - numba.core.ssa - DEBUG - incoming_def known_size.1 = $52inplace_multiply.3\n", - "2024-10-16 10:10:44,283 - numba.core.ssa - DEBUG - find_def_from_bottom label 34\n", - "2024-10-16 10:10:44,285 - numba.core.ssa - DEBUG - find_def_from_top label 34\n", - "2024-10-16 10:10:44,286 - numba.core.ssa - DEBUG - idom 20 from label 34\n", - "2024-10-16 10:10:44,286 - numba.core.ssa - DEBUG - find_def_from_bottom label 20\n", - "2024-10-16 10:10:44,287 - numba.core.ssa - DEBUG - find_def_from_top label 20\n", - "2024-10-16 10:10:44,287 - numba.core.ssa - DEBUG - idom 18 from label 20\n", - "2024-10-16 10:10:44,288 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,288 - numba.core.ssa - DEBUG - incoming_def known_size.2 = phi(incoming_values=[Var(known_size, arrayobj.py:2046)], incoming_blocks=[0])\n", - "2024-10-16 10:10:44,289 - numba.core.ssa - DEBUG - incoming_def known_size.3 = phi(incoming_values=[Var(known_size.1, arrayobj.py:2052), Var(known_size.2, arrayobj.py:2052)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,290 - numba.core.ssa - DEBUG - replaced with: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size.2, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,291 - numba.core.ssa - DEBUG - on stmt: known_size.1 = $52inplace_multiply.3\n", - "2024-10-16 10:10:44,291 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,291 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:44,292 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,292 - numba.core.ssa - DEBUG - on stmt: $const60.1 = const(int, 0)\n", - "2024-10-16 10:10:44,293 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = num_neg_value.2 == $const60.1\n", - "2024-10-16 10:10:44,293 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:44,294 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,295 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 86\n", - "2024-10-16 10:10:44,295 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:44,296 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,296 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = origsize != known_size\n", - "2024-10-16 10:10:44,297 - numba.core.ssa - DEBUG - find_def var='known_size' stmt=$70compare_op.2 = origsize != known_size\n", - "2024-10-16 10:10:44,299 - numba.core.ssa - DEBUG - find_def_from_top label 66\n", - "2024-10-16 10:10:44,299 - numba.core.ssa - DEBUG - idom 58 from label 66\n", - "2024-10-16 10:10:44,300 - numba.core.ssa - DEBUG - find_def_from_bottom label 58\n", - "2024-10-16 10:10:44,300 - numba.core.ssa - DEBUG - find_def_from_top label 58\n", - "2024-10-16 10:10:44,300 - numba.core.ssa - DEBUG - idom 18 from label 58\n", - "2024-10-16 10:10:44,301 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,301 - numba.core.ssa - DEBUG - replaced with: $70compare_op.2 = origsize != known_size.2\n", - "2024-10-16 10:10:44,302 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:44,302 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,303 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 82\n", - "2024-10-16 10:10:44,304 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:44,304 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,305 - numba.core.ssa - DEBUG - on stmt: $74load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,306 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,307 - numba.core.ssa - DEBUG - on stmt: $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,307 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,308 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 82\n", - "2024-10-16 10:10:44,309 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,309 - numba.core.ssa - DEBUG - on stmt: $const82.0 = const(NoneType, None)\n", - "2024-10-16 10:10:44,310 - numba.core.ssa - DEBUG - on stmt: $84return_value.1 = cast(value=$const82.0)\n", - "2024-10-16 10:10:44,310 - numba.core.ssa - DEBUG - on stmt: return $84return_value.1\n", - "2024-10-16 10:10:44,311 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:44,312 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,313 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:44,313 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = num_neg_value.2 == $const88.1\n", - "2024-10-16 10:10:44,314 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:44,315 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,315 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 160\n", - "2024-10-16 10:10:44,316 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:44,316 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,317 - numba.core.ssa - DEBUG - on stmt: $const96.1 = const(int, 0)\n", - "2024-10-16 10:10:44,318 - numba.core.ssa - DEBUG - on stmt: $98compare_op.2 = known_size == $const96.1\n", - "2024-10-16 10:10:44,318 - numba.core.ssa - DEBUG - find_def var='known_size' stmt=$98compare_op.2 = known_size == $const96.1\n", - "2024-10-16 10:10:44,319 - numba.core.ssa - DEBUG - find_def_from_top label 94\n", - "2024-10-16 10:10:44,320 - numba.core.ssa - DEBUG - idom 86 from label 94\n", - "2024-10-16 10:10:44,320 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-10-16 10:10:44,321 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-10-16 10:10:44,321 - numba.core.ssa - DEBUG - idom 58 from label 86\n", - "2024-10-16 10:10:44,322 - numba.core.ssa - DEBUG - find_def_from_bottom label 58\n", - "2024-10-16 10:10:44,323 - numba.core.ssa - DEBUG - find_def_from_top label 58\n", - "2024-10-16 10:10:44,323 - numba.core.ssa - DEBUG - idom 18 from label 58\n", - "2024-10-16 10:10:44,324 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,325 - numba.core.ssa - DEBUG - replaced with: $98compare_op.2 = known_size.2 == $const96.1\n", - "2024-10-16 10:10:44,325 - numba.core.ssa - DEBUG - on stmt: bool100 = global(bool: )\n", - "2024-10-16 10:10:44,326 - numba.core.ssa - DEBUG - on stmt: $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,326 - numba.core.ssa - DEBUG - on stmt: branch $100pred, 102, 116\n", - "2024-10-16 10:10:44,327 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:44,328 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,328 - numba.core.ssa - DEBUG - on stmt: inferred = const(int, 0)\n", - "2024-10-16 10:10:44,329 - numba.core.ssa - DEBUG - on stmt: $const108.2 = const(int, 0)\n", - "2024-10-16 10:10:44,330 - numba.core.ssa - DEBUG - on stmt: ok = origsize == $const108.2\n", - "2024-10-16 10:10:44,330 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,331 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 116\n", - "2024-10-16 10:10:44,331 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,332 - numba.core.ssa - DEBUG - on stmt: inferred = origsize // known_size\n", - "2024-10-16 10:10:44,333 - numba.core.ssa - DEBUG - find_def var='known_size' stmt=inferred = origsize // known_size\n", - "2024-10-16 10:10:44,333 - numba.core.ssa - DEBUG - find_def_from_top label 116\n", - "2024-10-16 10:10:44,334 - numba.core.ssa - DEBUG - idom 94 from label 116\n", - "2024-10-16 10:10:44,335 - numba.core.ssa - DEBUG - find_def_from_bottom label 94\n", - "2024-10-16 10:10:44,335 - numba.core.ssa - DEBUG - find_def_from_top label 94\n", - "2024-10-16 10:10:44,336 - numba.core.ssa - DEBUG - idom 86 from label 94\n", - "2024-10-16 10:10:44,337 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-10-16 10:10:44,337 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-10-16 10:10:44,338 - numba.core.ssa - DEBUG - idom 58 from label 86\n", - "2024-10-16 10:10:44,338 - numba.core.ssa - DEBUG - find_def_from_bottom label 58\n", - "2024-10-16 10:10:44,339 - numba.core.ssa - DEBUG - find_def_from_top label 58\n", - "2024-10-16 10:10:44,339 - numba.core.ssa - DEBUG - idom 18 from label 58\n", - "2024-10-16 10:10:44,340 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,341 - numba.core.ssa - DEBUG - replaced with: inferred = origsize // known_size.2\n", - "2024-10-16 10:10:44,342 - numba.core.ssa - DEBUG - on stmt: $128binary_modulo.5 = origsize % known_size\n", - "2024-10-16 10:10:44,342 - numba.core.ssa - DEBUG - find_def var='known_size' stmt=$128binary_modulo.5 = origsize % known_size\n", - "2024-10-16 10:10:44,343 - numba.core.ssa - DEBUG - find_def_from_top label 116\n", - "2024-10-16 10:10:44,343 - numba.core.ssa - DEBUG - idom 94 from label 116\n", - "2024-10-16 10:10:44,344 - numba.core.ssa - DEBUG - find_def_from_bottom label 94\n", - "2024-10-16 10:10:44,344 - numba.core.ssa - DEBUG - find_def_from_top label 94\n", - "2024-10-16 10:10:44,344 - numba.core.ssa - DEBUG - idom 86 from label 94\n", - "2024-10-16 10:10:44,345 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-10-16 10:10:44,345 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-10-16 10:10:44,347 - numba.core.ssa - DEBUG - idom 58 from label 86\n", - "2024-10-16 10:10:44,347 - numba.core.ssa - DEBUG - find_def_from_bottom label 58\n", - "2024-10-16 10:10:44,348 - numba.core.ssa - DEBUG - find_def_from_top label 58\n", - "2024-10-16 10:10:44,348 - numba.core.ssa - DEBUG - idom 18 from label 58\n", - "2024-10-16 10:10:44,349 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:44,349 - numba.core.ssa - DEBUG - replaced with: $128binary_modulo.5 = origsize % known_size.2\n", - "2024-10-16 10:10:44,350 - numba.core.ssa - DEBUG - on stmt: $const130.6 = const(int, 0)\n", - "2024-10-16 10:10:44,350 - numba.core.ssa - DEBUG - on stmt: ok = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:44,351 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,351 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-10-16 10:10:44,353 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,354 - numba.core.ssa - DEBUG - on stmt: bool138 = global(bool: )\n", - "2024-10-16 10:10:44,354 - numba.core.ssa - DEBUG - on stmt: $138pred = call bool138(ok, func=bool138, args=(Var(ok, arrayobj.py:2062),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,355 - numba.core.ssa - DEBUG - on stmt: branch $138pred, 148, 140\n", - "2024-10-16 10:10:44,355 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 140\n", - "2024-10-16 10:10:44,356 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,356 - numba.core.ssa - DEBUG - on stmt: $140load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,357 - numba.core.ssa - DEBUG - on stmt: $const142.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,358 - numba.core.ssa - DEBUG - on stmt: $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,358 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,359 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 148\n", - "2024-10-16 10:10:44,359 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,360 - numba.core.ssa - DEBUG - on stmt: shape[neg_ax] = inferred\n", - "2024-10-16 10:10:44,360 - numba.core.ssa - DEBUG - on stmt: $const156.3 = const(NoneType, None)\n", - "2024-10-16 10:10:44,362 - numba.core.ssa - DEBUG - on stmt: $158return_value.4 = cast(value=$const156.3)\n", - "2024-10-16 10:10:44,362 - numba.core.ssa - DEBUG - on stmt: return $158return_value.4\n", - "2024-10-16 10:10:44,363 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 160\n", - "2024-10-16 10:10:44,363 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,364 - numba.core.ssa - DEBUG - on stmt: $160load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,364 - numba.core.ssa - DEBUG - on stmt: $const162.1 = const(str, multiple negative shape values)\n", - "2024-10-16 10:10:44,364 - numba.core.ssa - DEBUG - on stmt: $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,365 - numba.core.ssa - DEBUG - on stmt: raise ('multiple negative shape values')\n", - "2024-10-16 10:10:44,365 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 161\n", - "2024-10-16 10:10:44,366 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,368 - numba.core.ssa - DEBUG - on stmt: num_neg_value.3 = phi(incoming_values=[Var(num_neg_value.2, arrayobj.py:2049), Var(num_neg_value.1, arrayobj.py:2049)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,368 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,369 - numba.core.ssa - DEBUG - Fix SSA violator on var ok\n", - "2024-10-16 10:10:44,369 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:44,370 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,370 - numba.core.ssa - DEBUG - on stmt: origsize = arg(0, name=origsize)\n", - "2024-10-16 10:10:44,371 - numba.core.ssa - DEBUG - on stmt: shape = arg(1, name=shape)\n", - "2024-10-16 10:10:44,372 - numba.core.ssa - DEBUG - on stmt: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:44,372 - numba.core.ssa - DEBUG - on stmt: known_size = const(int, 1)\n", - "2024-10-16 10:10:44,373 - numba.core.ssa - DEBUG - on stmt: $10load_global.2 = global(enumerate: )\n", - "2024-10-16 10:10:44,373 - numba.core.ssa - DEBUG - on stmt: $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,374 - numba.core.ssa - DEBUG - on stmt: $16get_iter.5 = getiter(value=$14call_function.4)\n", - "2024-10-16 10:10:44,374 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.5\n", - "2024-10-16 10:10:44,375 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,375 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:44,376 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,376 - numba.core.ssa - DEBUG - on stmt: known_size.2 = phi(incoming_values=[Var(known_size, arrayobj.py:2046), Var(known_size.3, arrayobj.py:2052)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,378 - numba.core.ssa - DEBUG - on stmt: num_neg_value.2 = phi(incoming_values=[Var(num_neg_value, arrayobj.py:2045), Var(num_neg_value.3, arrayobj.py:2049)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,379 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:44,379 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,380 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,380 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:44,381 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 58\n", - "2024-10-16 10:10:44,381 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 20\n", - "2024-10-16 10:10:44,382 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,383 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2)\n", - "2024-10-16 10:10:44,383 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=)\n", - "2024-10-16 10:10:44,384 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=)\n", - "2024-10-16 10:10:44,384 - numba.core.ssa - DEBUG - on stmt: ax = $20unpack_sequence.2\n", - "2024-10-16 10:10:44,385 - numba.core.ssa - DEBUG - on stmt: s = $20unpack_sequence.3\n", - "2024-10-16 10:10:44,385 - numba.core.ssa - DEBUG - on stmt: $const28.6 = const(int, 0)\n", - "2024-10-16 10:10:44,386 - numba.core.ssa - DEBUG - on stmt: $30compare_op.7 = s < $const28.6\n", - "2024-10-16 10:10:44,386 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:44,387 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,387 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 48\n", - "2024-10-16 10:10:44,388 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:44,388 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,389 - numba.core.ssa - DEBUG - on stmt: $const36.2 = const(int, 1)\n", - "2024-10-16 10:10:44,389 - numba.core.ssa - DEBUG - on stmt: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value.2, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,390 - numba.core.ssa - DEBUG - on stmt: num_neg_value.1 = $38inplace_add.3\n", - "2024-10-16 10:10:44,392 - numba.core.ssa - DEBUG - on stmt: neg_ax = ax\n", - "2024-10-16 10:10:44,392 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,393 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 48\n", - "2024-10-16 10:10:44,393 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,394 - numba.core.ssa - DEBUG - on stmt: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size.2, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,394 - numba.core.ssa - DEBUG - on stmt: known_size.1 = $52inplace_multiply.3\n", - "2024-10-16 10:10:44,395 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,395 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:44,396 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,396 - numba.core.ssa - DEBUG - on stmt: $const60.1 = const(int, 0)\n", - "2024-10-16 10:10:44,397 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = num_neg_value.2 == $const60.1\n", - "2024-10-16 10:10:44,397 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:44,398 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,398 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 86\n", - "2024-10-16 10:10:44,399 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:44,399 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,400 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = origsize != known_size.2\n", - "2024-10-16 10:10:44,400 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:44,403 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,403 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 82\n", - "2024-10-16 10:10:44,404 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:44,404 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,405 - numba.core.ssa - DEBUG - on stmt: $74load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,405 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,406 - numba.core.ssa - DEBUG - on stmt: $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,407 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,407 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 82\n", - "2024-10-16 10:10:44,408 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,408 - numba.core.ssa - DEBUG - on stmt: $const82.0 = const(NoneType, None)\n", - "2024-10-16 10:10:44,409 - numba.core.ssa - DEBUG - on stmt: $84return_value.1 = cast(value=$const82.0)\n", - "2024-10-16 10:10:44,409 - numba.core.ssa - DEBUG - on stmt: return $84return_value.1\n", - "2024-10-16 10:10:44,410 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:44,410 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,412 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:44,412 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = num_neg_value.2 == $const88.1\n", - "2024-10-16 10:10:44,413 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:44,413 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,414 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 160\n", - "2024-10-16 10:10:44,414 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:44,415 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,415 - numba.core.ssa - DEBUG - on stmt: $const96.1 = const(int, 0)\n", - "2024-10-16 10:10:44,416 - numba.core.ssa - DEBUG - on stmt: $98compare_op.2 = known_size.2 == $const96.1\n", - "2024-10-16 10:10:44,416 - numba.core.ssa - DEBUG - on stmt: bool100 = global(bool: )\n", - "2024-10-16 10:10:44,417 - numba.core.ssa - DEBUG - on stmt: $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,417 - numba.core.ssa - DEBUG - on stmt: branch $100pred, 102, 116\n", - "2024-10-16 10:10:44,418 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:44,419 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,420 - numba.core.ssa - DEBUG - on stmt: inferred = const(int, 0)\n", - "2024-10-16 10:10:44,420 - numba.core.ssa - DEBUG - on stmt: $const108.2 = const(int, 0)\n", - "2024-10-16 10:10:44,421 - numba.core.ssa - DEBUG - on stmt: ok = origsize == $const108.2\n", - "2024-10-16 10:10:44,421 - numba.core.ssa - DEBUG - first assign: ok\n", - "2024-10-16 10:10:44,422 - numba.core.ssa - DEBUG - replaced with: ok = origsize == $const108.2\n", - "2024-10-16 10:10:44,423 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,423 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 116\n", - "2024-10-16 10:10:44,424 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,425 - numba.core.ssa - DEBUG - on stmt: inferred = origsize // known_size.2\n", - "2024-10-16 10:10:44,425 - numba.core.ssa - DEBUG - on stmt: $128binary_modulo.5 = origsize % known_size.2\n", - "2024-10-16 10:10:44,426 - numba.core.ssa - DEBUG - on stmt: $const130.6 = const(int, 0)\n", - "2024-10-16 10:10:44,426 - numba.core.ssa - DEBUG - on stmt: ok = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:44,427 - numba.core.ssa - DEBUG - replaced with: ok.1 = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:44,428 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,428 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-10-16 10:10:44,429 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,429 - numba.core.ssa - DEBUG - on stmt: bool138 = global(bool: )\n", - "2024-10-16 10:10:44,430 - numba.core.ssa - DEBUG - on stmt: $138pred = call bool138(ok, func=bool138, args=(Var(ok, arrayobj.py:2062),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,430 - numba.core.ssa - DEBUG - on stmt: branch $138pred, 148, 140\n", - "2024-10-16 10:10:44,431 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 140\n", - "2024-10-16 10:10:44,431 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,432 - numba.core.ssa - DEBUG - on stmt: $140load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,433 - numba.core.ssa - DEBUG - on stmt: $const142.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,434 - numba.core.ssa - DEBUG - on stmt: $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,434 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,435 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 148\n", - "2024-10-16 10:10:44,436 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,436 - numba.core.ssa - DEBUG - on stmt: shape[neg_ax] = inferred\n", - "2024-10-16 10:10:44,437 - numba.core.ssa - DEBUG - on stmt: $const156.3 = const(NoneType, None)\n", - "2024-10-16 10:10:44,438 - numba.core.ssa - DEBUG - on stmt: $158return_value.4 = cast(value=$const156.3)\n", - "2024-10-16 10:10:44,438 - numba.core.ssa - DEBUG - on stmt: return $158return_value.4\n", - "2024-10-16 10:10:44,439 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 160\n", - "2024-10-16 10:10:44,439 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,440 - numba.core.ssa - DEBUG - on stmt: $160load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,440 - numba.core.ssa - DEBUG - on stmt: $const162.1 = const(str, multiple negative shape values)\n", - "2024-10-16 10:10:44,441 - numba.core.ssa - DEBUG - on stmt: $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,441 - numba.core.ssa - DEBUG - on stmt: raise ('multiple negative shape values')\n", - "2024-10-16 10:10:44,442 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 161\n", - "2024-10-16 10:10:44,442 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,443 - numba.core.ssa - DEBUG - on stmt: known_size.3 = phi(incoming_values=[Var(known_size.1, arrayobj.py:2052), Var(known_size.2, arrayobj.py:2052)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,443 - numba.core.ssa - DEBUG - on stmt: num_neg_value.3 = phi(incoming_values=[Var(num_neg_value.2, arrayobj.py:2049), Var(num_neg_value.1, arrayobj.py:2049)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,444 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,444 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {102: [],\n", - " 116: []})\n", - "2024-10-16 10:10:44,445 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:44,447 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,447 - numba.core.ssa - DEBUG - on stmt: origsize = arg(0, name=origsize)\n", - "2024-10-16 10:10:44,447 - numba.core.ssa - DEBUG - on stmt: shape = arg(1, name=shape)\n", - "2024-10-16 10:10:44,448 - numba.core.ssa - DEBUG - on stmt: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:44,448 - numba.core.ssa - DEBUG - on stmt: known_size = const(int, 1)\n", - "2024-10-16 10:10:44,449 - numba.core.ssa - DEBUG - on stmt: $10load_global.2 = global(enumerate: )\n", - "2024-10-16 10:10:44,449 - numba.core.ssa - DEBUG - on stmt: $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,450 - numba.core.ssa - DEBUG - on stmt: $16get_iter.5 = getiter(value=$14call_function.4)\n", - "2024-10-16 10:10:44,450 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.5\n", - "2024-10-16 10:10:44,451 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,451 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:44,452 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,454 - numba.core.ssa - DEBUG - on stmt: known_size.2 = phi(incoming_values=[Var(known_size, arrayobj.py:2046), Var(known_size.3, arrayobj.py:2052)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,454 - numba.core.ssa - DEBUG - on stmt: num_neg_value.2 = phi(incoming_values=[Var(num_neg_value, arrayobj.py:2045), Var(num_neg_value.3, arrayobj.py:2049)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,455 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:44,455 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,456 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,456 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:44,457 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 58\n", - "2024-10-16 10:10:44,458 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 20\n", - "2024-10-16 10:10:44,458 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,459 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2)\n", - "2024-10-16 10:10:44,460 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=)\n", - "2024-10-16 10:10:44,460 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=)\n", - "2024-10-16 10:10:44,461 - numba.core.ssa - DEBUG - on stmt: ax = $20unpack_sequence.2\n", - "2024-10-16 10:10:44,461 - numba.core.ssa - DEBUG - on stmt: s = $20unpack_sequence.3\n", - "2024-10-16 10:10:44,462 - numba.core.ssa - DEBUG - on stmt: $const28.6 = const(int, 0)\n", - "2024-10-16 10:10:44,463 - numba.core.ssa - DEBUG - on stmt: $30compare_op.7 = s < $const28.6\n", - "2024-10-16 10:10:44,464 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:44,464 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,465 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 48\n", - "2024-10-16 10:10:44,466 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:44,466 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,467 - numba.core.ssa - DEBUG - on stmt: $const36.2 = const(int, 1)\n", - "2024-10-16 10:10:44,468 - numba.core.ssa - DEBUG - on stmt: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value.2, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,468 - numba.core.ssa - DEBUG - on stmt: num_neg_value.1 = $38inplace_add.3\n", - "2024-10-16 10:10:44,468 - numba.core.ssa - DEBUG - on stmt: neg_ax = ax\n", - "2024-10-16 10:10:44,469 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,469 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 48\n", - "2024-10-16 10:10:44,470 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,470 - numba.core.ssa - DEBUG - on stmt: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size.2, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,471 - numba.core.ssa - DEBUG - on stmt: known_size.1 = $52inplace_multiply.3\n", - "2024-10-16 10:10:44,471 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,472 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:44,472 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,473 - numba.core.ssa - DEBUG - on stmt: $const60.1 = const(int, 0)\n", - "2024-10-16 10:10:44,473 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = num_neg_value.2 == $const60.1\n", - "2024-10-16 10:10:44,474 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:44,474 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,477 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 86\n", - "2024-10-16 10:10:44,477 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:44,478 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,478 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = origsize != known_size.2\n", - "2024-10-16 10:10:44,479 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:44,480 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,481 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 82\n", - "2024-10-16 10:10:44,481 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:44,482 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,482 - numba.core.ssa - DEBUG - on stmt: $74load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,483 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,484 - numba.core.ssa - DEBUG - on stmt: $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,484 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,485 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 82\n", - "2024-10-16 10:10:44,485 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,486 - numba.core.ssa - DEBUG - on stmt: $const82.0 = const(NoneType, None)\n", - "2024-10-16 10:10:44,486 - numba.core.ssa - DEBUG - on stmt: $84return_value.1 = cast(value=$const82.0)\n", - "2024-10-16 10:10:44,488 - numba.core.ssa - DEBUG - on stmt: return $84return_value.1\n", - "2024-10-16 10:10:44,488 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:44,489 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,489 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:44,490 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = num_neg_value.2 == $const88.1\n", - "2024-10-16 10:10:44,490 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:44,491 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,492 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 160\n", - "2024-10-16 10:10:44,493 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:44,493 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,494 - numba.core.ssa - DEBUG - on stmt: $const96.1 = const(int, 0)\n", - "2024-10-16 10:10:44,494 - numba.core.ssa - DEBUG - on stmt: $98compare_op.2 = known_size.2 == $const96.1\n", - "2024-10-16 10:10:44,495 - numba.core.ssa - DEBUG - on stmt: bool100 = global(bool: )\n", - "2024-10-16 10:10:44,496 - numba.core.ssa - DEBUG - on stmt: $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,496 - numba.core.ssa - DEBUG - on stmt: branch $100pred, 102, 116\n", - "2024-10-16 10:10:44,497 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:44,498 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,498 - numba.core.ssa - DEBUG - on stmt: inferred = const(int, 0)\n", - "2024-10-16 10:10:44,499 - numba.core.ssa - DEBUG - on stmt: $const108.2 = const(int, 0)\n", - "2024-10-16 10:10:44,499 - numba.core.ssa - DEBUG - on stmt: ok = origsize == $const108.2\n", - "2024-10-16 10:10:44,500 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,500 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 116\n", - "2024-10-16 10:10:44,501 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,502 - numba.core.ssa - DEBUG - on stmt: inferred = origsize // known_size.2\n", - "2024-10-16 10:10:44,503 - numba.core.ssa - DEBUG - on stmt: $128binary_modulo.5 = origsize % known_size.2\n", - "2024-10-16 10:10:44,503 - numba.core.ssa - DEBUG - on stmt: $const130.6 = const(int, 0)\n", - "2024-10-16 10:10:44,504 - numba.core.ssa - DEBUG - on stmt: ok.1 = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:44,504 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,505 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-10-16 10:10:44,505 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,506 - numba.core.ssa - DEBUG - on stmt: bool138 = global(bool: )\n", - "2024-10-16 10:10:44,507 - numba.core.ssa - DEBUG - on stmt: $138pred = call bool138(ok, func=bool138, args=(Var(ok, arrayobj.py:2062),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,507 - numba.core.ssa - DEBUG - find_def var='ok' stmt=$138pred = call bool138(ok, func=bool138, args=(Var(ok, arrayobj.py:2062),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,508 - numba.core.ssa - DEBUG - find_def_from_top label 136\n", - "2024-10-16 10:10:44,508 - numba.core.ssa - DEBUG - insert phi node ok.2 = phi(incoming_values=[], incoming_blocks=[]) at 136\n", - "2024-10-16 10:10:44,509 - numba.core.ssa - DEBUG - find_def_from_bottom label 116\n", - "2024-10-16 10:10:44,509 - numba.core.ssa - DEBUG - incoming_def ok.1 = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:44,511 - numba.core.ssa - DEBUG - find_def_from_bottom label 102\n", - "2024-10-16 10:10:44,511 - numba.core.ssa - DEBUG - incoming_def ok = origsize == $const108.2\n", - "2024-10-16 10:10:44,512 - numba.core.ssa - DEBUG - replaced with: $138pred = call bool138(ok.2, func=bool138, args=(Var(ok.2, arrayobj.py:2066),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,512 - numba.core.ssa - DEBUG - on stmt: branch $138pred, 148, 140\n", - "2024-10-16 10:10:44,513 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 140\n", - "2024-10-16 10:10:44,513 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,514 - numba.core.ssa - DEBUG - on stmt: $140load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,514 - numba.core.ssa - DEBUG - on stmt: $const142.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,515 - numba.core.ssa - DEBUG - on stmt: $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,515 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,517 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 148\n", - "2024-10-16 10:10:44,518 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,518 - numba.core.ssa - DEBUG - on stmt: shape[neg_ax] = inferred\n", - "2024-10-16 10:10:44,518 - numba.core.ssa - DEBUG - on stmt: $const156.3 = const(NoneType, None)\n", - "2024-10-16 10:10:44,519 - numba.core.ssa - DEBUG - on stmt: $158return_value.4 = cast(value=$const156.3)\n", - "2024-10-16 10:10:44,519 - numba.core.ssa - DEBUG - on stmt: return $158return_value.4\n", - "2024-10-16 10:10:44,520 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 160\n", - "2024-10-16 10:10:44,521 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,522 - numba.core.ssa - DEBUG - on stmt: $160load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,522 - numba.core.ssa - DEBUG - on stmt: $const162.1 = const(str, multiple negative shape values)\n", - "2024-10-16 10:10:44,523 - numba.core.ssa - DEBUG - on stmt: $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,523 - numba.core.ssa - DEBUG - on stmt: raise ('multiple negative shape values')\n", - "2024-10-16 10:10:44,524 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 161\n", - "2024-10-16 10:10:44,524 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,526 - numba.core.ssa - DEBUG - on stmt: known_size.3 = phi(incoming_values=[Var(known_size.1, arrayobj.py:2052), Var(known_size.2, arrayobj.py:2052)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,526 - numba.core.ssa - DEBUG - on stmt: num_neg_value.3 = phi(incoming_values=[Var(num_neg_value.2, arrayobj.py:2049), Var(num_neg_value.1, arrayobj.py:2049)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,527 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,527 - numba.core.ssa - DEBUG - Fix SSA violator on var inferred\n", - "2024-10-16 10:10:44,528 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:44,529 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,529 - numba.core.ssa - DEBUG - on stmt: origsize = arg(0, name=origsize)\n", - "2024-10-16 10:10:44,530 - numba.core.ssa - DEBUG - on stmt: shape = arg(1, name=shape)\n", - "2024-10-16 10:10:44,530 - numba.core.ssa - DEBUG - on stmt: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:44,531 - numba.core.ssa - DEBUG - on stmt: known_size = const(int, 1)\n", - "2024-10-16 10:10:44,531 - numba.core.ssa - DEBUG - on stmt: $10load_global.2 = global(enumerate: )\n", - "2024-10-16 10:10:44,532 - numba.core.ssa - DEBUG - on stmt: $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,533 - numba.core.ssa - DEBUG - on stmt: $16get_iter.5 = getiter(value=$14call_function.4)\n", - "2024-10-16 10:10:44,534 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.5\n", - "2024-10-16 10:10:44,534 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,534 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:44,535 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,535 - numba.core.ssa - DEBUG - on stmt: known_size.2 = phi(incoming_values=[Var(known_size, arrayobj.py:2046), Var(known_size.3, arrayobj.py:2052)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,536 - numba.core.ssa - DEBUG - on stmt: num_neg_value.2 = phi(incoming_values=[Var(num_neg_value, arrayobj.py:2045), Var(num_neg_value.3, arrayobj.py:2049)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,536 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:44,537 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,537 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,538 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:44,538 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 58\n", - "2024-10-16 10:10:44,539 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 20\n", - "2024-10-16 10:10:44,539 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,540 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2)\n", - "2024-10-16 10:10:44,540 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=)\n", - "2024-10-16 10:10:44,541 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=)\n", - "2024-10-16 10:10:44,541 - numba.core.ssa - DEBUG - on stmt: ax = $20unpack_sequence.2\n", - "2024-10-16 10:10:44,542 - numba.core.ssa - DEBUG - on stmt: s = $20unpack_sequence.3\n", - "2024-10-16 10:10:44,544 - numba.core.ssa - DEBUG - on stmt: $const28.6 = const(int, 0)\n", - "2024-10-16 10:10:44,545 - numba.core.ssa - DEBUG - on stmt: $30compare_op.7 = s < $const28.6\n", - "2024-10-16 10:10:44,545 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:44,546 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,546 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 48\n", - "2024-10-16 10:10:44,547 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:44,547 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,549 - numba.core.ssa - DEBUG - on stmt: $const36.2 = const(int, 1)\n", - "2024-10-16 10:10:44,549 - numba.core.ssa - DEBUG - on stmt: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value.2, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,550 - numba.core.ssa - DEBUG - on stmt: num_neg_value.1 = $38inplace_add.3\n", - "2024-10-16 10:10:44,550 - numba.core.ssa - DEBUG - on stmt: neg_ax = ax\n", - "2024-10-16 10:10:44,551 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,551 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 48\n", - "2024-10-16 10:10:44,552 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,552 - numba.core.ssa - DEBUG - on stmt: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size.2, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,553 - numba.core.ssa - DEBUG - on stmt: known_size.1 = $52inplace_multiply.3\n", - "2024-10-16 10:10:44,553 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,555 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:44,555 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,556 - numba.core.ssa - DEBUG - on stmt: $const60.1 = const(int, 0)\n", - "2024-10-16 10:10:44,556 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = num_neg_value.2 == $const60.1\n", - "2024-10-16 10:10:44,557 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:44,557 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,558 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 86\n", - "2024-10-16 10:10:44,559 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:44,560 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,560 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = origsize != known_size.2\n", - "2024-10-16 10:10:44,560 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:44,561 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,561 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 82\n", - "2024-10-16 10:10:44,562 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:44,562 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,563 - numba.core.ssa - DEBUG - on stmt: $74load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,563 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,564 - numba.core.ssa - DEBUG - on stmt: $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,564 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,565 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 82\n", - "2024-10-16 10:10:44,567 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,567 - numba.core.ssa - DEBUG - on stmt: $const82.0 = const(NoneType, None)\n", - "2024-10-16 10:10:44,568 - numba.core.ssa - DEBUG - on stmt: $84return_value.1 = cast(value=$const82.0)\n", - "2024-10-16 10:10:44,568 - numba.core.ssa - DEBUG - on stmt: return $84return_value.1\n", - "2024-10-16 10:10:44,569 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:44,570 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,570 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:44,571 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = num_neg_value.2 == $const88.1\n", - "2024-10-16 10:10:44,571 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:44,572 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,572 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 160\n", - "2024-10-16 10:10:44,573 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:44,573 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,574 - numba.core.ssa - DEBUG - on stmt: $const96.1 = const(int, 0)\n", - "2024-10-16 10:10:44,574 - numba.core.ssa - DEBUG - on stmt: $98compare_op.2 = known_size.2 == $const96.1\n", - "2024-10-16 10:10:44,575 - numba.core.ssa - DEBUG - on stmt: bool100 = global(bool: )\n", - "2024-10-16 10:10:44,575 - numba.core.ssa - DEBUG - on stmt: $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,576 - numba.core.ssa - DEBUG - on stmt: branch $100pred, 102, 116\n", - "2024-10-16 10:10:44,576 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:44,577 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,577 - numba.core.ssa - DEBUG - on stmt: inferred = const(int, 0)\n", - "2024-10-16 10:10:44,578 - numba.core.ssa - DEBUG - first assign: inferred\n", - "2024-10-16 10:10:44,578 - numba.core.ssa - DEBUG - replaced with: inferred = const(int, 0)\n", - "2024-10-16 10:10:44,579 - numba.core.ssa - DEBUG - on stmt: $const108.2 = const(int, 0)\n", - "2024-10-16 10:10:44,581 - numba.core.ssa - DEBUG - on stmt: ok = origsize == $const108.2\n", - "2024-10-16 10:10:44,582 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,582 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 116\n", - "2024-10-16 10:10:44,583 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,583 - numba.core.ssa - DEBUG - on stmt: inferred = origsize // known_size.2\n", - "2024-10-16 10:10:44,584 - numba.core.ssa - DEBUG - replaced with: inferred.1 = origsize // known_size.2\n", - "2024-10-16 10:10:44,584 - numba.core.ssa - DEBUG - on stmt: $128binary_modulo.5 = origsize % known_size.2\n", - "2024-10-16 10:10:44,586 - numba.core.ssa - DEBUG - on stmt: $const130.6 = const(int, 0)\n", - "2024-10-16 10:10:44,586 - numba.core.ssa - DEBUG - on stmt: ok.1 = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:44,587 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,587 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-10-16 10:10:44,588 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,588 - numba.core.ssa - DEBUG - on stmt: ok.2 = phi(incoming_values=[Var(ok.1, arrayobj.py:2065), Var(ok, arrayobj.py:2062)], incoming_blocks=[116, 102])\n", - "2024-10-16 10:10:44,588 - numba.core.ssa - DEBUG - on stmt: bool138 = global(bool: )\n", - "2024-10-16 10:10:44,589 - numba.core.ssa - DEBUG - on stmt: $138pred = call bool138(ok.2, func=bool138, args=(Var(ok.2, arrayobj.py:2066),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,589 - numba.core.ssa - DEBUG - on stmt: branch $138pred, 148, 140\n", - "2024-10-16 10:10:44,590 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 140\n", - "2024-10-16 10:10:44,590 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,591 - numba.core.ssa - DEBUG - on stmt: $140load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,591 - numba.core.ssa - DEBUG - on stmt: $const142.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,593 - numba.core.ssa - DEBUG - on stmt: $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,594 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,595 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 148\n", - "2024-10-16 10:10:44,595 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,596 - numba.core.ssa - DEBUG - on stmt: shape[neg_ax] = inferred\n", - "2024-10-16 10:10:44,596 - numba.core.ssa - DEBUG - on stmt: $const156.3 = const(NoneType, None)\n", - "2024-10-16 10:10:44,596 - numba.core.ssa - DEBUG - on stmt: $158return_value.4 = cast(value=$const156.3)\n", - "2024-10-16 10:10:44,598 - numba.core.ssa - DEBUG - on stmt: return $158return_value.4\n", - "2024-10-16 10:10:44,598 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 160\n", - "2024-10-16 10:10:44,599 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,599 - numba.core.ssa - DEBUG - on stmt: $160load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,600 - numba.core.ssa - DEBUG - on stmt: $const162.1 = const(str, multiple negative shape values)\n", - "2024-10-16 10:10:44,600 - numba.core.ssa - DEBUG - on stmt: $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,601 - numba.core.ssa - DEBUG - on stmt: raise ('multiple negative shape values')\n", - "2024-10-16 10:10:44,601 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 161\n", - "2024-10-16 10:10:44,602 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,602 - numba.core.ssa - DEBUG - on stmt: known_size.3 = phi(incoming_values=[Var(known_size.1, arrayobj.py:2052), Var(known_size.2, arrayobj.py:2052)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,604 - numba.core.ssa - DEBUG - on stmt: num_neg_value.3 = phi(incoming_values=[Var(num_neg_value.2, arrayobj.py:2049), Var(num_neg_value.1, arrayobj.py:2049)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,604 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,605 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {102: [],\n", - " 116: []})\n", - "2024-10-16 10:10:44,605 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:44,606 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,606 - numba.core.ssa - DEBUG - on stmt: origsize = arg(0, name=origsize)\n", - "2024-10-16 10:10:44,608 - numba.core.ssa - DEBUG - on stmt: shape = arg(1, name=shape)\n", - "2024-10-16 10:10:44,608 - numba.core.ssa - DEBUG - on stmt: num_neg_value = const(int, 0)\n", - "2024-10-16 10:10:44,609 - numba.core.ssa - DEBUG - on stmt: known_size = const(int, 1)\n", - "2024-10-16 10:10:44,609 - numba.core.ssa - DEBUG - on stmt: $10load_global.2 = global(enumerate: )\n", - "2024-10-16 10:10:44,610 - numba.core.ssa - DEBUG - on stmt: $14call_function.4 = call $10load_global.2(shape, func=$10load_global.2, args=[Var(shape, arrayobj.py:2044)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,610 - numba.core.ssa - DEBUG - on stmt: $16get_iter.5 = getiter(value=$14call_function.4)\n", - "2024-10-16 10:10:44,611 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.5\n", - "2024-10-16 10:10:44,611 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,612 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:44,612 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,613 - numba.core.ssa - DEBUG - on stmt: known_size.2 = phi(incoming_values=[Var(known_size, arrayobj.py:2046), Var(known_size.3, arrayobj.py:2052)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,613 - numba.core.ssa - DEBUG - on stmt: num_neg_value.2 = phi(incoming_values=[Var(num_neg_value, arrayobj.py:2045), Var(num_neg_value.3, arrayobj.py:2049)], incoming_blocks=[0, 161])\n", - "2024-10-16 10:10:44,615 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:44,615 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,616 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:44,616 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:44,617 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 58\n", - "2024-10-16 10:10:44,618 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 20\n", - "2024-10-16 10:10:44,618 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,619 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.4 = exhaust_iter(value=$phi20.1, count=2)\n", - "2024-10-16 10:10:44,620 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.2 = static_getitem(value=$20unpack_sequence.4, index=0, index_var=None, fn=)\n", - "2024-10-16 10:10:44,620 - numba.core.ssa - DEBUG - on stmt: $20unpack_sequence.3 = static_getitem(value=$20unpack_sequence.4, index=1, index_var=None, fn=)\n", - "2024-10-16 10:10:44,621 - numba.core.ssa - DEBUG - on stmt: ax = $20unpack_sequence.2\n", - "2024-10-16 10:10:44,621 - numba.core.ssa - DEBUG - on stmt: s = $20unpack_sequence.3\n", - "2024-10-16 10:10:44,622 - numba.core.ssa - DEBUG - on stmt: $const28.6 = const(int, 0)\n", - "2024-10-16 10:10:44,622 - numba.core.ssa - DEBUG - on stmt: $30compare_op.7 = s < $const28.6\n", - "2024-10-16 10:10:44,623 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:44,623 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.7, func=bool32, args=(Var($30compare_op.7, arrayobj.py:2048),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,624 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 48\n", - "2024-10-16 10:10:44,625 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:44,626 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,626 - numba.core.ssa - DEBUG - on stmt: $const36.2 = const(int, 1)\n", - "2024-10-16 10:10:44,627 - numba.core.ssa - DEBUG - on stmt: $38inplace_add.3 = inplace_binop(fn=, immutable_fn=, lhs=num_neg_value.2, rhs=$const36.2, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,628 - numba.core.ssa - DEBUG - on stmt: num_neg_value.1 = $38inplace_add.3\n", - "2024-10-16 10:10:44,628 - numba.core.ssa - DEBUG - on stmt: neg_ax = ax\n", - "2024-10-16 10:10:44,629 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,629 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 48\n", - "2024-10-16 10:10:44,630 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,630 - numba.core.ssa - DEBUG - on stmt: $52inplace_multiply.3 = inplace_binop(fn=, immutable_fn=, lhs=known_size.2, rhs=s, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:44,631 - numba.core.ssa - DEBUG - on stmt: known_size.1 = $52inplace_multiply.3\n", - "2024-10-16 10:10:44,631 - numba.core.ssa - DEBUG - on stmt: jump 161\n", - "2024-10-16 10:10:44,632 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:44,632 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,633 - numba.core.ssa - DEBUG - on stmt: $const60.1 = const(int, 0)\n", - "2024-10-16 10:10:44,633 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = num_neg_value.2 == $const60.1\n", - "2024-10-16 10:10:44,634 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:44,634 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, arrayobj.py:2054),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,635 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 86\n", - "2024-10-16 10:10:44,635 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:44,636 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,638 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = origsize != known_size.2\n", - "2024-10-16 10:10:44,639 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:44,639 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, arrayobj.py:2055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,639 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 82\n", - "2024-10-16 10:10:44,640 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:44,640 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,641 - numba.core.ssa - DEBUG - on stmt: $74load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,641 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,642 - numba.core.ssa - DEBUG - on stmt: $78call_function.2 = call $74load_global.0($const76.1, func=$74load_global.0, args=[Var($const76.1, arrayobj.py:2056)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,643 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,643 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 82\n", - "2024-10-16 10:10:44,644 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,644 - numba.core.ssa - DEBUG - on stmt: $const82.0 = const(NoneType, None)\n", - "2024-10-16 10:10:44,644 - numba.core.ssa - DEBUG - on stmt: $84return_value.1 = cast(value=$const82.0)\n", - "2024-10-16 10:10:44,645 - numba.core.ssa - DEBUG - on stmt: return $84return_value.1\n", - "2024-10-16 10:10:44,645 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:44,648 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,648 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:44,649 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = num_neg_value.2 == $const88.1\n", - "2024-10-16 10:10:44,649 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:44,650 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, arrayobj.py:2058),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,651 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 160\n", - "2024-10-16 10:10:44,651 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:44,652 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,653 - numba.core.ssa - DEBUG - on stmt: $const96.1 = const(int, 0)\n", - "2024-10-16 10:10:44,653 - numba.core.ssa - DEBUG - on stmt: $98compare_op.2 = known_size.2 == $const96.1\n", - "2024-10-16 10:10:44,654 - numba.core.ssa - DEBUG - on stmt: bool100 = global(bool: )\n", - "2024-10-16 10:10:44,654 - numba.core.ssa - DEBUG - on stmt: $100pred = call bool100($98compare_op.2, func=bool100, args=(Var($98compare_op.2, arrayobj.py:2060),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,655 - numba.core.ssa - DEBUG - on stmt: branch $100pred, 102, 116\n", - "2024-10-16 10:10:44,655 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:44,656 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,656 - numba.core.ssa - DEBUG - on stmt: inferred = const(int, 0)\n", - "2024-10-16 10:10:44,657 - numba.core.ssa - DEBUG - on stmt: $const108.2 = const(int, 0)\n", - "2024-10-16 10:10:44,657 - numba.core.ssa - DEBUG - on stmt: ok = origsize == $const108.2\n", - "2024-10-16 10:10:44,658 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,658 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 116\n", - "2024-10-16 10:10:44,659 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,659 - numba.core.ssa - DEBUG - on stmt: inferred.1 = origsize // known_size.2\n", - "2024-10-16 10:10:44,660 - numba.core.ssa - DEBUG - on stmt: $128binary_modulo.5 = origsize % known_size.2\n", - "2024-10-16 10:10:44,662 - numba.core.ssa - DEBUG - on stmt: $const130.6 = const(int, 0)\n", - "2024-10-16 10:10:44,662 - numba.core.ssa - DEBUG - on stmt: ok.1 = $128binary_modulo.5 == $const130.6\n", - "2024-10-16 10:10:44,663 - numba.core.ssa - DEBUG - on stmt: jump 136\n", - "2024-10-16 10:10:44,663 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-10-16 10:10:44,664 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,664 - numba.core.ssa - DEBUG - on stmt: ok.2 = phi(incoming_values=[Var(ok.1, arrayobj.py:2065), Var(ok, arrayobj.py:2062)], incoming_blocks=[116, 102])\n", - "2024-10-16 10:10:44,665 - numba.core.ssa - DEBUG - on stmt: bool138 = global(bool: )\n", - "2024-10-16 10:10:44,665 - numba.core.ssa - DEBUG - on stmt: $138pred = call bool138(ok.2, func=bool138, args=(Var(ok.2, arrayobj.py:2066),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,666 - numba.core.ssa - DEBUG - on stmt: branch $138pred, 148, 140\n", - "2024-10-16 10:10:44,666 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 140\n", - "2024-10-16 10:10:44,668 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,669 - numba.core.ssa - DEBUG - on stmt: $140load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,669 - numba.core.ssa - DEBUG - on stmt: $const142.1 = const(str, total size of new array must be unchanged)\n", - "2024-10-16 10:10:44,669 - numba.core.ssa - DEBUG - on stmt: $144call_function.2 = call $140load_global.0($const142.1, func=$140load_global.0, args=[Var($const142.1, arrayobj.py:2067)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,670 - numba.core.ssa - DEBUG - on stmt: raise ('total size of new array must be unchanged')\n", - "2024-10-16 10:10:44,670 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 148\n", - "2024-10-16 10:10:44,671 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,672 - numba.core.ssa - DEBUG - on stmt: shape[neg_ax] = inferred\n", - "2024-10-16 10:10:44,673 - numba.core.ssa - DEBUG - find_def var='inferred' stmt=shape[neg_ax] = inferred\n", - "2024-10-16 10:10:44,673 - numba.core.ssa - DEBUG - find_def_from_top label 148\n", - "2024-10-16 10:10:44,674 - numba.core.ssa - DEBUG - idom 136 from label 148\n", - "2024-10-16 10:10:44,674 - numba.core.ssa - DEBUG - find_def_from_bottom label 136\n", - "2024-10-16 10:10:44,675 - numba.core.ssa - DEBUG - find_def_from_top label 136\n", - "2024-10-16 10:10:44,675 - numba.core.ssa - DEBUG - insert phi node inferred.2 = phi(incoming_values=[], incoming_blocks=[]) at 136\n", - "2024-10-16 10:10:44,676 - numba.core.ssa - DEBUG - find_def_from_bottom label 116\n", - "2024-10-16 10:10:44,677 - numba.core.ssa - DEBUG - incoming_def inferred.1 = origsize // known_size.2\n", - "2024-10-16 10:10:44,678 - numba.core.ssa - DEBUG - find_def_from_bottom label 102\n", - "2024-10-16 10:10:44,678 - numba.core.ssa - DEBUG - incoming_def inferred = const(int, 0)\n", - "2024-10-16 10:10:44,679 - numba.core.ssa - DEBUG - replaced with: shape[neg_ax] = inferred.2\n", - "2024-10-16 10:10:44,680 - numba.core.ssa - DEBUG - on stmt: $const156.3 = const(NoneType, None)\n", - "2024-10-16 10:10:44,680 - numba.core.ssa - DEBUG - on stmt: $158return_value.4 = cast(value=$const156.3)\n", - "2024-10-16 10:10:44,681 - numba.core.ssa - DEBUG - on stmt: return $158return_value.4\n", - "2024-10-16 10:10:44,682 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 160\n", - "2024-10-16 10:10:44,682 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,683 - numba.core.ssa - DEBUG - on stmt: $160load_global.0 = global(ValueError: )\n", - "2024-10-16 10:10:44,683 - numba.core.ssa - DEBUG - on stmt: $const162.1 = const(str, multiple negative shape values)\n", - "2024-10-16 10:10:44,684 - numba.core.ssa - DEBUG - on stmt: $164call_function.2 = call $160load_global.0($const162.1, func=$160load_global.0, args=[Var($const162.1, arrayobj.py:2071)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,685 - numba.core.ssa - DEBUG - on stmt: raise ('multiple negative shape values')\n", - "2024-10-16 10:10:44,685 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 161\n", - "2024-10-16 10:10:44,686 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,687 - numba.core.ssa - DEBUG - on stmt: known_size.3 = phi(incoming_values=[Var(known_size.1, arrayobj.py:2052), Var(known_size.2, arrayobj.py:2052)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,687 - numba.core.ssa - DEBUG - on stmt: num_neg_value.3 = phi(incoming_values=[Var(num_neg_value.2, arrayobj.py:2049), Var(num_neg_value.1, arrayobj.py:2049)], incoming_blocks=[48, 34])\n", - "2024-10-16 10:10:44,688 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:44,889 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=2259)\n", - " 2\tLOAD_FAST(arg=0, lineno=2260)\n", - " 4\tLOAD_METHOD(arg=0, lineno=2260)\n", - " 6\tCALL_METHOD(arg=0, lineno=2260)\n", - " 8\tLOAD_METHOD(arg=1, lineno=2260)\n", - " 10\tLOAD_FAST(arg=0, lineno=2260)\n", - " 12\tLOAD_ATTR(arg=2, lineno=2260)\n", - " 14\tCALL_METHOD(arg=1, lineno=2260)\n", - " 16\tRETURN_VALUE(arg=None, lineno=2260)\n", - "2024-10-16 10:10:44,890 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:44,891 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:44,891 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:44,892 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=2259)\n", - "2024-10-16 10:10:44,893 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:44,893 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=2260)\n", - "2024-10-16 10:10:44,894 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:44,895 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=0, lineno=2260)\n", - "2024-10-16 10:10:44,895 - numba.core.byteflow - DEBUG - stack ['$ary2.0']\n", - "2024-10-16 10:10:44,896 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_METHOD(arg=0, lineno=2260)\n", - "2024-10-16 10:10:44,897 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:10:44,897 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=1, lineno=2260)\n", - "2024-10-16 10:10:44,898 - numba.core.byteflow - DEBUG - stack ['$6call_method.2']\n", - "2024-10-16 10:10:44,899 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_FAST(arg=0, lineno=2260)\n", - "2024-10-16 10:10:44,899 - numba.core.byteflow - DEBUG - stack ['$8load_method.3']\n", - "2024-10-16 10:10:44,900 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=2, lineno=2260)\n", - "2024-10-16 10:10:44,901 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$ary10.4']\n", - "2024-10-16 10:10:44,901 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=CALL_METHOD(arg=1, lineno=2260)\n", - "2024-10-16 10:10:44,902 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$12load_attr.5']\n", - "2024-10-16 10:10:44,903 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=RETURN_VALUE(arg=None, lineno=2260)\n", - "2024-10-16 10:10:44,903 - numba.core.byteflow - DEBUG - stack ['$14call_method.6']\n", - "2024-10-16 10:10:44,904 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:44,904 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:44,905 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:10:44,906 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:10:44,906 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:10:44,907 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:10:44,908 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:10:44,908 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:10:44,909 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:44,910 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$ary2.0'}), (4, {'item': '$ary2.0', 'res': '$4load_method.1'}), (6, {'func': '$4load_method.1', 'args': [], 'res': '$6call_method.2'}), (8, {'item': '$6call_method.2', 'res': '$8load_method.3'}), (10, {'res': '$ary10.4'}), (12, {'item': '$ary10.4', 'res': '$12load_attr.5'}), (14, {'func': '$8load_method.3', 'args': ['$12load_attr.5'], 'res': '$14call_method.6'}), (16, {'retval': '$14call_method.6', 'castval': '$16return_value.7'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:44,911 - numba.core.interpreter - DEBUG - label 0:\n", - " ary = arg(0, name=ary) ['ary']\n", - " $4load_method.1 = getattr(value=ary, attr=copy) ['$4load_method.1', 'ary']\n", - " $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$6call_method.2']\n", - " $8load_method.3 = getattr(value=$6call_method.2, attr=reshape) ['$6call_method.2', '$8load_method.3']\n", - " $12load_attr.5 = getattr(value=ary, attr=size) ['$12load_attr.5', 'ary']\n", - " $14call_method.6 = call $8load_method.3($12load_attr.5, func=$8load_method.3, args=[Var($12load_attr.5, arrayobj.py:2260)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_attr.5', '$14call_method.6', '$8load_method.3']\n", - " $16return_value.7 = cast(value=$14call_method.6) ['$14call_method.6', '$16return_value.7']\n", - " return $16return_value.7 ['$16return_value.7']\n", - "\n", - "2024-10-16 10:10:44,919 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:44,920 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,920 - numba.core.ssa - DEBUG - on stmt: ary = arg(0, name=ary)\n", - "2024-10-16 10:10:44,921 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=ary, attr=copy)\n", - "2024-10-16 10:10:44,922 - numba.core.ssa - DEBUG - on stmt: $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,922 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6call_method.2, attr=reshape)\n", - "2024-10-16 10:10:44,923 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=ary, attr=size)\n", - "2024-10-16 10:10:44,924 - numba.core.ssa - DEBUG - on stmt: $14call_method.6 = call $8load_method.3($12load_attr.5, func=$8load_method.3, args=[Var($12load_attr.5, arrayobj.py:2260)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,924 - numba.core.ssa - DEBUG - on stmt: $16return_value.7 = cast(value=$14call_method.6)\n", - "2024-10-16 10:10:44,925 - numba.core.ssa - DEBUG - on stmt: return $16return_value.7\n", - "2024-10-16 10:10:44,926 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12load_attr.5': [],\n", - " '$14call_method.6': [],\n", - " '$16return_value.7': [],\n", - " '$4load_method.1': [],\n", - " '$6call_method.2': [],\n", - " '$8load_method.3': [],\n", - " 'ary': []})\n", - "2024-10-16 10:10:44,927 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:10:44,954 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=4245)\n", - " 2\tLOAD_FAST(arg=0, lineno=4248)\n", - " 4\tLOAD_METHOD(arg=0, lineno=4248)\n", - " 6\tLOAD_FAST(arg=1, lineno=4248)\n", - " 8\tLOAD_FAST(arg=2, lineno=4248)\n", - " 10\tCALL_METHOD(arg=2, lineno=4248)\n", - " 12\tRETURN_VALUE(arg=None, lineno=4248)\n", - "2024-10-16 10:10:44,954 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:44,955 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:44,956 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:44,957 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=4245)\n", - "2024-10-16 10:10:44,958 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:44,958 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=4248)\n", - "2024-10-16 10:10:44,959 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:44,960 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=0, lineno=4248)\n", - "2024-10-16 10:10:44,961 - numba.core.byteflow - DEBUG - stack ['$arrtype2.0']\n", - "2024-10-16 10:10:44,961 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=4248)\n", - "2024-10-16 10:10:44,962 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:10:44,963 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_FAST(arg=2, lineno=4248)\n", - "2024-10-16 10:10:44,964 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$size6.2']\n", - "2024-10-16 10:10:44,965 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=CALL_METHOD(arg=2, lineno=4248)\n", - "2024-10-16 10:10:44,965 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$size6.2', '$align8.3']\n", - "2024-10-16 10:10:44,966 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=RETURN_VALUE(arg=None, lineno=4248)\n", - "2024-10-16 10:10:44,967 - numba.core.byteflow - DEBUG - stack ['$10call_method.4']\n", - "2024-10-16 10:10:44,968 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:44,969 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:44,969 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:10:44,970 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:10:44,971 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:10:44,972 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:10:44,973 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:10:44,973 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:10:44,974 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:44,975 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$arrtype2.0'}), (4, {'item': '$arrtype2.0', 'res': '$4load_method.1'}), (6, {'res': '$size6.2'}), (8, {'res': '$align8.3'}), (10, {'func': '$4load_method.1', 'args': ['$size6.2', '$align8.3'], 'res': '$10call_method.4'}), (12, {'retval': '$10call_method.4', 'castval': '$12return_value.5'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:44,976 - numba.core.interpreter - DEBUG - label 0:\n", - " arrtype = arg(0, name=arrtype) ['arrtype']\n", - " size = arg(1, name=size) ['size']\n", - " align = arg(2, name=align) ['align']\n", - " $4load_method.1 = getattr(value=arrtype, attr=_allocate) ['$4load_method.1', 'arrtype']\n", - " $10call_method.4 = call $4load_method.1(size, align, func=$4load_method.1, args=[Var(size, arrayobj.py:4245), Var(align, arrayobj.py:4245)], kws=(), vararg=None, varkwarg=None, target=None) ['$10call_method.4', '$4load_method.1', 'align', 'size']\n", - " $12return_value.5 = cast(value=$10call_method.4) ['$10call_method.4', '$12return_value.5']\n", - " return $12return_value.5 ['$12return_value.5']\n", - "\n", - "2024-10-16 10:10:44,988 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:44,989 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:44,990 - numba.core.ssa - DEBUG - on stmt: arrtype = arg(0, name=arrtype)\n", - "2024-10-16 10:10:44,991 - numba.core.ssa - DEBUG - on stmt: size = arg(1, name=size)\n", - "2024-10-16 10:10:44,992 - numba.core.ssa - DEBUG - on stmt: align = arg(2, name=align)\n", - "2024-10-16 10:10:44,992 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=arrtype, attr=_allocate)\n", - "2024-10-16 10:10:44,993 - numba.core.ssa - DEBUG - on stmt: $10call_method.4 = call $4load_method.1(size, align, func=$4load_method.1, args=[Var(size, arrayobj.py:4245), Var(align, arrayobj.py:4245)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:44,994 - numba.core.ssa - DEBUG - on stmt: $12return_value.5 = cast(value=$10call_method.4)\n", - "2024-10-16 10:10:44,995 - numba.core.ssa - DEBUG - on stmt: return $12return_value.5\n", - "2024-10-16 10:10:44,996 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10call_method.4': [],\n", - " '$12return_value.5': [],\n", - " '$4load_method.1': [],\n", - " 'align': [],\n", - " 'arrtype': [],\n", - " 'size': []})\n", - "2024-10-16 10:10:44,997 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:10:45,004 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=4240)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=4241)\n", - " 4\tLOAD_FAST(arg=1, lineno=4241)\n", - " 6\tLOAD_FAST(arg=2, lineno=4241)\n", - " 8\tCALL_FUNCTION(arg=2, lineno=4241)\n", - " 10\tRETURN_VALUE(arg=None, lineno=4241)\n", - "2024-10-16 10:10:45,004 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:45,005 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,006 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:45,007 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=4240)\n", - "2024-10-16 10:10:45,008 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,009 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=4241)\n", - "2024-10-16 10:10:45,009 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,010 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=1, lineno=4241)\n", - "2024-10-16 10:10:45,011 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:10:45,012 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=2, lineno=4241)\n", - "2024-10-16 10:10:45,013 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$allocsize4.1']\n", - "2024-10-16 10:10:45,013 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_FUNCTION(arg=2, lineno=4241)\n", - "2024-10-16 10:10:45,014 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$allocsize4.1', '$align6.2']\n", - "2024-10-16 10:10:45,015 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=RETURN_VALUE(arg=None, lineno=4241)\n", - "2024-10-16 10:10:45,016 - numba.core.byteflow - DEBUG - stack ['$8call_function.3']\n", - "2024-10-16 10:10:45,017 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:45,018 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:45,019 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:10:45,019 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:10:45,020 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:10:45,021 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:10:45,022 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:10:45,023 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:10:45,024 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:45,025 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$allocsize4.1'}), (6, {'res': '$align6.2'}), (8, {'func': '$2load_global.0', 'args': ['$allocsize4.1', '$align6.2'], 'res': '$8call_function.3'}), (10, {'retval': '$8call_function.3', 'castval': '$10return_value.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:45,026 - numba.core.interpreter - DEBUG - label 0:\n", - " cls = arg(0, name=cls) ['cls']\n", - " allocsize = arg(1, name=allocsize) ['allocsize']\n", - " align = arg(2, name=align) ['align']\n", - " $2load_global.0 = global(intrin_alloc: ) ['$2load_global.0']\n", - " $8call_function.3 = call $2load_global.0(allocsize, align, func=$2load_global.0, args=[Var(allocsize, arrayobj.py:4240), Var(align, arrayobj.py:4240)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', '$8call_function.3', 'align', 'allocsize']\n", - " $10return_value.4 = cast(value=$8call_function.3) ['$10return_value.4', '$8call_function.3']\n", - " return $10return_value.4 ['$10return_value.4']\n", - "\n", - "2024-10-16 10:10:45,044 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:45,054 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,054 - numba.core.ssa - DEBUG - on stmt: cls = arg(0, name=cls)\n", - "2024-10-16 10:10:45,055 - numba.core.ssa - DEBUG - on stmt: allocsize = arg(1, name=allocsize)\n", - "2024-10-16 10:10:45,056 - numba.core.ssa - DEBUG - on stmt: align = arg(2, name=align)\n", - "2024-10-16 10:10:45,057 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(intrin_alloc: )\n", - "2024-10-16 10:10:45,058 - numba.core.ssa - DEBUG - on stmt: $8call_function.3 = call $2load_global.0(allocsize, align, func=$2load_global.0, args=[Var(allocsize, arrayobj.py:4240), Var(align, arrayobj.py:4240)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,059 - numba.core.ssa - DEBUG - on stmt: $10return_value.4 = cast(value=$8call_function.3)\n", - "2024-10-16 10:10:45,060 - numba.core.ssa - DEBUG - on stmt: return $10return_value.4\n", - "2024-10-16 10:10:45,061 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10return_value.4': [],\n", - " '$2load_global.0': [],\n", - " '$8call_function.3': [],\n", - " 'align': [],\n", - " 'allocsize': [],\n", - " 'cls': []})\n", - "2024-10-16 10:10:45,062 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:10:45,298 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=1)\n", - " 2\tLOAD_FAST(arg=0, lineno=1)\n", - " 4\tLOAD_CONST(arg=1, lineno=1)\n", - " 6\tBINARY_FLOOR_DIVIDE(arg=None, lineno=1)\n", - " 8\tRETURN_VALUE(arg=None, lineno=1)\n", - "2024-10-16 10:10:45,298 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:45,299 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,300 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:45,301 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=1)\n", - "2024-10-16 10:10:45,301 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,302 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=1)\n", - "2024-10-16 10:10:45,302 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,303 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_CONST(arg=1, lineno=1)\n", - "2024-10-16 10:10:45,304 - numba.core.byteflow - DEBUG - stack ['$_68call_method_31_12.0']\n", - "2024-10-16 10:10:45,305 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=BINARY_FLOOR_DIVIDE(arg=None, lineno=1)\n", - "2024-10-16 10:10:45,305 - numba.core.byteflow - DEBUG - stack ['$_68call_method_31_12.0', '$const4.1']\n", - "2024-10-16 10:10:45,306 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=1)\n", - "2024-10-16 10:10:45,307 - numba.core.byteflow - DEBUG - stack ['$6binary_floor_divide.2']\n", - "2024-10-16 10:10:45,307 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:45,308 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:45,308 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:10:45,309 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:10:45,310 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:10:45,310 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:10:45,311 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:10:45,312 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:10:45,312 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:45,313 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$_68call_method_31_12.0'}), (4, {'res': '$const4.1'}), (6, {'lhs': '$_68call_method_31_12.0', 'rhs': '$const4.1', 'res': '$6binary_floor_divide.2'}), (8, {'retval': '$6binary_floor_divide.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:45,314 - numba.core.interpreter - DEBUG - label 0:\n", - " _68call_method_31_1 = arg(0, name=_68call_method_31_1) ['_68call_method_31_1']\n", - " $const4.1 = const(int, 2) ['$const4.1']\n", - " $6binary_floor_divide.2 = _68call_method_31_1 // $const4.1 ['$6binary_floor_divide.2', '$const4.1', '_68call_method_31_1']\n", - " $8return_value.3 = cast(value=$6binary_floor_divide.2) ['$6binary_floor_divide.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:10:45,320 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:45,321 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,321 - numba.core.ssa - DEBUG - on stmt: _68call_method_31_1 = arg(0, name=_68call_method_31_1)\n", - "2024-10-16 10:10:45,322 - numba.core.ssa - DEBUG - on stmt: $const4.1 = const(int, 2)\n", - "2024-10-16 10:10:45,323 - numba.core.ssa - DEBUG - on stmt: $6binary_floor_divide.2 = _68call_method_31_1 // $const4.1\n", - "2024-10-16 10:10:45,323 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6binary_floor_divide.2)\n", - "2024-10-16 10:10:45,324 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:10:45,325 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$6binary_floor_divide.2': [],\n", - " '$8return_value.3': [],\n", - " '$const4.1': [],\n", - " '_68call_method_31_1': []})\n", - "2024-10-16 10:10:45,326 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:10:45,349 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=189)\n", - " 2\tLOAD_FAST(arg=0, lineno=204)\n", - " 4\tLOAD_FAST(arg=2, lineno=204)\n", - " 6\tCOMPARE_OP(arg=4, lineno=204)\n", - " 8\tPOP_JUMP_IF_FALSE(arg=8, lineno=204)\n", - " 10\tLOAD_CONST(arg=1, lineno=207)\n", - " 12\tRETURN_VALUE(arg=None, lineno=207)\n", - "> 14\tLOAD_CONST(arg=1, lineno=209)\n", - " 16\tSTORE_FAST(arg=4, lineno=209)\n", - " 18\tLOAD_FAST(arg=2, lineno=210)\n", - " 20\tLOAD_FAST(arg=0, lineno=210)\n", - " 22\tBINARY_SUBTRACT(arg=None, lineno=210)\n", - " 24\tSTORE_FAST(arg=5, lineno=210)\n", - " 26\tLOAD_FAST(arg=4, lineno=211)\n", - " 28\tLOAD_FAST(arg=0, lineno=211)\n", - " 30\tCOMPARE_OP(arg=0, lineno=211)\n", - " 32\tPOP_JUMP_IF_FALSE(arg=64, lineno=211)\n", - "> 34\tLOAD_FAST(arg=1, lineno=212)\n", - " 36\tLOAD_FAST(arg=4, lineno=212)\n", - " 38\tBINARY_SUBSCR(arg=None, lineno=212)\n", - " 40\tSTORE_FAST(arg=6, lineno=212)\n", - " 42\tLOAD_FAST(arg=3, lineno=213)\n", - " 44\tLOAD_FAST(arg=5, lineno=213)\n", - " 46\tBINARY_SUBSCR(arg=None, lineno=213)\n", - " 48\tSTORE_FAST(arg=7, lineno=213)\n", - " 50\tLOAD_FAST(arg=7, lineno=216)\n", - " 52\tLOAD_CONST(arg=2, lineno=216)\n", - " 54\tCOMPARE_OP(arg=3, lineno=216)\n", - " 56\tPOP_JUMP_IF_FALSE(arg=44, lineno=216)\n", - " 58\tLOAD_FAST(arg=6, lineno=220)\n", - " 60\tLOAD_FAST(arg=7, lineno=220)\n", - " 62\tCOMPARE_OP(arg=3, lineno=220)\n", - " 64\tPOP_JUMP_IF_FALSE(arg=43, lineno=220)\n", - " 66\tLOAD_FAST(arg=6, lineno=220)\n", - " 68\tLOAD_CONST(arg=2, lineno=220)\n", - " 70\tCOMPARE_OP(arg=3, lineno=220)\n", - " 72\tPOP_JUMP_IF_FALSE(arg=43, lineno=220)\n", - " 74\tLOAD_FAST(arg=5, lineno=221)\n", - " 76\tLOAD_CONST(arg=2, lineno=221)\n", - " 78\tBINARY_ADD(arg=None, lineno=221)\n", - " 80\tUNARY_NEGATIVE(arg=None, lineno=221)\n", - " 82\tRETURN_VALUE(arg=None, lineno=221)\n", - "> 84\tJUMP_FORWARD(arg=8, lineno=221)\n", - "> 86\tLOAD_FAST(arg=6, lineno=222)\n", - " 88\tLOAD_CONST(arg=2, lineno=222)\n", - " 90\tCOMPARE_OP(arg=3, lineno=222)\n", - " 92\tPOP_JUMP_IF_FALSE(arg=52, lineno=222)\n", - " 94\tLOAD_FAST(arg=6, lineno=224)\n", - " 96\tLOAD_FAST(arg=3, lineno=224)\n", - " 98\tLOAD_FAST(arg=5, lineno=224)\n", - " 100\tSTORE_SUBSCR(arg=None, lineno=224)\n", - "> 102\tLOAD_FAST(arg=4, lineno=225)\n", - " 104\tLOAD_CONST(arg=2, lineno=225)\n", - " 106\tINPLACE_ADD(arg=None, lineno=225)\n", - " 108\tSTORE_FAST(arg=4, lineno=225)\n", - " 110\tLOAD_FAST(arg=5, lineno=226)\n", - " 112\tLOAD_CONST(arg=2, lineno=226)\n", - " 114\tINPLACE_ADD(arg=None, lineno=226)\n", - " 116\tSTORE_FAST(arg=5, lineno=226)\n", - " 118\tLOAD_FAST(arg=4, lineno=211)\n", - " 120\tLOAD_FAST(arg=0, lineno=211)\n", - " 122\tCOMPARE_OP(arg=0, lineno=211)\n", - " 124\tPOP_JUMP_IF_TRUE(arg=18, lineno=211)\n", - "> 126\tLOAD_FAST(arg=5, lineno=227)\n", - " 128\tRETURN_VALUE(arg=None, lineno=227)\n", - "2024-10-16 10:10:45,350 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:45,351 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,352 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:45,352 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=189)\n", - "2024-10-16 10:10:45,353 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,354 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=204)\n", - "2024-10-16 10:10:45,354 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,355 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=2, lineno=204)\n", - "2024-10-16 10:10:45,356 - numba.core.byteflow - DEBUG - stack ['$src_ndim2.0']\n", - "2024-10-16 10:10:45,356 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=COMPARE_OP(arg=4, lineno=204)\n", - "2024-10-16 10:10:45,357 - numba.core.byteflow - DEBUG - stack ['$src_ndim2.0', '$dest_ndim4.1']\n", - "2024-10-16 10:10:45,358 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=POP_JUMP_IF_FALSE(arg=8, lineno=204)\n", - "2024-10-16 10:10:45,358 - numba.core.byteflow - DEBUG - stack ['$6compare_op.2']\n", - "2024-10-16 10:10:45,359 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=10, stack=(), blockstack=(), npush=0), Edge(pc=14, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:45,359 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=10 nstack_initial=0), State(pc_initial=14 nstack_initial=0)])\n", - "2024-10-16 10:10:45,360 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,361 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=10 nstack_initial=0)\n", - "2024-10-16 10:10:45,362 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_CONST(arg=1, lineno=207)\n", - "2024-10-16 10:10:45,362 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,363 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=RETURN_VALUE(arg=None, lineno=207)\n", - "2024-10-16 10:10:45,364 - numba.core.byteflow - DEBUG - stack ['$const10.0']\n", - "2024-10-16 10:10:45,365 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:45,365 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=14 nstack_initial=0)])\n", - "2024-10-16 10:10:45,366 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,367 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=14 nstack_initial=0)\n", - "2024-10-16 10:10:45,367 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_CONST(arg=1, lineno=209)\n", - "2024-10-16 10:10:45,368 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,368 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=STORE_FAST(arg=4, lineno=209)\n", - "2024-10-16 10:10:45,369 - numba.core.byteflow - DEBUG - stack ['$const14.0']\n", - "2024-10-16 10:10:45,370 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_FAST(arg=2, lineno=210)\n", - "2024-10-16 10:10:45,370 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,371 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=0, lineno=210)\n", - "2024-10-16 10:10:45,372 - numba.core.byteflow - DEBUG - stack ['$dest_ndim18.1']\n", - "2024-10-16 10:10:45,373 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=BINARY_SUBTRACT(arg=None, lineno=210)\n", - "2024-10-16 10:10:45,373 - numba.core.byteflow - DEBUG - stack ['$dest_ndim18.1', '$src_ndim20.2']\n", - "2024-10-16 10:10:45,374 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=STORE_FAST(arg=5, lineno=210)\n", - "2024-10-16 10:10:45,375 - numba.core.byteflow - DEBUG - stack ['$22binary_subtract.3']\n", - "2024-10-16 10:10:45,375 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_FAST(arg=4, lineno=211)\n", - "2024-10-16 10:10:45,376 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,377 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_FAST(arg=0, lineno=211)\n", - "2024-10-16 10:10:45,377 - numba.core.byteflow - DEBUG - stack ['$src_index26.4']\n", - "2024-10-16 10:10:45,378 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=COMPARE_OP(arg=0, lineno=211)\n", - "2024-10-16 10:10:45,378 - numba.core.byteflow - DEBUG - stack ['$src_index26.4', '$src_ndim28.5']\n", - "2024-10-16 10:10:45,379 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=POP_JUMP_IF_FALSE(arg=64, lineno=211)\n", - "2024-10-16 10:10:45,380 - numba.core.byteflow - DEBUG - stack ['$30compare_op.6']\n", - "2024-10-16 10:10:45,381 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=34, stack=(), blockstack=(), npush=0), Edge(pc=126, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:45,382 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=34 nstack_initial=0), State(pc_initial=126 nstack_initial=0)])\n", - "2024-10-16 10:10:45,382 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,383 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=34 nstack_initial=0)\n", - "2024-10-16 10:10:45,384 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=1, lineno=212)\n", - "2024-10-16 10:10:45,385 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,386 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_FAST(arg=4, lineno=212)\n", - "2024-10-16 10:10:45,386 - numba.core.byteflow - DEBUG - stack ['$src_shape34.0']\n", - "2024-10-16 10:10:45,387 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=BINARY_SUBSCR(arg=None, lineno=212)\n", - "2024-10-16 10:10:45,388 - numba.core.byteflow - DEBUG - stack ['$src_shape34.0', '$src_index36.1']\n", - "2024-10-16 10:10:45,389 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=STORE_FAST(arg=6, lineno=212)\n", - "2024-10-16 10:10:45,390 - numba.core.byteflow - DEBUG - stack ['$38binary_subscr.2']\n", - "2024-10-16 10:10:45,390 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_FAST(arg=3, lineno=213)\n", - "2024-10-16 10:10:45,391 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,392 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=LOAD_FAST(arg=5, lineno=213)\n", - "2024-10-16 10:10:45,393 - numba.core.byteflow - DEBUG - stack ['$dest_shape42.3']\n", - "2024-10-16 10:10:45,394 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=BINARY_SUBSCR(arg=None, lineno=213)\n", - "2024-10-16 10:10:45,394 - numba.core.byteflow - DEBUG - stack ['$dest_shape42.3', '$dest_index44.4']\n", - "2024-10-16 10:10:45,395 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=STORE_FAST(arg=7, lineno=213)\n", - "2024-10-16 10:10:45,396 - numba.core.byteflow - DEBUG - stack ['$46binary_subscr.5']\n", - "2024-10-16 10:10:45,397 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_FAST(arg=7, lineno=216)\n", - "2024-10-16 10:10:45,398 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,399 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=LOAD_CONST(arg=2, lineno=216)\n", - "2024-10-16 10:10:45,399 - numba.core.byteflow - DEBUG - stack ['$dest_dim_size50.6']\n", - "2024-10-16 10:10:45,400 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=COMPARE_OP(arg=3, lineno=216)\n", - "2024-10-16 10:10:45,401 - numba.core.byteflow - DEBUG - stack ['$dest_dim_size50.6', '$const52.7']\n", - "2024-10-16 10:10:45,402 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=POP_JUMP_IF_FALSE(arg=44, lineno=216)\n", - "2024-10-16 10:10:45,403 - numba.core.byteflow - DEBUG - stack ['$54compare_op.8']\n", - "2024-10-16 10:10:45,404 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=58, stack=(), blockstack=(), npush=0), Edge(pc=86, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:45,404 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=126 nstack_initial=0), State(pc_initial=58 nstack_initial=0), State(pc_initial=86 nstack_initial=0)])\n", - "2024-10-16 10:10:45,405 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,406 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=126 nstack_initial=0)\n", - "2024-10-16 10:10:45,407 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_FAST(arg=5, lineno=227)\n", - "2024-10-16 10:10:45,408 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,409 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=RETURN_VALUE(arg=None, lineno=227)\n", - "2024-10-16 10:10:45,410 - numba.core.byteflow - DEBUG - stack ['$dest_index126.0']\n", - "2024-10-16 10:10:45,410 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:45,411 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=58 nstack_initial=0), State(pc_initial=86 nstack_initial=0)])\n", - "2024-10-16 10:10:45,412 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,413 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=58 nstack_initial=0)\n", - "2024-10-16 10:10:45,414 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_FAST(arg=6, lineno=220)\n", - "2024-10-16 10:10:45,415 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,415 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_FAST(arg=7, lineno=220)\n", - "2024-10-16 10:10:45,416 - numba.core.byteflow - DEBUG - stack ['$src_dim_size58.0']\n", - "2024-10-16 10:10:45,417 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=COMPARE_OP(arg=3, lineno=220)\n", - "2024-10-16 10:10:45,418 - numba.core.byteflow - DEBUG - stack ['$src_dim_size58.0', '$dest_dim_size60.1']\n", - "2024-10-16 10:10:45,419 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=POP_JUMP_IF_FALSE(arg=43, lineno=220)\n", - "2024-10-16 10:10:45,420 - numba.core.byteflow - DEBUG - stack ['$62compare_op.2']\n", - "2024-10-16 10:10:45,420 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=66, stack=(), blockstack=(), npush=0), Edge(pc=84, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:45,421 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=0), State(pc_initial=66 nstack_initial=0), State(pc_initial=84 nstack_initial=0)])\n", - "2024-10-16 10:10:45,422 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,423 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=86 nstack_initial=0)\n", - "2024-10-16 10:10:45,424 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=6, lineno=222)\n", - "2024-10-16 10:10:45,424 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,425 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_CONST(arg=2, lineno=222)\n", - "2024-10-16 10:10:45,426 - numba.core.byteflow - DEBUG - stack ['$src_dim_size86.0']\n", - "2024-10-16 10:10:45,427 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=COMPARE_OP(arg=3, lineno=222)\n", - "2024-10-16 10:10:45,428 - numba.core.byteflow - DEBUG - stack ['$src_dim_size86.0', '$const88.1']\n", - "2024-10-16 10:10:45,428 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=POP_JUMP_IF_FALSE(arg=52, lineno=222)\n", - "2024-10-16 10:10:45,429 - numba.core.byteflow - DEBUG - stack ['$90compare_op.2']\n", - "2024-10-16 10:10:45,430 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=94, stack=(), blockstack=(), npush=0), Edge(pc=102, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:45,431 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=66 nstack_initial=0), State(pc_initial=84 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=102 nstack_initial=0)])\n", - "2024-10-16 10:10:45,432 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,433 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=66 nstack_initial=0)\n", - "2024-10-16 10:10:45,433 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_FAST(arg=6, lineno=220)\n", - "2024-10-16 10:10:45,434 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,435 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_CONST(arg=2, lineno=220)\n", - "2024-10-16 10:10:45,436 - numba.core.byteflow - DEBUG - stack ['$src_dim_size66.0']\n", - "2024-10-16 10:10:45,437 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=COMPARE_OP(arg=3, lineno=220)\n", - "2024-10-16 10:10:45,437 - numba.core.byteflow - DEBUG - stack ['$src_dim_size66.0', '$const68.1']\n", - "2024-10-16 10:10:45,438 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=POP_JUMP_IF_FALSE(arg=43, lineno=220)\n", - "2024-10-16 10:10:45,439 - numba.core.byteflow - DEBUG - stack ['$70compare_op.2']\n", - "2024-10-16 10:10:45,440 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=74, stack=(), blockstack=(), npush=0), Edge(pc=84, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:45,441 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=84 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=102 nstack_initial=0), State(pc_initial=74 nstack_initial=0), State(pc_initial=84 nstack_initial=0)])\n", - "2024-10-16 10:10:45,441 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,442 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=84 nstack_initial=0)\n", - "2024-10-16 10:10:45,443 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=JUMP_FORWARD(arg=8, lineno=221)\n", - "2024-10-16 10:10:45,444 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,445 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=102, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:45,446 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=94 nstack_initial=0), State(pc_initial=102 nstack_initial=0), State(pc_initial=74 nstack_initial=0), State(pc_initial=84 nstack_initial=0), State(pc_initial=102 nstack_initial=0)])\n", - "2024-10-16 10:10:45,446 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,447 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=94 nstack_initial=0)\n", - "2024-10-16 10:10:45,448 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_FAST(arg=6, lineno=224)\n", - "2024-10-16 10:10:45,449 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,449 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=LOAD_FAST(arg=3, lineno=224)\n", - "2024-10-16 10:10:45,450 - numba.core.byteflow - DEBUG - stack ['$src_dim_size94.0']\n", - "2024-10-16 10:10:45,451 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=5, lineno=224)\n", - "2024-10-16 10:10:45,452 - numba.core.byteflow - DEBUG - stack ['$src_dim_size94.0', '$dest_shape96.1']\n", - "2024-10-16 10:10:45,452 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=STORE_SUBSCR(arg=None, lineno=224)\n", - "2024-10-16 10:10:45,453 - numba.core.byteflow - DEBUG - stack ['$src_dim_size94.0', '$dest_shape96.1', '$dest_index98.2']\n", - "2024-10-16 10:10:45,454 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=102, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:45,455 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=102 nstack_initial=0), State(pc_initial=74 nstack_initial=0), State(pc_initial=84 nstack_initial=0), State(pc_initial=102 nstack_initial=0), State(pc_initial=102 nstack_initial=0)])\n", - "2024-10-16 10:10:45,456 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,456 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=102 nstack_initial=0)\n", - "2024-10-16 10:10:45,457 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=LOAD_FAST(arg=4, lineno=225)\n", - "2024-10-16 10:10:45,458 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,459 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=LOAD_CONST(arg=2, lineno=225)\n", - "2024-10-16 10:10:45,459 - numba.core.byteflow - DEBUG - stack ['$src_index102.0']\n", - "2024-10-16 10:10:45,460 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=INPLACE_ADD(arg=None, lineno=225)\n", - "2024-10-16 10:10:45,461 - numba.core.byteflow - DEBUG - stack ['$src_index102.0', '$const104.1']\n", - "2024-10-16 10:10:45,462 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=STORE_FAST(arg=4, lineno=225)\n", - "2024-10-16 10:10:45,462 - numba.core.byteflow - DEBUG - stack ['$106inplace_add.2']\n", - "2024-10-16 10:10:45,463 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=LOAD_FAST(arg=5, lineno=226)\n", - "2024-10-16 10:10:45,464 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,465 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=2, lineno=226)\n", - "2024-10-16 10:10:45,466 - numba.core.byteflow - DEBUG - stack ['$dest_index110.3']\n", - "2024-10-16 10:10:45,466 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=INPLACE_ADD(arg=None, lineno=226)\n", - "2024-10-16 10:10:45,493 - numba.core.byteflow - DEBUG - stack ['$dest_index110.3', '$const112.4']\n", - "2024-10-16 10:10:45,493 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=STORE_FAST(arg=5, lineno=226)\n", - "2024-10-16 10:10:45,494 - numba.core.byteflow - DEBUG - stack ['$114inplace_add.5']\n", - "2024-10-16 10:10:45,494 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_FAST(arg=4, lineno=211)\n", - "2024-10-16 10:10:45,495 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,496 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=0, lineno=211)\n", - "2024-10-16 10:10:45,496 - numba.core.byteflow - DEBUG - stack ['$src_index118.6']\n", - "2024-10-16 10:10:45,497 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=COMPARE_OP(arg=0, lineno=211)\n", - "2024-10-16 10:10:45,497 - numba.core.byteflow - DEBUG - stack ['$src_index118.6', '$src_ndim120.7']\n", - "2024-10-16 10:10:45,498 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=POP_JUMP_IF_TRUE(arg=18, lineno=211)\n", - "2024-10-16 10:10:45,498 - numba.core.byteflow - DEBUG - stack ['$122compare_op.8']\n", - "2024-10-16 10:10:45,499 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=126, stack=(), blockstack=(), npush=0), Edge(pc=34, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:45,501 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=0), State(pc_initial=84 nstack_initial=0), State(pc_initial=102 nstack_initial=0), State(pc_initial=102 nstack_initial=0), State(pc_initial=126 nstack_initial=0), State(pc_initial=34 nstack_initial=0)])\n", - "2024-10-16 10:10:45,502 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:45,502 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=0)\n", - "2024-10-16 10:10:45,503 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_FAST(arg=5, lineno=221)\n", - "2024-10-16 10:10:45,503 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:45,504 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=LOAD_CONST(arg=2, lineno=221)\n", - "2024-10-16 10:10:45,505 - numba.core.byteflow - DEBUG - stack ['$dest_index74.0']\n", - "2024-10-16 10:10:45,505 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=BINARY_ADD(arg=None, lineno=221)\n", - "2024-10-16 10:10:45,506 - numba.core.byteflow - DEBUG - stack ['$dest_index74.0', '$const76.1']\n", - "2024-10-16 10:10:45,506 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=UNARY_NEGATIVE(arg=None, lineno=221)\n", - "2024-10-16 10:10:45,507 - numba.core.byteflow - DEBUG - stack ['$78binary_add.2']\n", - "2024-10-16 10:10:45,507 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=RETURN_VALUE(arg=None, lineno=221)\n", - "2024-10-16 10:10:45,508 - numba.core.byteflow - DEBUG - stack ['$80unary_negative.3']\n", - "2024-10-16 10:10:45,509 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:45,509 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=84 nstack_initial=0), State(pc_initial=102 nstack_initial=0), State(pc_initial=102 nstack_initial=0), State(pc_initial=126 nstack_initial=0), State(pc_initial=34 nstack_initial=0)])\n", - "2024-10-16 10:10:45,510 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=102 nstack_initial=0), State(pc_initial=102 nstack_initial=0), State(pc_initial=126 nstack_initial=0), State(pc_initial=34 nstack_initial=0)])\n", - "2024-10-16 10:10:45,510 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=102 nstack_initial=0), State(pc_initial=126 nstack_initial=0), State(pc_initial=34 nstack_initial=0)])\n", - "2024-10-16 10:10:45,511 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=126 nstack_initial=0), State(pc_initial=34 nstack_initial=0)])\n", - "2024-10-16 10:10:45,512 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=34 nstack_initial=0)])\n", - "2024-10-16 10:10:45,515 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:45,515 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=10 nstack_initial=0): set(),\n", - " State(pc_initial=14 nstack_initial=0): set(),\n", - " State(pc_initial=34 nstack_initial=0): set(),\n", - " State(pc_initial=58 nstack_initial=0): set(),\n", - " State(pc_initial=66 nstack_initial=0): set(),\n", - " State(pc_initial=74 nstack_initial=0): set(),\n", - " State(pc_initial=84 nstack_initial=0): set(),\n", - " State(pc_initial=86 nstack_initial=0): set(),\n", - " State(pc_initial=94 nstack_initial=0): set(),\n", - " State(pc_initial=102 nstack_initial=0): set(),\n", - " State(pc_initial=126 nstack_initial=0): set()})\n", - "2024-10-16 10:10:45,516 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:10:45,517 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:10:45,518 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:10:45,518 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:10:45,519 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:10:45,520 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:45,520 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$src_ndim2.0'}), (4, {'res': '$dest_ndim4.1'}), (6, {'lhs': '$src_ndim2.0', 'rhs': '$dest_ndim4.1', 'res': '$6compare_op.2'}), (8, {'pred': '$6compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={10: (), 14: ()})\n", - "2024-10-16 10:10:45,521 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=10 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((10, {'res': '$const10.0'}), (12, {'retval': '$const10.0', 'castval': '$12return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:45,522 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=14 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((14, {'res': '$const14.0'}), (16, {'value': '$const14.0'}), (18, {'res': '$dest_ndim18.1'}), (20, {'res': '$src_ndim20.2'}), (22, {'lhs': '$dest_ndim18.1', 'rhs': '$src_ndim20.2', 'res': '$22binary_subtract.3'}), (24, {'value': '$22binary_subtract.3'}), (26, {'res': '$src_index26.4'}), (28, {'res': '$src_ndim28.5'}), (30, {'lhs': '$src_index26.4', 'rhs': '$src_ndim28.5', 'res': '$30compare_op.6'}), (32, {'pred': '$30compare_op.6'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={34: (), 126: ()})\n", - "2024-10-16 10:10:45,523 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=34 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((34, {'res': '$src_shape34.0'}), (36, {'res': '$src_index36.1'}), (38, {'index': '$src_index36.1', 'target': '$src_shape34.0', 'res': '$38binary_subscr.2'}), (40, {'value': '$38binary_subscr.2'}), (42, {'res': '$dest_shape42.3'}), (44, {'res': '$dest_index44.4'}), (46, {'index': '$dest_index44.4', 'target': '$dest_shape42.3', 'res': '$46binary_subscr.5'}), (48, {'value': '$46binary_subscr.5'}), (50, {'res': '$dest_dim_size50.6'}), (52, {'res': '$const52.7'}), (54, {'lhs': '$dest_dim_size50.6', 'rhs': '$const52.7', 'res': '$54compare_op.8'}), (56, {'pred': '$54compare_op.8'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={58: (), 86: ()})\n", - "2024-10-16 10:10:45,524 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=58 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((58, {'res': '$src_dim_size58.0'}), (60, {'res': '$dest_dim_size60.1'}), (62, {'lhs': '$src_dim_size58.0', 'rhs': '$dest_dim_size60.1', 'res': '$62compare_op.2'}), (64, {'pred': '$62compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={66: (), 84: ()})\n", - "2024-10-16 10:10:45,524 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=66 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((66, {'res': '$src_dim_size66.0'}), (68, {'res': '$const68.1'}), (70, {'lhs': '$src_dim_size66.0', 'rhs': '$const68.1', 'res': '$70compare_op.2'}), (72, {'pred': '$70compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={74: (), 84: ()})\n", - "2024-10-16 10:10:45,526 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((74, {'res': '$dest_index74.0'}), (76, {'res': '$const76.1'}), (78, {'lhs': '$dest_index74.0', 'rhs': '$const76.1', 'res': '$78binary_add.2'}), (80, {'value': '$78binary_add.2', 'res': '$80unary_negative.3'}), (82, {'retval': '$80unary_negative.3', 'castval': '$82return_value.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:45,526 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=84 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((84, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={102: ()})\n", - "2024-10-16 10:10:45,527 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=86 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((86, {'res': '$src_dim_size86.0'}), (88, {'res': '$const88.1'}), (90, {'lhs': '$src_dim_size86.0', 'rhs': '$const88.1', 'res': '$90compare_op.2'}), (92, {'pred': '$90compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={94: (), 102: ()})\n", - "2024-10-16 10:10:45,527 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=94 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((94, {'res': '$src_dim_size94.0'}), (96, {'res': '$dest_shape96.1'}), (98, {'res': '$dest_index98.2'}), (100, {'target': '$dest_shape96.1', 'index': '$dest_index98.2', 'value': '$src_dim_size94.0'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={102: ()})\n", - "2024-10-16 10:10:45,528 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=102 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((102, {'res': '$src_index102.0'}), (104, {'res': '$const104.1'}), (106, {'lhs': '$src_index102.0', 'rhs': '$const104.1', 'res': '$106inplace_add.2'}), (108, {'value': '$106inplace_add.2'}), (110, {'res': '$dest_index110.3'}), (112, {'res': '$const112.4'}), (114, {'lhs': '$dest_index110.3', 'rhs': '$const112.4', 'res': '$114inplace_add.5'}), (116, {'value': '$114inplace_add.5'}), (118, {'res': '$src_index118.6'}), (120, {'res': '$src_ndim120.7'}), (122, {'lhs': '$src_index118.6', 'rhs': '$src_ndim120.7', 'res': '$122compare_op.8'}), (124, {'pred': '$122compare_op.8'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={126: (), 34: ()})\n", - "2024-10-16 10:10:45,529 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=126 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((126, {'res': '$dest_index126.0'}), (128, {'retval': '$dest_index126.0', 'castval': '$128return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:45,534 - numba.core.interpreter - DEBUG - label 0:\n", - " src_ndim = arg(0, name=src_ndim) ['src_ndim']\n", - " src_shape = arg(1, name=src_shape) ['src_shape']\n", - " dest_ndim = arg(2, name=dest_ndim) ['dest_ndim']\n", - " dest_shape = arg(3, name=dest_shape) ['dest_shape']\n", - " $6compare_op.2 = src_ndim > dest_ndim ['$6compare_op.2', 'dest_ndim', 'src_ndim']\n", - " bool8 = global(bool: ) ['bool8']\n", - " $8pred = call bool8($6compare_op.2, func=bool8, args=(Var($6compare_op.2, npyimpl.py:204),), kws=(), vararg=None, varkwarg=None, target=None) ['$6compare_op.2', '$8pred', 'bool8']\n", - " branch $8pred, 10, 14 ['$8pred']\n", - "label 10:\n", - " $const10.0 = const(int, 0) ['$const10.0']\n", - " $12return_value.1 = cast(value=$const10.0) ['$12return_value.1', '$const10.0']\n", - " return $12return_value.1 ['$12return_value.1']\n", - "label 14:\n", - " src_index = const(int, 0) ['src_index']\n", - " dest_index = dest_ndim - src_ndim ['dest_index', 'dest_ndim', 'src_ndim']\n", - " $30compare_op.6 = src_index < src_ndim ['$30compare_op.6', 'src_index', 'src_ndim']\n", - " bool32 = global(bool: ) ['bool32']\n", - " $32pred = call bool32($30compare_op.6, func=bool32, args=(Var($30compare_op.6, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None) ['$30compare_op.6', '$32pred', 'bool32']\n", - " branch $32pred, 34, 126 ['$32pred']\n", - "label 34:\n", - " src_dim_size = getitem(value=src_shape, index=src_index, fn=) ['src_dim_size', 'src_index', 'src_shape']\n", - " dest_dim_size = getitem(value=dest_shape, index=dest_index, fn=) ['dest_dim_size', 'dest_index', 'dest_shape']\n", - " $const52.7 = const(int, 1) ['$const52.7']\n", - " $54compare_op.8 = dest_dim_size != $const52.7 ['$54compare_op.8', '$const52.7', 'dest_dim_size']\n", - " bool56 = global(bool: ) ['bool56']\n", - " $56pred = call bool56($54compare_op.8, func=bool56, args=(Var($54compare_op.8, npyimpl.py:216),), kws=(), vararg=None, varkwarg=None, target=None) ['$54compare_op.8', '$56pred', 'bool56']\n", - " branch $56pred, 58, 86 ['$56pred']\n", - "label 58:\n", - " $62compare_op.2 = src_dim_size != dest_dim_size ['$62compare_op.2', 'dest_dim_size', 'src_dim_size']\n", - " bool64 = global(bool: ) ['bool64']\n", - " $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None) ['$62compare_op.2', '$64pred', 'bool64']\n", - " branch $64pred, 66, 84 ['$64pred']\n", - "label 66:\n", - " $const68.1 = const(int, 1) ['$const68.1']\n", - " $70compare_op.2 = src_dim_size != $const68.1 ['$70compare_op.2', '$const68.1', 'src_dim_size']\n", - " bool72 = global(bool: ) ['bool72']\n", - " $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None) ['$70compare_op.2', '$72pred', 'bool72']\n", - " branch $72pred, 74, 84 ['$72pred']\n", - "label 74:\n", - " $const76.1 = const(int, 1) ['$const76.1']\n", - " $78binary_add.2 = dest_index + $const76.1 ['$78binary_add.2', '$const76.1', 'dest_index']\n", - " $80unary_negative.3 = unary(fn=, value=$78binary_add.2) ['$78binary_add.2', '$80unary_negative.3']\n", - " $82return_value.4 = cast(value=$80unary_negative.3) ['$80unary_negative.3', '$82return_value.4']\n", - " return $82return_value.4 ['$82return_value.4']\n", - "label 84:\n", - " jump 102 []\n", - "label 86:\n", - " $const88.1 = const(int, 1) ['$const88.1']\n", - " $90compare_op.2 = src_dim_size != $const88.1 ['$90compare_op.2', '$const88.1', 'src_dim_size']\n", - " bool92 = global(bool: ) ['bool92']\n", - " $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, npyimpl.py:222),), kws=(), vararg=None, varkwarg=None, target=None) ['$90compare_op.2', '$92pred', 'bool92']\n", - " branch $92pred, 94, 102 ['$92pred']\n", - "label 94:\n", - " dest_shape[dest_index] = src_dim_size ['dest_index', 'dest_shape', 'src_dim_size']\n", - " jump 102 []\n", - "label 102:\n", - " $const104.1 = const(int, 1) ['$const104.1']\n", - " $106inplace_add.2 = inplace_binop(fn=, immutable_fn=, lhs=src_index, rhs=$const104.1, static_lhs=Undefined, static_rhs=Undefined) ['$106inplace_add.2', '$const104.1', 'src_index']\n", - " src_index = $106inplace_add.2 ['$106inplace_add.2', 'src_index']\n", - " $const112.4 = const(int, 1) ['$const112.4']\n", - " $114inplace_add.5 = inplace_binop(fn=, immutable_fn=, lhs=dest_index, rhs=$const112.4, static_lhs=Undefined, static_rhs=Undefined) ['$114inplace_add.5', '$const112.4', 'dest_index']\n", - " dest_index = $114inplace_add.5 ['$114inplace_add.5', 'dest_index']\n", - " $122compare_op.8 = src_index < src_ndim ['$122compare_op.8', 'src_index', 'src_ndim']\n", - " bool124 = global(bool: ) ['bool124']\n", - " $124pred = call bool124($122compare_op.8, func=bool124, args=(Var($122compare_op.8, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None) ['$122compare_op.8', '$124pred', 'bool124']\n", - " branch $124pred, 34, 126 ['$124pred']\n", - "label 126:\n", - " $128return_value.1 = cast(value=dest_index) ['$128return_value.1', 'dest_index']\n", - " return $128return_value.1 ['$128return_value.1']\n", - "\n", - "2024-10-16 10:10:45,562 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:45,563 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,564 - numba.core.ssa - DEBUG - on stmt: src_ndim = arg(0, name=src_ndim)\n", - "2024-10-16 10:10:45,564 - numba.core.ssa - DEBUG - on stmt: src_shape = arg(1, name=src_shape)\n", - "2024-10-16 10:10:45,565 - numba.core.ssa - DEBUG - on stmt: dest_ndim = arg(2, name=dest_ndim)\n", - "2024-10-16 10:10:45,566 - numba.core.ssa - DEBUG - on stmt: dest_shape = arg(3, name=dest_shape)\n", - "2024-10-16 10:10:45,567 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = src_ndim > dest_ndim\n", - "2024-10-16 10:10:45,567 - numba.core.ssa - DEBUG - on stmt: bool8 = global(bool: )\n", - "2024-10-16 10:10:45,568 - numba.core.ssa - DEBUG - on stmt: $8pred = call bool8($6compare_op.2, func=bool8, args=(Var($6compare_op.2, npyimpl.py:204),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,569 - numba.core.ssa - DEBUG - on stmt: branch $8pred, 10, 14\n", - "2024-10-16 10:10:45,569 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 10\n", - "2024-10-16 10:10:45,570 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,571 - numba.core.ssa - DEBUG - on stmt: $const10.0 = const(int, 0)\n", - "2024-10-16 10:10:45,572 - numba.core.ssa - DEBUG - on stmt: $12return_value.1 = cast(value=$const10.0)\n", - "2024-10-16 10:10:45,572 - numba.core.ssa - DEBUG - on stmt: return $12return_value.1\n", - "2024-10-16 10:10:45,573 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 14\n", - "2024-10-16 10:10:45,574 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,574 - numba.core.ssa - DEBUG - on stmt: src_index = const(int, 0)\n", - "2024-10-16 10:10:45,575 - numba.core.ssa - DEBUG - on stmt: dest_index = dest_ndim - src_ndim\n", - "2024-10-16 10:10:45,576 - numba.core.ssa - DEBUG - on stmt: $30compare_op.6 = src_index < src_ndim\n", - "2024-10-16 10:10:45,577 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:45,577 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.6, func=bool32, args=(Var($30compare_op.6, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,578 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 126\n", - "2024-10-16 10:10:45,579 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 34\n", - "2024-10-16 10:10:45,579 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,580 - numba.core.ssa - DEBUG - on stmt: src_dim_size = getitem(value=src_shape, index=src_index, fn=)\n", - "2024-10-16 10:10:45,581 - numba.core.ssa - DEBUG - on stmt: dest_dim_size = getitem(value=dest_shape, index=dest_index, fn=)\n", - "2024-10-16 10:10:45,582 - numba.core.ssa - DEBUG - on stmt: $const52.7 = const(int, 1)\n", - "2024-10-16 10:10:45,582 - numba.core.ssa - DEBUG - on stmt: $54compare_op.8 = dest_dim_size != $const52.7\n", - "2024-10-16 10:10:45,583 - numba.core.ssa - DEBUG - on stmt: bool56 = global(bool: )\n", - "2024-10-16 10:10:45,584 - numba.core.ssa - DEBUG - on stmt: $56pred = call bool56($54compare_op.8, func=bool56, args=(Var($54compare_op.8, npyimpl.py:216),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,585 - numba.core.ssa - DEBUG - on stmt: branch $56pred, 58, 86\n", - "2024-10-16 10:10:45,585 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 58\n", - "2024-10-16 10:10:45,586 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,587 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = src_dim_size != dest_dim_size\n", - "2024-10-16 10:10:45,588 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:45,588 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,589 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 84\n", - "2024-10-16 10:10:45,590 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 66\n", - "2024-10-16 10:10:45,591 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,592 - numba.core.ssa - DEBUG - on stmt: $const68.1 = const(int, 1)\n", - "2024-10-16 10:10:45,592 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = src_dim_size != $const68.1\n", - "2024-10-16 10:10:45,593 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:45,594 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,595 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 84\n", - "2024-10-16 10:10:45,596 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-10-16 10:10:45,596 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,597 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(int, 1)\n", - "2024-10-16 10:10:45,598 - numba.core.ssa - DEBUG - on stmt: $78binary_add.2 = dest_index + $const76.1\n", - "2024-10-16 10:10:45,599 - numba.core.ssa - DEBUG - on stmt: $80unary_negative.3 = unary(fn=, value=$78binary_add.2)\n", - "2024-10-16 10:10:45,600 - numba.core.ssa - DEBUG - on stmt: $82return_value.4 = cast(value=$80unary_negative.3)\n", - "2024-10-16 10:10:45,601 - numba.core.ssa - DEBUG - on stmt: return $82return_value.4\n", - "2024-10-16 10:10:45,601 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 84\n", - "2024-10-16 10:10:45,602 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,603 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,604 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 86\n", - "2024-10-16 10:10:45,605 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,605 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:45,606 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = src_dim_size != $const88.1\n", - "2024-10-16 10:10:45,607 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:45,608 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, npyimpl.py:222),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,609 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 102\n", - "2024-10-16 10:10:45,609 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 94\n", - "2024-10-16 10:10:45,610 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,611 - numba.core.ssa - DEBUG - on stmt: dest_shape[dest_index] = src_dim_size\n", - "2024-10-16 10:10:45,611 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,612 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 102\n", - "2024-10-16 10:10:45,613 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,614 - numba.core.ssa - DEBUG - on stmt: $const104.1 = const(int, 1)\n", - "2024-10-16 10:10:45,614 - numba.core.ssa - DEBUG - on stmt: $106inplace_add.2 = inplace_binop(fn=, immutable_fn=, lhs=src_index, rhs=$const104.1, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,615 - numba.core.ssa - DEBUG - on stmt: src_index = $106inplace_add.2\n", - "2024-10-16 10:10:45,616 - numba.core.ssa - DEBUG - on stmt: $const112.4 = const(int, 1)\n", - "2024-10-16 10:10:45,617 - numba.core.ssa - DEBUG - on stmt: $114inplace_add.5 = inplace_binop(fn=, immutable_fn=, lhs=dest_index, rhs=$const112.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,617 - numba.core.ssa - DEBUG - on stmt: dest_index = $114inplace_add.5\n", - "2024-10-16 10:10:45,618 - numba.core.ssa - DEBUG - on stmt: $122compare_op.8 = src_index < src_ndim\n", - "2024-10-16 10:10:45,619 - numba.core.ssa - DEBUG - on stmt: bool124 = global(bool: )\n", - "2024-10-16 10:10:45,620 - numba.core.ssa - DEBUG - on stmt: $124pred = call bool124($122compare_op.8, func=bool124, args=(Var($122compare_op.8, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,621 - numba.core.ssa - DEBUG - on stmt: branch $124pred, 34, 126\n", - "2024-10-16 10:10:45,621 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 126\n", - "2024-10-16 10:10:45,622 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,623 - numba.core.ssa - DEBUG - on stmt: $128return_value.1 = cast(value=dest_index)\n", - "2024-10-16 10:10:45,624 - numba.core.ssa - DEBUG - on stmt: return $128return_value.1\n", - "2024-10-16 10:10:45,626 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$106inplace_add.2': [],\n", - " '$114inplace_add.5': [],\n", - " '$122compare_op.8': [],\n", - " '$124pred': [],\n", - " '$128return_value.1': [],\n", - " '$12return_value.1': [],\n", - " '$30compare_op.6': [],\n", - " '$32pred': [],\n", - " '$54compare_op.8': [],\n", - " '$56pred': [],\n", - " '$62compare_op.2': [],\n", - " '$64pred': [],\n", - " '$6compare_op.2': [],\n", - " '$70compare_op.2': [],\n", - " '$72pred': [],\n", - " '$78binary_add.2': [],\n", - " '$80unary_negative.3': [],\n", - " '$82return_value.4': [],\n", - " '$8pred': [],\n", - " '$90compare_op.2': [],\n", - " '$92pred': [],\n", - " '$const10.0': [],\n", - " '$const104.1': [],\n", - " '$const112.4': [],\n", - " '$const52.7': [],\n", - " '$const68.1': [],\n", - " '$const76.1': [],\n", - " '$const88.1': [],\n", - " 'bool124': [],\n", - " 'bool32': [],\n", - " 'bool56': [],\n", - " 'bool64': [],\n", - " 'bool72': [],\n", - " 'bool8': [],\n", - " 'bool92': [],\n", - " 'dest_dim_size': [],\n", - " 'dest_index': [,\n", - " ],\n", - " 'dest_ndim': [],\n", - " 'dest_shape': [],\n", - " 'src_dim_size': [],\n", - " 'src_index': [,\n", - " ],\n", - " 'src_ndim': [],\n", - " 'src_shape': []})\n", - "2024-10-16 10:10:45,627 - numba.core.ssa - DEBUG - SSA violators {'dest_index', 'src_index'}\n", - "2024-10-16 10:10:45,627 - numba.core.ssa - DEBUG - Fix SSA violator on var dest_index\n", - "2024-10-16 10:10:45,628 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:45,629 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,630 - numba.core.ssa - DEBUG - on stmt: src_ndim = arg(0, name=src_ndim)\n", - "2024-10-16 10:10:45,630 - numba.core.ssa - DEBUG - on stmt: src_shape = arg(1, name=src_shape)\n", - "2024-10-16 10:10:45,631 - numba.core.ssa - DEBUG - on stmt: dest_ndim = arg(2, name=dest_ndim)\n", - "2024-10-16 10:10:45,632 - numba.core.ssa - DEBUG - on stmt: dest_shape = arg(3, name=dest_shape)\n", - "2024-10-16 10:10:45,633 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = src_ndim > dest_ndim\n", - "2024-10-16 10:10:45,633 - numba.core.ssa - DEBUG - on stmt: bool8 = global(bool: )\n", - "2024-10-16 10:10:45,634 - numba.core.ssa - DEBUG - on stmt: $8pred = call bool8($6compare_op.2, func=bool8, args=(Var($6compare_op.2, npyimpl.py:204),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,635 - numba.core.ssa - DEBUG - on stmt: branch $8pred, 10, 14\n", - "2024-10-16 10:10:45,636 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 10\n", - "2024-10-16 10:10:45,637 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,637 - numba.core.ssa - DEBUG - on stmt: $const10.0 = const(int, 0)\n", - "2024-10-16 10:10:45,638 - numba.core.ssa - DEBUG - on stmt: $12return_value.1 = cast(value=$const10.0)\n", - "2024-10-16 10:10:45,639 - numba.core.ssa - DEBUG - on stmt: return $12return_value.1\n", - "2024-10-16 10:10:45,640 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 14\n", - "2024-10-16 10:10:45,640 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,641 - numba.core.ssa - DEBUG - on stmt: src_index = const(int, 0)\n", - "2024-10-16 10:10:45,642 - numba.core.ssa - DEBUG - on stmt: dest_index = dest_ndim - src_ndim\n", - "2024-10-16 10:10:45,643 - numba.core.ssa - DEBUG - first assign: dest_index\n", - "2024-10-16 10:10:45,643 - numba.core.ssa - DEBUG - replaced with: dest_index = dest_ndim - src_ndim\n", - "2024-10-16 10:10:45,644 - numba.core.ssa - DEBUG - on stmt: $30compare_op.6 = src_index < src_ndim\n", - "2024-10-16 10:10:45,645 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:45,646 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.6, func=bool32, args=(Var($30compare_op.6, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,646 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 126\n", - "2024-10-16 10:10:45,647 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:45,648 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,648 - numba.core.ssa - DEBUG - on stmt: src_dim_size = getitem(value=src_shape, index=src_index, fn=)\n", - "2024-10-16 10:10:45,649 - numba.core.ssa - DEBUG - on stmt: dest_dim_size = getitem(value=dest_shape, index=dest_index, fn=)\n", - "2024-10-16 10:10:45,650 - numba.core.ssa - DEBUG - on stmt: $const52.7 = const(int, 1)\n", - "2024-10-16 10:10:45,651 - numba.core.ssa - DEBUG - on stmt: $54compare_op.8 = dest_dim_size != $const52.7\n", - "2024-10-16 10:10:45,651 - numba.core.ssa - DEBUG - on stmt: bool56 = global(bool: )\n", - "2024-10-16 10:10:45,652 - numba.core.ssa - DEBUG - on stmt: $56pred = call bool56($54compare_op.8, func=bool56, args=(Var($54compare_op.8, npyimpl.py:216),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,653 - numba.core.ssa - DEBUG - on stmt: branch $56pred, 58, 86\n", - "2024-10-16 10:10:45,654 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:45,654 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,655 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = src_dim_size != dest_dim_size\n", - "2024-10-16 10:10:45,656 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:45,657 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,657 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 84\n", - "2024-10-16 10:10:45,658 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:45,659 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,660 - numba.core.ssa - DEBUG - on stmt: $const68.1 = const(int, 1)\n", - "2024-10-16 10:10:45,660 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = src_dim_size != $const68.1\n", - "2024-10-16 10:10:45,661 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:45,662 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,663 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 84\n", - "2024-10-16 10:10:45,663 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:45,664 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,665 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(int, 1)\n", - "2024-10-16 10:10:45,666 - numba.core.ssa - DEBUG - on stmt: $78binary_add.2 = dest_index + $const76.1\n", - "2024-10-16 10:10:45,666 - numba.core.ssa - DEBUG - on stmt: $80unary_negative.3 = unary(fn=, value=$78binary_add.2)\n", - "2024-10-16 10:10:45,667 - numba.core.ssa - DEBUG - on stmt: $82return_value.4 = cast(value=$80unary_negative.3)\n", - "2024-10-16 10:10:45,667 - numba.core.ssa - DEBUG - on stmt: return $82return_value.4\n", - "2024-10-16 10:10:45,668 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 84\n", - "2024-10-16 10:10:45,669 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,670 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,670 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:45,671 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,672 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:45,673 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = src_dim_size != $const88.1\n", - "2024-10-16 10:10:45,673 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:45,674 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, npyimpl.py:222),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,675 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 102\n", - "2024-10-16 10:10:45,675 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:45,676 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,677 - numba.core.ssa - DEBUG - on stmt: dest_shape[dest_index] = src_dim_size\n", - "2024-10-16 10:10:45,677 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,678 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:45,679 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,679 - numba.core.ssa - DEBUG - on stmt: $const104.1 = const(int, 1)\n", - "2024-10-16 10:10:45,680 - numba.core.ssa - DEBUG - on stmt: $106inplace_add.2 = inplace_binop(fn=, immutable_fn=, lhs=src_index, rhs=$const104.1, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,681 - numba.core.ssa - DEBUG - on stmt: src_index = $106inplace_add.2\n", - "2024-10-16 10:10:45,682 - numba.core.ssa - DEBUG - on stmt: $const112.4 = const(int, 1)\n", - "2024-10-16 10:10:45,682 - numba.core.ssa - DEBUG - on stmt: $114inplace_add.5 = inplace_binop(fn=, immutable_fn=, lhs=dest_index, rhs=$const112.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,683 - numba.core.ssa - DEBUG - on stmt: dest_index = $114inplace_add.5\n", - "2024-10-16 10:10:45,684 - numba.core.ssa - DEBUG - replaced with: dest_index.1 = $114inplace_add.5\n", - "2024-10-16 10:10:45,684 - numba.core.ssa - DEBUG - on stmt: $122compare_op.8 = src_index < src_ndim\n", - "2024-10-16 10:10:45,685 - numba.core.ssa - DEBUG - on stmt: bool124 = global(bool: )\n", - "2024-10-16 10:10:45,686 - numba.core.ssa - DEBUG - on stmt: $124pred = call bool124($122compare_op.8, func=bool124, args=(Var($122compare_op.8, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,686 - numba.core.ssa - DEBUG - on stmt: branch $124pred, 34, 126\n", - "2024-10-16 10:10:45,687 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 126\n", - "2024-10-16 10:10:45,688 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,688 - numba.core.ssa - DEBUG - on stmt: $128return_value.1 = cast(value=dest_index)\n", - "2024-10-16 10:10:45,689 - numba.core.ssa - DEBUG - on stmt: return $128return_value.1\n", - "2024-10-16 10:10:45,690 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {14: [],\n", - " 102: []})\n", - "2024-10-16 10:10:45,691 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:45,691 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,692 - numba.core.ssa - DEBUG - on stmt: src_ndim = arg(0, name=src_ndim)\n", - "2024-10-16 10:10:45,693 - numba.core.ssa - DEBUG - on stmt: src_shape = arg(1, name=src_shape)\n", - "2024-10-16 10:10:45,694 - numba.core.ssa - DEBUG - on stmt: dest_ndim = arg(2, name=dest_ndim)\n", - "2024-10-16 10:10:45,694 - numba.core.ssa - DEBUG - on stmt: dest_shape = arg(3, name=dest_shape)\n", - "2024-10-16 10:10:45,695 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = src_ndim > dest_ndim\n", - "2024-10-16 10:10:45,695 - numba.core.ssa - DEBUG - on stmt: bool8 = global(bool: )\n", - "2024-10-16 10:10:45,696 - numba.core.ssa - DEBUG - on stmt: $8pred = call bool8($6compare_op.2, func=bool8, args=(Var($6compare_op.2, npyimpl.py:204),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,697 - numba.core.ssa - DEBUG - on stmt: branch $8pred, 10, 14\n", - "2024-10-16 10:10:45,697 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 10\n", - "2024-10-16 10:10:45,698 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,699 - numba.core.ssa - DEBUG - on stmt: $const10.0 = const(int, 0)\n", - "2024-10-16 10:10:45,699 - numba.core.ssa - DEBUG - on stmt: $12return_value.1 = cast(value=$const10.0)\n", - "2024-10-16 10:10:45,700 - numba.core.ssa - DEBUG - on stmt: return $12return_value.1\n", - "2024-10-16 10:10:45,700 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 14\n", - "2024-10-16 10:10:45,701 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,702 - numba.core.ssa - DEBUG - on stmt: src_index = const(int, 0)\n", - "2024-10-16 10:10:45,703 - numba.core.ssa - DEBUG - on stmt: dest_index = dest_ndim - src_ndim\n", - "2024-10-16 10:10:45,703 - numba.core.ssa - DEBUG - on stmt: $30compare_op.6 = src_index < src_ndim\n", - "2024-10-16 10:10:45,704 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:45,704 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.6, func=bool32, args=(Var($30compare_op.6, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,705 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 126\n", - "2024-10-16 10:10:45,706 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:45,706 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,707 - numba.core.ssa - DEBUG - on stmt: src_dim_size = getitem(value=src_shape, index=src_index, fn=)\n", - "2024-10-16 10:10:45,708 - numba.core.ssa - DEBUG - on stmt: dest_dim_size = getitem(value=dest_shape, index=dest_index, fn=)\n", - "2024-10-16 10:10:45,708 - numba.core.ssa - DEBUG - find_def var='dest_index' stmt=dest_dim_size = getitem(value=dest_shape, index=dest_index, fn=)\n", - "2024-10-16 10:10:45,709 - numba.core.ssa - DEBUG - find_def_from_top label 34\n", - "2024-10-16 10:10:45,710 - numba.core.ssa - DEBUG - insert phi node dest_index.2 = phi(incoming_values=[], incoming_blocks=[]) at 34\n", - "2024-10-16 10:10:45,710 - numba.core.ssa - DEBUG - find_def_from_bottom label 102\n", - "2024-10-16 10:10:45,711 - numba.core.ssa - DEBUG - incoming_def dest_index.1 = $114inplace_add.5\n", - "2024-10-16 10:10:45,712 - numba.core.ssa - DEBUG - find_def_from_bottom label 14\n", - "2024-10-16 10:10:45,712 - numba.core.ssa - DEBUG - incoming_def dest_index = dest_ndim - src_ndim\n", - "2024-10-16 10:10:45,713 - numba.core.ssa - DEBUG - replaced with: dest_dim_size = getitem(value=dest_shape, index=dest_index.2, fn=)\n", - "2024-10-16 10:10:45,713 - numba.core.ssa - DEBUG - on stmt: $const52.7 = const(int, 1)\n", - "2024-10-16 10:10:45,715 - numba.core.ssa - DEBUG - on stmt: $54compare_op.8 = dest_dim_size != $const52.7\n", - "2024-10-16 10:10:45,715 - numba.core.ssa - DEBUG - on stmt: bool56 = global(bool: )\n", - "2024-10-16 10:10:45,716 - numba.core.ssa - DEBUG - on stmt: $56pred = call bool56($54compare_op.8, func=bool56, args=(Var($54compare_op.8, npyimpl.py:216),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,717 - numba.core.ssa - DEBUG - on stmt: branch $56pred, 58, 86\n", - "2024-10-16 10:10:45,717 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:45,718 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,719 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = src_dim_size != dest_dim_size\n", - "2024-10-16 10:10:45,719 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:45,720 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,721 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 84\n", - "2024-10-16 10:10:45,721 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:45,722 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,723 - numba.core.ssa - DEBUG - on stmt: $const68.1 = const(int, 1)\n", - "2024-10-16 10:10:45,723 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = src_dim_size != $const68.1\n", - "2024-10-16 10:10:45,724 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:45,725 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,726 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 84\n", - "2024-10-16 10:10:45,726 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:45,727 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,728 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(int, 1)\n", - "2024-10-16 10:10:45,728 - numba.core.ssa - DEBUG - on stmt: $78binary_add.2 = dest_index + $const76.1\n", - "2024-10-16 10:10:45,729 - numba.core.ssa - DEBUG - find_def var='dest_index' stmt=$78binary_add.2 = dest_index + $const76.1\n", - "2024-10-16 10:10:45,730 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-10-16 10:10:45,730 - numba.core.ssa - DEBUG - idom 66 from label 74\n", - "2024-10-16 10:10:45,731 - numba.core.ssa - DEBUG - find_def_from_bottom label 66\n", - "2024-10-16 10:10:45,732 - numba.core.ssa - DEBUG - find_def_from_top label 66\n", - "2024-10-16 10:10:45,732 - numba.core.ssa - DEBUG - idom 58 from label 66\n", - "2024-10-16 10:10:45,733 - numba.core.ssa - DEBUG - find_def_from_bottom label 58\n", - "2024-10-16 10:10:45,734 - numba.core.ssa - DEBUG - find_def_from_top label 58\n", - "2024-10-16 10:10:45,735 - numba.core.ssa - DEBUG - idom 34 from label 58\n", - "2024-10-16 10:10:45,735 - numba.core.ssa - DEBUG - find_def_from_bottom label 34\n", - "2024-10-16 10:10:45,736 - numba.core.ssa - DEBUG - replaced with: $78binary_add.2 = dest_index.2 + $const76.1\n", - "2024-10-16 10:10:45,737 - numba.core.ssa - DEBUG - on stmt: $80unary_negative.3 = unary(fn=, value=$78binary_add.2)\n", - "2024-10-16 10:10:45,737 - numba.core.ssa - DEBUG - on stmt: $82return_value.4 = cast(value=$80unary_negative.3)\n", - "2024-10-16 10:10:45,738 - numba.core.ssa - DEBUG - on stmt: return $82return_value.4\n", - "2024-10-16 10:10:45,739 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 84\n", - "2024-10-16 10:10:45,739 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,740 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,741 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:45,742 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,742 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:45,743 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = src_dim_size != $const88.1\n", - "2024-10-16 10:10:45,744 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:45,744 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, npyimpl.py:222),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,745 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 102\n", - "2024-10-16 10:10:45,746 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:45,747 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,747 - numba.core.ssa - DEBUG - on stmt: dest_shape[dest_index] = src_dim_size\n", - "2024-10-16 10:10:45,748 - numba.core.ssa - DEBUG - find_def var='dest_index' stmt=dest_shape[dest_index] = src_dim_size\n", - "2024-10-16 10:10:45,749 - numba.core.ssa - DEBUG - find_def_from_top label 94\n", - "2024-10-16 10:10:45,749 - numba.core.ssa - DEBUG - idom 86 from label 94\n", - "2024-10-16 10:10:45,750 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-10-16 10:10:45,751 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-10-16 10:10:45,751 - numba.core.ssa - DEBUG - idom 34 from label 86\n", - "2024-10-16 10:10:45,752 - numba.core.ssa - DEBUG - find_def_from_bottom label 34\n", - "2024-10-16 10:10:45,753 - numba.core.ssa - DEBUG - replaced with: dest_shape[dest_index.2] = src_dim_size\n", - "2024-10-16 10:10:45,754 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,754 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:45,755 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,756 - numba.core.ssa - DEBUG - on stmt: $const104.1 = const(int, 1)\n", - "2024-10-16 10:10:45,756 - numba.core.ssa - DEBUG - on stmt: $106inplace_add.2 = inplace_binop(fn=, immutable_fn=, lhs=src_index, rhs=$const104.1, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,757 - numba.core.ssa - DEBUG - on stmt: src_index = $106inplace_add.2\n", - "2024-10-16 10:10:45,758 - numba.core.ssa - DEBUG - on stmt: $const112.4 = const(int, 1)\n", - "2024-10-16 10:10:45,758 - numba.core.ssa - DEBUG - on stmt: $114inplace_add.5 = inplace_binop(fn=, immutable_fn=, lhs=dest_index, rhs=$const112.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,759 - numba.core.ssa - DEBUG - find_def var='dest_index' stmt=$114inplace_add.5 = inplace_binop(fn=, immutable_fn=, lhs=dest_index, rhs=$const112.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,760 - numba.core.ssa - DEBUG - find_def_from_top label 102\n", - "2024-10-16 10:10:45,761 - numba.core.ssa - DEBUG - idom 34 from label 102\n", - "2024-10-16 10:10:45,761 - numba.core.ssa - DEBUG - find_def_from_bottom label 34\n", - "2024-10-16 10:10:45,762 - numba.core.ssa - DEBUG - replaced with: $114inplace_add.5 = inplace_binop(fn=, immutable_fn=, lhs=dest_index.2, rhs=$const112.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,763 - numba.core.ssa - DEBUG - on stmt: dest_index.1 = $114inplace_add.5\n", - "2024-10-16 10:10:45,763 - numba.core.ssa - DEBUG - on stmt: $122compare_op.8 = src_index < src_ndim\n", - "2024-10-16 10:10:45,764 - numba.core.ssa - DEBUG - on stmt: bool124 = global(bool: )\n", - "2024-10-16 10:10:45,765 - numba.core.ssa - DEBUG - on stmt: $124pred = call bool124($122compare_op.8, func=bool124, args=(Var($122compare_op.8, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,765 - numba.core.ssa - DEBUG - on stmt: branch $124pred, 34, 126\n", - "2024-10-16 10:10:45,766 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 126\n", - "2024-10-16 10:10:45,767 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,767 - numba.core.ssa - DEBUG - on stmt: $128return_value.1 = cast(value=dest_index)\n", - "2024-10-16 10:10:45,768 - numba.core.ssa - DEBUG - find_def var='dest_index' stmt=$128return_value.1 = cast(value=dest_index)\n", - "2024-10-16 10:10:45,769 - numba.core.ssa - DEBUG - find_def_from_top label 126\n", - "2024-10-16 10:10:45,769 - numba.core.ssa - DEBUG - insert phi node dest_index.3 = phi(incoming_values=[], incoming_blocks=[]) at 126\n", - "2024-10-16 10:10:45,770 - numba.core.ssa - DEBUG - find_def_from_bottom label 102\n", - "2024-10-16 10:10:45,771 - numba.core.ssa - DEBUG - incoming_def dest_index.1 = $114inplace_add.5\n", - "2024-10-16 10:10:45,772 - numba.core.ssa - DEBUG - find_def_from_bottom label 14\n", - "2024-10-16 10:10:45,772 - numba.core.ssa - DEBUG - incoming_def dest_index = dest_ndim - src_ndim\n", - "2024-10-16 10:10:45,773 - numba.core.ssa - DEBUG - replaced with: $128return_value.1 = cast(value=dest_index.3)\n", - "2024-10-16 10:10:45,774 - numba.core.ssa - DEBUG - on stmt: return $128return_value.1\n", - "2024-10-16 10:10:45,774 - numba.core.ssa - DEBUG - Fix SSA violator on var src_index\n", - "2024-10-16 10:10:45,775 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:45,776 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,777 - numba.core.ssa - DEBUG - on stmt: src_ndim = arg(0, name=src_ndim)\n", - "2024-10-16 10:10:45,777 - numba.core.ssa - DEBUG - on stmt: src_shape = arg(1, name=src_shape)\n", - "2024-10-16 10:10:45,778 - numba.core.ssa - DEBUG - on stmt: dest_ndim = arg(2, name=dest_ndim)\n", - "2024-10-16 10:10:45,779 - numba.core.ssa - DEBUG - on stmt: dest_shape = arg(3, name=dest_shape)\n", - "2024-10-16 10:10:45,779 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = src_ndim > dest_ndim\n", - "2024-10-16 10:10:45,780 - numba.core.ssa - DEBUG - on stmt: bool8 = global(bool: )\n", - "2024-10-16 10:10:45,781 - numba.core.ssa - DEBUG - on stmt: $8pred = call bool8($6compare_op.2, func=bool8, args=(Var($6compare_op.2, npyimpl.py:204),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,781 - numba.core.ssa - DEBUG - on stmt: branch $8pred, 10, 14\n", - "2024-10-16 10:10:45,782 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 10\n", - "2024-10-16 10:10:45,783 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,784 - numba.core.ssa - DEBUG - on stmt: $const10.0 = const(int, 0)\n", - "2024-10-16 10:10:45,784 - numba.core.ssa - DEBUG - on stmt: $12return_value.1 = cast(value=$const10.0)\n", - "2024-10-16 10:10:45,785 - numba.core.ssa - DEBUG - on stmt: return $12return_value.1\n", - "2024-10-16 10:10:45,786 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 14\n", - "2024-10-16 10:10:45,786 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,787 - numba.core.ssa - DEBUG - on stmt: src_index = const(int, 0)\n", - "2024-10-16 10:10:45,788 - numba.core.ssa - DEBUG - first assign: src_index\n", - "2024-10-16 10:10:45,788 - numba.core.ssa - DEBUG - replaced with: src_index = const(int, 0)\n", - "2024-10-16 10:10:45,789 - numba.core.ssa - DEBUG - on stmt: dest_index = dest_ndim - src_ndim\n", - "2024-10-16 10:10:45,790 - numba.core.ssa - DEBUG - on stmt: $30compare_op.6 = src_index < src_ndim\n", - "2024-10-16 10:10:45,790 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:45,791 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.6, func=bool32, args=(Var($30compare_op.6, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,792 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 126\n", - "2024-10-16 10:10:45,792 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:45,793 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,793 - numba.core.ssa - DEBUG - on stmt: dest_index.2 = phi(incoming_values=[Var(dest_index.1, npyimpl.py:226), Var(dest_index, npyimpl.py:210)], incoming_blocks=[102, 14])\n", - "2024-10-16 10:10:45,794 - numba.core.ssa - DEBUG - on stmt: src_dim_size = getitem(value=src_shape, index=src_index, fn=)\n", - "2024-10-16 10:10:45,795 - numba.core.ssa - DEBUG - on stmt: dest_dim_size = getitem(value=dest_shape, index=dest_index.2, fn=)\n", - "2024-10-16 10:10:45,795 - numba.core.ssa - DEBUG - on stmt: $const52.7 = const(int, 1)\n", - "2024-10-16 10:10:45,796 - numba.core.ssa - DEBUG - on stmt: $54compare_op.8 = dest_dim_size != $const52.7\n", - "2024-10-16 10:10:45,797 - numba.core.ssa - DEBUG - on stmt: bool56 = global(bool: )\n", - "2024-10-16 10:10:45,797 - numba.core.ssa - DEBUG - on stmt: $56pred = call bool56($54compare_op.8, func=bool56, args=(Var($54compare_op.8, npyimpl.py:216),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,798 - numba.core.ssa - DEBUG - on stmt: branch $56pred, 58, 86\n", - "2024-10-16 10:10:45,799 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:45,800 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,800 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = src_dim_size != dest_dim_size\n", - "2024-10-16 10:10:45,801 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:45,802 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,802 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 84\n", - "2024-10-16 10:10:45,803 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:45,804 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,804 - numba.core.ssa - DEBUG - on stmt: $const68.1 = const(int, 1)\n", - "2024-10-16 10:10:45,805 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = src_dim_size != $const68.1\n", - "2024-10-16 10:10:45,806 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:45,806 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,807 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 84\n", - "2024-10-16 10:10:45,808 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:45,809 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,809 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(int, 1)\n", - "2024-10-16 10:10:45,810 - numba.core.ssa - DEBUG - on stmt: $78binary_add.2 = dest_index.2 + $const76.1\n", - "2024-10-16 10:10:45,811 - numba.core.ssa - DEBUG - on stmt: $80unary_negative.3 = unary(fn=, value=$78binary_add.2)\n", - "2024-10-16 10:10:45,811 - numba.core.ssa - DEBUG - on stmt: $82return_value.4 = cast(value=$80unary_negative.3)\n", - "2024-10-16 10:10:45,812 - numba.core.ssa - DEBUG - on stmt: return $82return_value.4\n", - "2024-10-16 10:10:45,813 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 84\n", - "2024-10-16 10:10:45,813 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,814 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,815 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:45,815 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,816 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:45,817 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = src_dim_size != $const88.1\n", - "2024-10-16 10:10:45,817 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:45,818 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, npyimpl.py:222),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,819 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 102\n", - "2024-10-16 10:10:45,819 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:45,820 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,821 - numba.core.ssa - DEBUG - on stmt: dest_shape[dest_index.2] = src_dim_size\n", - "2024-10-16 10:10:45,821 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,822 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:45,823 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,823 - numba.core.ssa - DEBUG - on stmt: $const104.1 = const(int, 1)\n", - "2024-10-16 10:10:45,824 - numba.core.ssa - DEBUG - on stmt: $106inplace_add.2 = inplace_binop(fn=, immutable_fn=, lhs=src_index, rhs=$const104.1, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,825 - numba.core.ssa - DEBUG - on stmt: src_index = $106inplace_add.2\n", - "2024-10-16 10:10:45,825 - numba.core.ssa - DEBUG - replaced with: src_index.1 = $106inplace_add.2\n", - "2024-10-16 10:10:45,826 - numba.core.ssa - DEBUG - on stmt: $const112.4 = const(int, 1)\n", - "2024-10-16 10:10:45,827 - numba.core.ssa - DEBUG - on stmt: $114inplace_add.5 = inplace_binop(fn=, immutable_fn=, lhs=dest_index.2, rhs=$const112.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,827 - numba.core.ssa - DEBUG - on stmt: dest_index.1 = $114inplace_add.5\n", - "2024-10-16 10:10:45,828 - numba.core.ssa - DEBUG - on stmt: $122compare_op.8 = src_index < src_ndim\n", - "2024-10-16 10:10:45,829 - numba.core.ssa - DEBUG - on stmt: bool124 = global(bool: )\n", - "2024-10-16 10:10:45,829 - numba.core.ssa - DEBUG - on stmt: $124pred = call bool124($122compare_op.8, func=bool124, args=(Var($122compare_op.8, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,830 - numba.core.ssa - DEBUG - on stmt: branch $124pred, 34, 126\n", - "2024-10-16 10:10:45,831 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 126\n", - "2024-10-16 10:10:45,831 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,832 - numba.core.ssa - DEBUG - on stmt: dest_index.3 = phi(incoming_values=[Var(dest_index.1, npyimpl.py:226), Var(dest_index, npyimpl.py:210)], incoming_blocks=[102, 14])\n", - "2024-10-16 10:10:45,833 - numba.core.ssa - DEBUG - on stmt: $128return_value.1 = cast(value=dest_index.3)\n", - "2024-10-16 10:10:45,834 - numba.core.ssa - DEBUG - on stmt: return $128return_value.1\n", - "2024-10-16 10:10:45,834 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {14: [],\n", - " 102: []})\n", - "2024-10-16 10:10:45,835 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:45,836 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,836 - numba.core.ssa - DEBUG - on stmt: src_ndim = arg(0, name=src_ndim)\n", - "2024-10-16 10:10:45,837 - numba.core.ssa - DEBUG - on stmt: src_shape = arg(1, name=src_shape)\n", - "2024-10-16 10:10:45,838 - numba.core.ssa - DEBUG - on stmt: dest_ndim = arg(2, name=dest_ndim)\n", - "2024-10-16 10:10:45,838 - numba.core.ssa - DEBUG - on stmt: dest_shape = arg(3, name=dest_shape)\n", - "2024-10-16 10:10:45,839 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = src_ndim > dest_ndim\n", - "2024-10-16 10:10:45,840 - numba.core.ssa - DEBUG - on stmt: bool8 = global(bool: )\n", - "2024-10-16 10:10:45,840 - numba.core.ssa - DEBUG - on stmt: $8pred = call bool8($6compare_op.2, func=bool8, args=(Var($6compare_op.2, npyimpl.py:204),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,841 - numba.core.ssa - DEBUG - on stmt: branch $8pred, 10, 14\n", - "2024-10-16 10:10:45,842 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 10\n", - "2024-10-16 10:10:45,842 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,843 - numba.core.ssa - DEBUG - on stmt: $const10.0 = const(int, 0)\n", - "2024-10-16 10:10:45,844 - numba.core.ssa - DEBUG - on stmt: $12return_value.1 = cast(value=$const10.0)\n", - "2024-10-16 10:10:45,844 - numba.core.ssa - DEBUG - on stmt: return $12return_value.1\n", - "2024-10-16 10:10:45,845 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 14\n", - "2024-10-16 10:10:45,846 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,846 - numba.core.ssa - DEBUG - on stmt: src_index = const(int, 0)\n", - "2024-10-16 10:10:45,847 - numba.core.ssa - DEBUG - on stmt: dest_index = dest_ndim - src_ndim\n", - "2024-10-16 10:10:45,848 - numba.core.ssa - DEBUG - on stmt: $30compare_op.6 = src_index < src_ndim\n", - "2024-10-16 10:10:45,848 - numba.core.ssa - DEBUG - find_def var='src_index' stmt=$30compare_op.6 = src_index < src_ndim\n", - "2024-10-16 10:10:45,849 - numba.core.ssa - DEBUG - on stmt: bool32 = global(bool: )\n", - "2024-10-16 10:10:45,853 - numba.core.ssa - DEBUG - on stmt: $32pred = call bool32($30compare_op.6, func=bool32, args=(Var($30compare_op.6, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,877 - numba.core.ssa - DEBUG - on stmt: branch $32pred, 34, 126\n", - "2024-10-16 10:10:45,877 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:45,877 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,878 - numba.core.ssa - DEBUG - on stmt: dest_index.2 = phi(incoming_values=[Var(dest_index.1, npyimpl.py:226), Var(dest_index, npyimpl.py:210)], incoming_blocks=[102, 14])\n", - "2024-10-16 10:10:45,878 - numba.core.ssa - DEBUG - on stmt: src_dim_size = getitem(value=src_shape, index=src_index, fn=)\n", - "2024-10-16 10:10:45,879 - numba.core.ssa - DEBUG - find_def var='src_index' stmt=src_dim_size = getitem(value=src_shape, index=src_index, fn=)\n", - "2024-10-16 10:10:45,879 - numba.core.ssa - DEBUG - find_def_from_top label 34\n", - "2024-10-16 10:10:45,880 - numba.core.ssa - DEBUG - insert phi node src_index.2 = phi(incoming_values=[], incoming_blocks=[]) at 34\n", - "2024-10-16 10:10:45,880 - numba.core.ssa - DEBUG - find_def_from_bottom label 102\n", - "2024-10-16 10:10:45,880 - numba.core.ssa - DEBUG - incoming_def src_index.1 = $106inplace_add.2\n", - "2024-10-16 10:10:45,881 - numba.core.ssa - DEBUG - find_def_from_bottom label 14\n", - "2024-10-16 10:10:45,881 - numba.core.ssa - DEBUG - incoming_def src_index = const(int, 0)\n", - "2024-10-16 10:10:45,882 - numba.core.ssa - DEBUG - replaced with: src_dim_size = getitem(value=src_shape, index=src_index.2, fn=)\n", - "2024-10-16 10:10:45,882 - numba.core.ssa - DEBUG - on stmt: dest_dim_size = getitem(value=dest_shape, index=dest_index.2, fn=)\n", - "2024-10-16 10:10:45,883 - numba.core.ssa - DEBUG - on stmt: $const52.7 = const(int, 1)\n", - "2024-10-16 10:10:45,883 - numba.core.ssa - DEBUG - on stmt: $54compare_op.8 = dest_dim_size != $const52.7\n", - "2024-10-16 10:10:45,902 - numba.core.ssa - DEBUG - on stmt: bool56 = global(bool: )\n", - "2024-10-16 10:10:45,910 - numba.core.ssa - DEBUG - on stmt: $56pred = call bool56($54compare_op.8, func=bool56, args=(Var($54compare_op.8, npyimpl.py:216),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,911 - numba.core.ssa - DEBUG - on stmt: branch $56pred, 58, 86\n", - "2024-10-16 10:10:45,911 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 58\n", - "2024-10-16 10:10:45,912 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,912 - numba.core.ssa - DEBUG - on stmt: $62compare_op.2 = src_dim_size != dest_dim_size\n", - "2024-10-16 10:10:45,913 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:10:45,914 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.2, func=bool64, args=(Var($62compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,915 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 84\n", - "2024-10-16 10:10:45,916 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:10:45,916 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,917 - numba.core.ssa - DEBUG - on stmt: $const68.1 = const(int, 1)\n", - "2024-10-16 10:10:45,917 - numba.core.ssa - DEBUG - on stmt: $70compare_op.2 = src_dim_size != $const68.1\n", - "2024-10-16 10:10:45,918 - numba.core.ssa - DEBUG - on stmt: bool72 = global(bool: )\n", - "2024-10-16 10:10:45,919 - numba.core.ssa - DEBUG - on stmt: $72pred = call bool72($70compare_op.2, func=bool72, args=(Var($70compare_op.2, npyimpl.py:220),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,919 - numba.core.ssa - DEBUG - on stmt: branch $72pred, 74, 84\n", - "2024-10-16 10:10:45,920 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:10:45,921 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,921 - numba.core.ssa - DEBUG - on stmt: $const76.1 = const(int, 1)\n", - "2024-10-16 10:10:45,922 - numba.core.ssa - DEBUG - on stmt: $78binary_add.2 = dest_index.2 + $const76.1\n", - "2024-10-16 10:10:45,922 - numba.core.ssa - DEBUG - on stmt: $80unary_negative.3 = unary(fn=, value=$78binary_add.2)\n", - "2024-10-16 10:10:45,923 - numba.core.ssa - DEBUG - on stmt: $82return_value.4 = cast(value=$80unary_negative.3)\n", - "2024-10-16 10:10:45,924 - numba.core.ssa - DEBUG - on stmt: return $82return_value.4\n", - "2024-10-16 10:10:45,924 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 84\n", - "2024-10-16 10:10:45,925 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,925 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,926 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:10:45,927 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,927 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:10:45,928 - numba.core.ssa - DEBUG - on stmt: $90compare_op.2 = src_dim_size != $const88.1\n", - "2024-10-16 10:10:45,929 - numba.core.ssa - DEBUG - on stmt: bool92 = global(bool: )\n", - "2024-10-16 10:10:45,929 - numba.core.ssa - DEBUG - on stmt: $92pred = call bool92($90compare_op.2, func=bool92, args=(Var($90compare_op.2, npyimpl.py:222),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,930 - numba.core.ssa - DEBUG - on stmt: branch $92pred, 94, 102\n", - "2024-10-16 10:10:45,931 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:10:45,931 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,932 - numba.core.ssa - DEBUG - on stmt: dest_shape[dest_index.2] = src_dim_size\n", - "2024-10-16 10:10:45,933 - numba.core.ssa - DEBUG - on stmt: jump 102\n", - "2024-10-16 10:10:45,933 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 102\n", - "2024-10-16 10:10:45,934 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,934 - numba.core.ssa - DEBUG - on stmt: $const104.1 = const(int, 1)\n", - "2024-10-16 10:10:45,935 - numba.core.ssa - DEBUG - on stmt: $106inplace_add.2 = inplace_binop(fn=, immutable_fn=, lhs=src_index, rhs=$const104.1, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,936 - numba.core.ssa - DEBUG - find_def var='src_index' stmt=$106inplace_add.2 = inplace_binop(fn=, immutable_fn=, lhs=src_index, rhs=$const104.1, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,937 - numba.core.ssa - DEBUG - find_def_from_top label 102\n", - "2024-10-16 10:10:45,937 - numba.core.ssa - DEBUG - idom 34 from label 102\n", - "2024-10-16 10:10:45,938 - numba.core.ssa - DEBUG - find_def_from_bottom label 34\n", - "2024-10-16 10:10:45,938 - numba.core.ssa - DEBUG - replaced with: $106inplace_add.2 = inplace_binop(fn=, immutable_fn=, lhs=src_index.2, rhs=$const104.1, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,939 - numba.core.ssa - DEBUG - on stmt: src_index.1 = $106inplace_add.2\n", - "2024-10-16 10:10:45,940 - numba.core.ssa - DEBUG - on stmt: $const112.4 = const(int, 1)\n", - "2024-10-16 10:10:45,940 - numba.core.ssa - DEBUG - on stmt: $114inplace_add.5 = inplace_binop(fn=, immutable_fn=, lhs=dest_index.2, rhs=$const112.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:45,941 - numba.core.ssa - DEBUG - on stmt: dest_index.1 = $114inplace_add.5\n", - "2024-10-16 10:10:45,941 - numba.core.ssa - DEBUG - on stmt: $122compare_op.8 = src_index < src_ndim\n", - "2024-10-16 10:10:45,942 - numba.core.ssa - DEBUG - find_def var='src_index' stmt=$122compare_op.8 = src_index < src_ndim\n", - "2024-10-16 10:10:45,942 - numba.core.ssa - DEBUG - replaced with: $122compare_op.8 = src_index.1 < src_ndim\n", - "2024-10-16 10:10:45,943 - numba.core.ssa - DEBUG - on stmt: bool124 = global(bool: )\n", - "2024-10-16 10:10:45,943 - numba.core.ssa - DEBUG - on stmt: $124pred = call bool124($122compare_op.8, func=bool124, args=(Var($122compare_op.8, npyimpl.py:211),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:45,944 - numba.core.ssa - DEBUG - on stmt: branch $124pred, 34, 126\n", - "2024-10-16 10:10:45,944 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 126\n", - "2024-10-16 10:10:45,945 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:45,945 - numba.core.ssa - DEBUG - on stmt: dest_index.3 = phi(incoming_values=[Var(dest_index.1, npyimpl.py:226), Var(dest_index, npyimpl.py:210)], incoming_blocks=[102, 14])\n", - "2024-10-16 10:10:45,946 - numba.core.ssa - DEBUG - on stmt: $128return_value.1 = cast(value=dest_index.3)\n", - "2024-10-16 10:10:45,946 - numba.core.ssa - DEBUG - on stmt: return $128return_value.1\n", - "2024-10-16 10:10:46,097 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=166)\n", - " 2\tLOAD_DEREF(arg=0, lineno=167)\n", - " 4\tSTORE_FAST(arg=1, lineno=167)\n", - " 6\tLOAD_GLOBAL(arg=0, lineno=168)\n", - " 8\tLOAD_METHOD(arg=1, lineno=168)\n", - " 10\tLOAD_FAST(arg=0, lineno=168)\n", - " 12\tCALL_METHOD(arg=1, lineno=168)\n", - " 14\tGET_ITER(arg=None, lineno=168)\n", - "> 16\tFOR_ITER(arg=8, lineno=168)\n", - " 18\tSTORE_FAST(arg=2, lineno=168)\n", - " 20\tLOAD_FAST(arg=1, lineno=169)\n", - " 22\tLOAD_FAST(arg=2, lineno=169)\n", - " 24\tLOAD_METHOD(arg=2, lineno=169)\n", - " 26\tCALL_METHOD(arg=0, lineno=169)\n", - " 28\tINPLACE_ADD(arg=None, lineno=169)\n", - " 30\tSTORE_FAST(arg=1, lineno=169)\n", - " 32\tJUMP_ABSOLUTE(arg=9, lineno=169)\n", - "> 34\tLOAD_FAST(arg=1, lineno=170)\n", - " 36\tRETURN_VALUE(arg=None, lineno=170)\n", - "2024-10-16 10:10:46,098 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:46,099 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:46,099 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:46,100 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=166)\n", - "2024-10-16 10:10:46,101 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,101 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_DEREF(arg=0, lineno=167)\n", - "2024-10-16 10:10:46,102 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,103 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=STORE_FAST(arg=1, lineno=167)\n", - "2024-10-16 10:10:46,104 - numba.core.byteflow - DEBUG - stack ['$2load_deref.0']\n", - "2024-10-16 10:10:46,104 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_GLOBAL(arg=0, lineno=168)\n", - "2024-10-16 10:10:46,105 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,106 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=1, lineno=168)\n", - "2024-10-16 10:10:46,106 - numba.core.byteflow - DEBUG - stack ['$6load_global.1']\n", - "2024-10-16 10:10:46,107 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_FAST(arg=0, lineno=168)\n", - "2024-10-16 10:10:46,107 - numba.core.byteflow - DEBUG - stack ['$8load_method.2']\n", - "2024-10-16 10:10:46,108 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=CALL_METHOD(arg=1, lineno=168)\n", - "2024-10-16 10:10:46,109 - numba.core.byteflow - DEBUG - stack ['$8load_method.2', '$arr10.3']\n", - "2024-10-16 10:10:46,109 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=GET_ITER(arg=None, lineno=168)\n", - "2024-10-16 10:10:46,110 - numba.core.byteflow - DEBUG - stack ['$12call_method.4']\n", - "2024-10-16 10:10:46,111 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=16, stack=('$14get_iter.5',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:46,112 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=16 nstack_initial=1)])\n", - "2024-10-16 10:10:46,112 - numba.core.byteflow - DEBUG - stack: ['$phi16.0']\n", - "2024-10-16 10:10:46,113 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=16 nstack_initial=1)\n", - "2024-10-16 10:10:46,114 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=FOR_ITER(arg=8, lineno=168)\n", - "2024-10-16 10:10:46,114 - numba.core.byteflow - DEBUG - stack ['$phi16.0']\n", - "2024-10-16 10:10:46,115 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=34, stack=(), blockstack=(), npush=0), Edge(pc=18, stack=('$phi16.0', '$16for_iter.2'), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:46,116 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=34 nstack_initial=0), State(pc_initial=18 nstack_initial=2)])\n", - "2024-10-16 10:10:46,117 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:46,117 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=34 nstack_initial=0)\n", - "2024-10-16 10:10:46,118 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=1, lineno=170)\n", - "2024-10-16 10:10:46,119 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,119 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=RETURN_VALUE(arg=None, lineno=170)\n", - "2024-10-16 10:10:46,120 - numba.core.byteflow - DEBUG - stack ['$c34.0']\n", - "2024-10-16 10:10:46,121 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:46,121 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=18 nstack_initial=2)])\n", - "2024-10-16 10:10:46,122 - numba.core.byteflow - DEBUG - stack: ['$phi18.0', '$phi18.1']\n", - "2024-10-16 10:10:46,123 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=18 nstack_initial=2)\n", - "2024-10-16 10:10:46,123 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=STORE_FAST(arg=2, lineno=168)\n", - "2024-10-16 10:10:46,124 - numba.core.byteflow - DEBUG - stack ['$phi18.0', '$phi18.1']\n", - "2024-10-16 10:10:46,125 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=1, lineno=169)\n", - "2024-10-16 10:10:46,125 - numba.core.byteflow - DEBUG - stack ['$phi18.0']\n", - "2024-10-16 10:10:46,126 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=2, lineno=169)\n", - "2024-10-16 10:10:46,127 - numba.core.byteflow - DEBUG - stack ['$phi18.0', '$c20.2']\n", - "2024-10-16 10:10:46,127 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_METHOD(arg=2, lineno=169)\n", - "2024-10-16 10:10:46,128 - numba.core.byteflow - DEBUG - stack ['$phi18.0', '$c20.2', '$v22.3']\n", - "2024-10-16 10:10:46,129 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=CALL_METHOD(arg=0, lineno=169)\n", - "2024-10-16 10:10:46,129 - numba.core.byteflow - DEBUG - stack ['$phi18.0', '$c20.2', '$24load_method.4']\n", - "2024-10-16 10:10:46,130 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=INPLACE_ADD(arg=None, lineno=169)\n", - "2024-10-16 10:10:46,131 - numba.core.byteflow - DEBUG - stack ['$phi18.0', '$c20.2', '$26call_method.5']\n", - "2024-10-16 10:10:46,132 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=STORE_FAST(arg=1, lineno=169)\n", - "2024-10-16 10:10:46,132 - numba.core.byteflow - DEBUG - stack ['$phi18.0', '$28inplace_add.6']\n", - "2024-10-16 10:10:46,133 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=JUMP_ABSOLUTE(arg=9, lineno=169)\n", - "2024-10-16 10:10:46,134 - numba.core.byteflow - DEBUG - stack ['$phi18.0']\n", - "2024-10-16 10:10:46,134 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=16, stack=('$phi18.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:46,135 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=16 nstack_initial=1)])\n", - "2024-10-16 10:10:46,136 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:46,137 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=16 nstack_initial=1): {'$phi16.0'},\n", - " State(pc_initial=18 nstack_initial=2): {'$phi18.1'},\n", - " State(pc_initial=34 nstack_initial=0): set()})\n", - "2024-10-16 10:10:46,137 - numba.core.byteflow - DEBUG - defmap: {'$phi16.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi18.1': State(pc_initial=16 nstack_initial=1)}\n", - "2024-10-16 10:10:46,138 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi16.0': {('$14get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi18.0', State(pc_initial=18 nstack_initial=2))},\n", - " '$phi18.0': {('$phi16.0', State(pc_initial=16 nstack_initial=1))},\n", - " '$phi18.1': {('$16for_iter.2',\n", - " State(pc_initial=16 nstack_initial=1))}})\n", - "2024-10-16 10:10:46,139 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi16.0': {('$14get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi16.0', State(pc_initial=16 nstack_initial=1))},\n", - " '$phi18.0': {('$14get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi18.1': {('$16for_iter.2',\n", - " State(pc_initial=16 nstack_initial=1))}})\n", - "2024-10-16 10:10:46,140 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi16.0': {('$14get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi18.0': {('$14get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi18.1': {('$16for_iter.2',\n", - " State(pc_initial=16 nstack_initial=1))}})\n", - "2024-10-16 10:10:46,141 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi16.0': {('$14get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi18.0': {('$14get_iter.5',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi18.1': {('$16for_iter.2',\n", - " State(pc_initial=16 nstack_initial=1))}})\n", - "2024-10-16 10:10:46,142 - numba.core.byteflow - DEBUG - keep phismap: {'$phi16.0': {('$14get_iter.5', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi18.1': {('$16for_iter.2', State(pc_initial=16 nstack_initial=1))}}\n", - "2024-10-16 10:10:46,143 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi16.0': '$14get_iter.5'},\n", - " State(pc_initial=16 nstack_initial=1): {'$phi18.1': '$16for_iter.2'}})\n", - "2024-10-16 10:10:46,144 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:46,144 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_deref.0'}), (4, {'value': '$2load_deref.0'}), (6, {'res': '$6load_global.1'}), (8, {'item': '$6load_global.1', 'res': '$8load_method.2'}), (10, {'res': '$arr10.3'}), (12, {'func': '$8load_method.2', 'args': ['$arr10.3'], 'res': '$12call_method.4'}), (14, {'value': '$12call_method.4', 'res': '$14get_iter.5'})), outgoing_phis={'$phi16.0': '$14get_iter.5'}, blockstack=(), active_try_block=None, outgoing_edgepushed={16: ('$14get_iter.5',)})\n", - "2024-10-16 10:10:46,145 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=16 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((16, {'iterator': '$phi16.0', 'pair': '$16for_iter.1', 'indval': '$16for_iter.2', 'pred': '$16for_iter.3'}),), outgoing_phis={'$phi18.1': '$16for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={34: (), 18: ('$phi16.0', '$16for_iter.2')})\n", - "2024-10-16 10:10:46,146 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=18 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((18, {'value': '$phi18.1'}), (20, {'res': '$c20.2'}), (22, {'res': '$v22.3'}), (24, {'item': '$v22.3', 'res': '$24load_method.4'}), (26, {'func': '$24load_method.4', 'args': [], 'res': '$26call_method.5'}), (28, {'lhs': '$c20.2', 'rhs': '$26call_method.5', 'res': '$28inplace_add.6'}), (30, {'value': '$28inplace_add.6'}), (32, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={16: ('$phi18.0',)})\n", - "2024-10-16 10:10:46,147 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=34 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((34, {'res': '$c34.0'}), (36, {'retval': '$c34.0', 'castval': '$36return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:46,149 - numba.core.interpreter - DEBUG - label 0:\n", - " arr = arg(0, name=arr) ['arr']\n", - " c = freevar(zero: 0) ['c']\n", - " $6load_global.1 = global(np: ) ['$6load_global.1']\n", - " $8load_method.2 = getattr(value=$6load_global.1, attr=nditer) ['$6load_global.1', '$8load_method.2']\n", - " $12call_method.4 = call $8load_method.2(arr, func=$8load_method.2, args=[Var(arr, arraymath.py:166)], kws=(), vararg=None, varkwarg=None, target=None) ['$12call_method.4', '$8load_method.2', 'arr']\n", - " $14get_iter.5 = getiter(value=$12call_method.4) ['$12call_method.4', '$14get_iter.5']\n", - " $phi16.0 = $14get_iter.5 ['$14get_iter.5', '$phi16.0']\n", - " jump 16 []\n", - "label 16:\n", - " $16for_iter.1 = iternext(value=$phi16.0) ['$16for_iter.1', '$phi16.0']\n", - " $16for_iter.2 = pair_first(value=$16for_iter.1) ['$16for_iter.1', '$16for_iter.2']\n", - " $16for_iter.3 = pair_second(value=$16for_iter.1) ['$16for_iter.1', '$16for_iter.3']\n", - " $phi18.1 = $16for_iter.2 ['$16for_iter.2', '$phi18.1']\n", - " branch $16for_iter.3, 18, 34 ['$16for_iter.3']\n", - "label 18:\n", - " v = $phi18.1 ['$phi18.1', 'v']\n", - " $24load_method.4 = getattr(value=v, attr=item) ['$24load_method.4', 'v']\n", - " $26call_method.5 = call $24load_method.4(func=$24load_method.4, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$24load_method.4', '$26call_method.5']\n", - " $28inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=c, rhs=$26call_method.5, static_lhs=Undefined, static_rhs=Undefined) ['$26call_method.5', '$28inplace_add.6', 'c']\n", - " c = $28inplace_add.6 ['$28inplace_add.6', 'c']\n", - " jump 16 []\n", - "label 34:\n", - " $36return_value.1 = cast(value=c) ['$36return_value.1', 'c']\n", - " return $36return_value.1 ['$36return_value.1']\n", - "\n", - "2024-10-16 10:10:46,205 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:46,206 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,206 - numba.core.ssa - DEBUG - on stmt: arr = arg(0, name=arr)\n", - "2024-10-16 10:10:46,207 - numba.core.ssa - DEBUG - on stmt: c = freevar(zero: 0)\n", - "2024-10-16 10:10:46,208 - numba.core.ssa - DEBUG - on stmt: $6load_global.1 = global(np: )\n", - "2024-10-16 10:10:46,209 - numba.core.ssa - DEBUG - on stmt: $8load_method.2 = getattr(value=$6load_global.1, attr=nditer)\n", - "2024-10-16 10:10:46,210 - numba.core.ssa - DEBUG - on stmt: $12call_method.4 = call $8load_method.2(arr, func=$8load_method.2, args=[Var(arr, arraymath.py:166)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:46,211 - numba.core.ssa - DEBUG - on stmt: $14get_iter.5 = getiter(value=$12call_method.4)\n", - "2024-10-16 10:10:46,211 - numba.core.ssa - DEBUG - on stmt: $phi16.0 = $14get_iter.5\n", - "2024-10-16 10:10:46,212 - numba.core.ssa - DEBUG - on stmt: jump 16\n", - "2024-10-16 10:10:46,213 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 16\n", - "2024-10-16 10:10:46,214 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,215 - numba.core.ssa - DEBUG - on stmt: $16for_iter.1 = iternext(value=$phi16.0)\n", - "2024-10-16 10:10:46,215 - numba.core.ssa - DEBUG - on stmt: $16for_iter.2 = pair_first(value=$16for_iter.1)\n", - "2024-10-16 10:10:46,216 - numba.core.ssa - DEBUG - on stmt: $16for_iter.3 = pair_second(value=$16for_iter.1)\n", - "2024-10-16 10:10:46,217 - numba.core.ssa - DEBUG - on stmt: $phi18.1 = $16for_iter.2\n", - "2024-10-16 10:10:46,218 - numba.core.ssa - DEBUG - on stmt: branch $16for_iter.3, 18, 34\n", - "2024-10-16 10:10:46,219 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 18\n", - "2024-10-16 10:10:46,220 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,220 - numba.core.ssa - DEBUG - on stmt: v = $phi18.1\n", - "2024-10-16 10:10:46,221 - numba.core.ssa - DEBUG - on stmt: $24load_method.4 = getattr(value=v, attr=item)\n", - "2024-10-16 10:10:46,222 - numba.core.ssa - DEBUG - on stmt: $26call_method.5 = call $24load_method.4(func=$24load_method.4, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:46,223 - numba.core.ssa - DEBUG - on stmt: $28inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=c, rhs=$26call_method.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:46,224 - numba.core.ssa - DEBUG - on stmt: c = $28inplace_add.6\n", - "2024-10-16 10:10:46,224 - numba.core.ssa - DEBUG - on stmt: jump 16\n", - "2024-10-16 10:10:46,225 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 34\n", - "2024-10-16 10:10:46,226 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,227 - numba.core.ssa - DEBUG - on stmt: $36return_value.1 = cast(value=c)\n", - "2024-10-16 10:10:46,228 - numba.core.ssa - DEBUG - on stmt: return $36return_value.1\n", - "2024-10-16 10:10:46,229 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12call_method.4': [],\n", - " '$14get_iter.5': [],\n", - " '$16for_iter.1': [],\n", - " '$16for_iter.2': [],\n", - " '$16for_iter.3': [],\n", - " '$24load_method.4': [],\n", - " '$26call_method.5': [],\n", - " '$28inplace_add.6': [],\n", - " '$36return_value.1': [],\n", - " '$6load_global.1': [],\n", - " '$8load_method.2': [],\n", - " '$phi16.0': [],\n", - " '$phi18.1': [],\n", - " 'arr': [],\n", - " 'c': [,\n", - " ],\n", - " 'v': []})\n", - "2024-10-16 10:10:46,230 - numba.core.ssa - DEBUG - SSA violators {'c'}\n", - "2024-10-16 10:10:46,230 - numba.core.ssa - DEBUG - Fix SSA violator on var c\n", - "2024-10-16 10:10:46,231 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:46,232 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,233 - numba.core.ssa - DEBUG - on stmt: arr = arg(0, name=arr)\n", - "2024-10-16 10:10:46,234 - numba.core.ssa - DEBUG - on stmt: c = freevar(zero: 0)\n", - "2024-10-16 10:10:46,234 - numba.core.ssa - DEBUG - first assign: c\n", - "2024-10-16 10:10:46,235 - numba.core.ssa - DEBUG - replaced with: c = freevar(zero: 0)\n", - "2024-10-16 10:10:46,236 - numba.core.ssa - DEBUG - on stmt: $6load_global.1 = global(np: )\n", - "2024-10-16 10:10:46,237 - numba.core.ssa - DEBUG - on stmt: $8load_method.2 = getattr(value=$6load_global.1, attr=nditer)\n", - "2024-10-16 10:10:46,238 - numba.core.ssa - DEBUG - on stmt: $12call_method.4 = call $8load_method.2(arr, func=$8load_method.2, args=[Var(arr, arraymath.py:166)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:46,239 - numba.core.ssa - DEBUG - on stmt: $14get_iter.5 = getiter(value=$12call_method.4)\n", - "2024-10-16 10:10:46,240 - numba.core.ssa - DEBUG - on stmt: $phi16.0 = $14get_iter.5\n", - "2024-10-16 10:10:46,241 - numba.core.ssa - DEBUG - on stmt: jump 16\n", - "2024-10-16 10:10:46,242 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 16\n", - "2024-10-16 10:10:46,242 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,243 - numba.core.ssa - DEBUG - on stmt: $16for_iter.1 = iternext(value=$phi16.0)\n", - "2024-10-16 10:10:46,244 - numba.core.ssa - DEBUG - on stmt: $16for_iter.2 = pair_first(value=$16for_iter.1)\n", - "2024-10-16 10:10:46,245 - numba.core.ssa - DEBUG - on stmt: $16for_iter.3 = pair_second(value=$16for_iter.1)\n", - "2024-10-16 10:10:46,246 - numba.core.ssa - DEBUG - on stmt: $phi18.1 = $16for_iter.2\n", - "2024-10-16 10:10:46,247 - numba.core.ssa - DEBUG - on stmt: branch $16for_iter.3, 18, 34\n", - "2024-10-16 10:10:46,247 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:46,248 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,249 - numba.core.ssa - DEBUG - on stmt: v = $phi18.1\n", - "2024-10-16 10:10:46,250 - numba.core.ssa - DEBUG - on stmt: $24load_method.4 = getattr(value=v, attr=item)\n", - "2024-10-16 10:10:46,251 - numba.core.ssa - DEBUG - on stmt: $26call_method.5 = call $24load_method.4(func=$24load_method.4, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:46,252 - numba.core.ssa - DEBUG - on stmt: $28inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=c, rhs=$26call_method.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:46,253 - numba.core.ssa - DEBUG - on stmt: c = $28inplace_add.6\n", - "2024-10-16 10:10:46,253 - numba.core.ssa - DEBUG - replaced with: c.1 = $28inplace_add.6\n", - "2024-10-16 10:10:46,254 - numba.core.ssa - DEBUG - on stmt: jump 16\n", - "2024-10-16 10:10:46,255 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:46,256 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,257 - numba.core.ssa - DEBUG - on stmt: $36return_value.1 = cast(value=c)\n", - "2024-10-16 10:10:46,258 - numba.core.ssa - DEBUG - on stmt: return $36return_value.1\n", - "2024-10-16 10:10:46,259 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 18: []})\n", - "2024-10-16 10:10:46,259 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:10:46,260 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,261 - numba.core.ssa - DEBUG - on stmt: arr = arg(0, name=arr)\n", - "2024-10-16 10:10:46,262 - numba.core.ssa - DEBUG - on stmt: c = freevar(zero: 0)\n", - "2024-10-16 10:10:46,263 - numba.core.ssa - DEBUG - on stmt: $6load_global.1 = global(np: )\n", - "2024-10-16 10:10:46,264 - numba.core.ssa - DEBUG - on stmt: $8load_method.2 = getattr(value=$6load_global.1, attr=nditer)\n", - "2024-10-16 10:10:46,265 - numba.core.ssa - DEBUG - on stmt: $12call_method.4 = call $8load_method.2(arr, func=$8load_method.2, args=[Var(arr, arraymath.py:166)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:46,265 - numba.core.ssa - DEBUG - on stmt: $14get_iter.5 = getiter(value=$12call_method.4)\n", - "2024-10-16 10:10:46,266 - numba.core.ssa - DEBUG - on stmt: $phi16.0 = $14get_iter.5\n", - "2024-10-16 10:10:46,267 - numba.core.ssa - DEBUG - on stmt: jump 16\n", - "2024-10-16 10:10:46,268 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 16\n", - "2024-10-16 10:10:46,269 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,270 - numba.core.ssa - DEBUG - on stmt: $16for_iter.1 = iternext(value=$phi16.0)\n", - "2024-10-16 10:10:46,271 - numba.core.ssa - DEBUG - on stmt: $16for_iter.2 = pair_first(value=$16for_iter.1)\n", - "2024-10-16 10:10:46,272 - numba.core.ssa - DEBUG - on stmt: $16for_iter.3 = pair_second(value=$16for_iter.1)\n", - "2024-10-16 10:10:46,272 - numba.core.ssa - DEBUG - on stmt: $phi18.1 = $16for_iter.2\n", - "2024-10-16 10:10:46,273 - numba.core.ssa - DEBUG - on stmt: branch $16for_iter.3, 18, 34\n", - "2024-10-16 10:10:46,274 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 18\n", - "2024-10-16 10:10:46,275 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,276 - numba.core.ssa - DEBUG - on stmt: v = $phi18.1\n", - "2024-10-16 10:10:46,277 - numba.core.ssa - DEBUG - on stmt: $24load_method.4 = getattr(value=v, attr=item)\n", - "2024-10-16 10:10:46,277 - numba.core.ssa - DEBUG - on stmt: $26call_method.5 = call $24load_method.4(func=$24load_method.4, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:46,278 - numba.core.ssa - DEBUG - on stmt: $28inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=c, rhs=$26call_method.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:46,279 - numba.core.ssa - DEBUG - find_def var='c' stmt=$28inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=c, rhs=$26call_method.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:46,280 - numba.core.ssa - DEBUG - find_def_from_top label 18\n", - "2024-10-16 10:10:46,281 - numba.core.ssa - DEBUG - idom 16 from label 18\n", - "2024-10-16 10:10:46,282 - numba.core.ssa - DEBUG - find_def_from_bottom label 16\n", - "2024-10-16 10:10:46,283 - numba.core.ssa - DEBUG - find_def_from_top label 16\n", - "2024-10-16 10:10:46,283 - numba.core.ssa - DEBUG - insert phi node c.2 = phi(incoming_values=[], incoming_blocks=[]) at 16\n", - "2024-10-16 10:10:46,284 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:10:46,285 - numba.core.ssa - DEBUG - incoming_def c = freevar(zero: 0)\n", - "2024-10-16 10:10:46,286 - numba.core.ssa - DEBUG - find_def_from_bottom label 18\n", - "2024-10-16 10:10:46,286 - numba.core.ssa - DEBUG - incoming_def c.1 = $28inplace_add.6\n", - "2024-10-16 10:10:46,287 - numba.core.ssa - DEBUG - replaced with: $28inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=c.2, rhs=$26call_method.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:10:46,288 - numba.core.ssa - DEBUG - on stmt: c.1 = $28inplace_add.6\n", - "2024-10-16 10:10:46,289 - numba.core.ssa - DEBUG - on stmt: jump 16\n", - "2024-10-16 10:10:46,290 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-10-16 10:10:46,290 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,291 - numba.core.ssa - DEBUG - on stmt: $36return_value.1 = cast(value=c)\n", - "2024-10-16 10:10:46,292 - numba.core.ssa - DEBUG - find_def var='c' stmt=$36return_value.1 = cast(value=c)\n", - "2024-10-16 10:10:46,293 - numba.core.ssa - DEBUG - find_def_from_top label 34\n", - "2024-10-16 10:10:46,294 - numba.core.ssa - DEBUG - idom 16 from label 34\n", - "2024-10-16 10:10:46,294 - numba.core.ssa - DEBUG - find_def_from_bottom label 16\n", - "2024-10-16 10:10:46,295 - numba.core.ssa - DEBUG - replaced with: $36return_value.1 = cast(value=c.2)\n", - "2024-10-16 10:10:46,296 - numba.core.ssa - DEBUG - on stmt: return $36return_value.1\n", - "2024-10-16 10:10:46,353 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3523)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3524)\n", - " 4\tLOAD_FAST(arg=0, lineno=3524)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=3524)\n", - " 8\tSTORE_FAST(arg=2, lineno=3524)\n", - " 10\tLOAD_GLOBAL(arg=1, lineno=3525)\n", - " 12\tLOAD_FAST(arg=2, lineno=3525)\n", - " 14\tCALL_FUNCTION(arg=1, lineno=3525)\n", - " 16\tGET_ITER(arg=None, lineno=3525)\n", - "> 18\tFOR_ITER(arg=20, lineno=3525)\n", - " 20\tSTORE_FAST(arg=3, lineno=3525)\n", - " 22\tLOAD_FAST(arg=0, lineno=3526)\n", - " 24\tLOAD_FAST(arg=3, lineno=3526)\n", - " 26\tBINARY_SUBSCR(arg=None, lineno=3526)\n", - " 28\tLOAD_FAST(arg=1, lineno=3526)\n", - " 30\tLOAD_GLOBAL(arg=0, lineno=3526)\n", - " 32\tLOAD_FAST(arg=1, lineno=3526)\n", - " 34\tCALL_FUNCTION(arg=1, lineno=3526)\n", - " 36\tLOAD_FAST(arg=2, lineno=3526)\n", - " 38\tBINARY_SUBTRACT(arg=None, lineno=3526)\n", - " 40\tLOAD_FAST(arg=3, lineno=3526)\n", - " 42\tBINARY_ADD(arg=None, lineno=3526)\n", - " 44\tBINARY_SUBSCR(arg=None, lineno=3526)\n", - " 46\tCOMPARE_OP(arg=3, lineno=3526)\n", - " 48\tPOP_JUMP_IF_FALSE(arg=30, lineno=3526)\n", - " 50\tLOAD_GLOBAL(arg=2, lineno=3527)\n", - " 52\tLOAD_CONST(arg=1, lineno=3527)\n", - " 54\tCALL_FUNCTION(arg=1, lineno=3527)\n", - " 56\tRAISE_VARARGS(arg=1, lineno=3527)\n", - "> 58\tJUMP_ABSOLUTE(arg=10, lineno=3526)\n", - "> 60\tLOAD_CONST(arg=0, lineno=3525)\n", - " 62\tRETURN_VALUE(arg=None, lineno=3525)\n", - "2024-10-16 10:10:46,354 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:46,355 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:46,356 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:46,357 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3523)\n", - "2024-10-16 10:10:46,358 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,359 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3524)\n", - "2024-10-16 10:10:46,359 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,360 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=3524)\n", - "2024-10-16 10:10:46,361 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:10:46,362 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=3524)\n", - "2024-10-16 10:10:46,363 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$shape4.1']\n", - "2024-10-16 10:10:46,364 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=2, lineno=3524)\n", - "2024-10-16 10:10:46,365 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-10-16 10:10:46,365 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=1, lineno=3525)\n", - "2024-10-16 10:10:46,366 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,367 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=2, lineno=3525)\n", - "2024-10-16 10:10:46,368 - numba.core.byteflow - DEBUG - stack ['$10load_global.3']\n", - "2024-10-16 10:10:46,369 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=CALL_FUNCTION(arg=1, lineno=3525)\n", - "2024-10-16 10:10:46,370 - numba.core.byteflow - DEBUG - stack ['$10load_global.3', '$n12.4']\n", - "2024-10-16 10:10:46,370 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=GET_ITER(arg=None, lineno=3525)\n", - "2024-10-16 10:10:46,371 - numba.core.byteflow - DEBUG - stack ['$14call_function.5']\n", - "2024-10-16 10:10:46,372 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=18, stack=('$16get_iter.6',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:46,373 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=18 nstack_initial=1)])\n", - "2024-10-16 10:10:46,374 - numba.core.byteflow - DEBUG - stack: ['$phi18.0']\n", - "2024-10-16 10:10:46,375 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=18 nstack_initial=1)\n", - "2024-10-16 10:10:46,376 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=FOR_ITER(arg=20, lineno=3525)\n", - "2024-10-16 10:10:46,376 - numba.core.byteflow - DEBUG - stack ['$phi18.0']\n", - "2024-10-16 10:10:46,377 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=60, stack=(), blockstack=(), npush=0), Edge(pc=20, stack=('$phi18.0', '$18for_iter.2'), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:46,378 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=0), State(pc_initial=20 nstack_initial=2)])\n", - "2024-10-16 10:10:46,379 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:46,380 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=60 nstack_initial=0)\n", - "2024-10-16 10:10:46,381 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_CONST(arg=0, lineno=3525)\n", - "2024-10-16 10:10:46,382 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,382 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=RETURN_VALUE(arg=None, lineno=3525)\n", - "2024-10-16 10:10:46,383 - numba.core.byteflow - DEBUG - stack ['$const60.0']\n", - "2024-10-16 10:10:46,384 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:46,385 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=20 nstack_initial=2)])\n", - "2024-10-16 10:10:46,386 - numba.core.byteflow - DEBUG - stack: ['$phi20.0', '$phi20.1']\n", - "2024-10-16 10:10:46,387 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=20 nstack_initial=2)\n", - "2024-10-16 10:10:46,387 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=STORE_FAST(arg=3, lineno=3525)\n", - "2024-10-16 10:10:46,388 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$phi20.1']\n", - "2024-10-16 10:10:46,389 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=0, lineno=3526)\n", - "2024-10-16 10:10:46,390 - numba.core.byteflow - DEBUG - stack ['$phi20.0']\n", - "2024-10-16 10:10:46,391 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_FAST(arg=3, lineno=3526)\n", - "2024-10-16 10:10:46,392 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$shape22.2']\n", - "2024-10-16 10:10:46,393 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=BINARY_SUBSCR(arg=None, lineno=3526)\n", - "2024-10-16 10:10:46,394 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$shape22.2', '$i24.3']\n", - "2024-10-16 10:10:46,395 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_FAST(arg=1, lineno=3526)\n", - "2024-10-16 10:10:46,396 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4']\n", - "2024-10-16 10:10:46,396 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_GLOBAL(arg=0, lineno=3526)\n", - "2024-10-16 10:10:46,397 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4', '$main_shape28.5']\n", - "2024-10-16 10:10:46,398 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_FAST(arg=1, lineno=3526)\n", - "2024-10-16 10:10:46,399 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4', '$main_shape28.5', '$30load_global.6']\n", - "2024-10-16 10:10:46,400 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=CALL_FUNCTION(arg=1, lineno=3526)\n", - "2024-10-16 10:10:46,401 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4', '$main_shape28.5', '$30load_global.6', '$main_shape32.7']\n", - "2024-10-16 10:10:46,402 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_FAST(arg=2, lineno=3526)\n", - "2024-10-16 10:10:46,402 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4', '$main_shape28.5', '$34call_function.8']\n", - "2024-10-16 10:10:46,403 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=BINARY_SUBTRACT(arg=None, lineno=3526)\n", - "2024-10-16 10:10:46,404 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4', '$main_shape28.5', '$34call_function.8', '$n36.9']\n", - "2024-10-16 10:10:46,405 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_FAST(arg=3, lineno=3526)\n", - "2024-10-16 10:10:46,406 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4', '$main_shape28.5', '$38binary_subtract.10']\n", - "2024-10-16 10:10:46,407 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=BINARY_ADD(arg=None, lineno=3526)\n", - "2024-10-16 10:10:46,408 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4', '$main_shape28.5', '$38binary_subtract.10', '$i40.11']\n", - "2024-10-16 10:10:46,408 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=BINARY_SUBSCR(arg=None, lineno=3526)\n", - "2024-10-16 10:10:46,409 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4', '$main_shape28.5', '$42binary_add.12']\n", - "2024-10-16 10:10:46,410 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=COMPARE_OP(arg=3, lineno=3526)\n", - "2024-10-16 10:10:46,411 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$26binary_subscr.4', '$44binary_subscr.13']\n", - "2024-10-16 10:10:46,412 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=POP_JUMP_IF_FALSE(arg=30, lineno=3526)\n", - "2024-10-16 10:10:46,413 - numba.core.byteflow - DEBUG - stack ['$phi20.0', '$46compare_op.14']\n", - "2024-10-16 10:10:46,413 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=50, stack=('$phi20.0',), blockstack=(), npush=0), Edge(pc=58, stack=('$phi20.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:46,414 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=50 nstack_initial=1), State(pc_initial=58 nstack_initial=1)])\n", - "2024-10-16 10:10:46,415 - numba.core.byteflow - DEBUG - stack: ['$phi50.0']\n", - "2024-10-16 10:10:46,416 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=50 nstack_initial=1)\n", - "2024-10-16 10:10:46,417 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_GLOBAL(arg=2, lineno=3527)\n", - "2024-10-16 10:10:46,417 - numba.core.byteflow - DEBUG - stack ['$phi50.0']\n", - "2024-10-16 10:10:46,418 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=LOAD_CONST(arg=1, lineno=3527)\n", - "2024-10-16 10:10:46,419 - numba.core.byteflow - DEBUG - stack ['$phi50.0', '$50load_global.1']\n", - "2024-10-16 10:10:46,420 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=CALL_FUNCTION(arg=1, lineno=3527)\n", - "2024-10-16 10:10:46,421 - numba.core.byteflow - DEBUG - stack ['$phi50.0', '$50load_global.1', '$const52.2']\n", - "2024-10-16 10:10:46,422 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=RAISE_VARARGS(arg=1, lineno=3527)\n", - "2024-10-16 10:10:46,422 - numba.core.byteflow - DEBUG - stack ['$phi50.0', '$54call_function.3']\n", - "2024-10-16 10:10:46,423 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:46,424 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=58 nstack_initial=1)])\n", - "2024-10-16 10:10:46,425 - numba.core.byteflow - DEBUG - stack: ['$phi58.0']\n", - "2024-10-16 10:10:46,426 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=58 nstack_initial=1)\n", - "2024-10-16 10:10:46,426 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=JUMP_ABSOLUTE(arg=10, lineno=3526)\n", - "2024-10-16 10:10:46,427 - numba.core.byteflow - DEBUG - stack ['$phi58.0']\n", - "2024-10-16 10:10:46,428 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=18, stack=('$phi58.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:10:46,429 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=18 nstack_initial=1)])\n", - "2024-10-16 10:10:46,430 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:46,431 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=18 nstack_initial=1): {'$phi18.0'},\n", - " State(pc_initial=20 nstack_initial=2): {'$phi20.1'},\n", - " State(pc_initial=50 nstack_initial=1): set(),\n", - " State(pc_initial=58 nstack_initial=1): set(),\n", - " State(pc_initial=60 nstack_initial=0): set()})\n", - "2024-10-16 10:10:46,447 - numba.core.byteflow - DEBUG - defmap: {'$phi18.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi20.1': State(pc_initial=18 nstack_initial=1)}\n", - "2024-10-16 10:10:46,448 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi18.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi58.0', State(pc_initial=58 nstack_initial=1))},\n", - " '$phi20.0': {('$phi18.0', State(pc_initial=18 nstack_initial=1))},\n", - " '$phi20.1': {('$18for_iter.2',\n", - " State(pc_initial=18 nstack_initial=1))},\n", - " '$phi50.0': {('$phi20.0', State(pc_initial=20 nstack_initial=2))},\n", - " '$phi58.0': {('$phi20.0', State(pc_initial=20 nstack_initial=2))}})\n", - "2024-10-16 10:10:46,449 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi18.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi20.0', State(pc_initial=20 nstack_initial=2))},\n", - " '$phi20.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi20.0', State(pc_initial=20 nstack_initial=2))},\n", - " '$phi20.1': {('$18for_iter.2',\n", - " State(pc_initial=18 nstack_initial=1))},\n", - " '$phi50.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi58.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))}})\n", - "2024-10-16 10:10:46,450 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi18.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.1': {('$18for_iter.2',\n", - " State(pc_initial=18 nstack_initial=1))},\n", - " '$phi50.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi58.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))}})\n", - "2024-10-16 10:10:46,451 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi18.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.1': {('$18for_iter.2',\n", - " State(pc_initial=18 nstack_initial=1))},\n", - " '$phi50.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi58.0': {('$16get_iter.6',\n", - " State(pc_initial=0 nstack_initial=0))}})\n", - "2024-10-16 10:10:46,452 - numba.core.byteflow - DEBUG - keep phismap: {'$phi18.0': {('$16get_iter.6', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi20.1': {('$18for_iter.2', State(pc_initial=18 nstack_initial=1))}}\n", - "2024-10-16 10:10:46,453 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi18.0': '$16get_iter.6'},\n", - " State(pc_initial=18 nstack_initial=1): {'$phi20.1': '$18for_iter.2'}})\n", - "2024-10-16 10:10:46,454 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:46,455 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$shape4.1'}), (6, {'func': '$2load_global.0', 'args': ['$shape4.1'], 'res': '$6call_function.2'}), (8, {'value': '$6call_function.2'}), (10, {'res': '$10load_global.3'}), (12, {'res': '$n12.4'}), (14, {'func': '$10load_global.3', 'args': ['$n12.4'], 'res': '$14call_function.5'}), (16, {'value': '$14call_function.5', 'res': '$16get_iter.6'})), outgoing_phis={'$phi18.0': '$16get_iter.6'}, blockstack=(), active_try_block=None, outgoing_edgepushed={18: ('$16get_iter.6',)})\n", - "2024-10-16 10:10:46,455 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=18 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((18, {'iterator': '$phi18.0', 'pair': '$18for_iter.1', 'indval': '$18for_iter.2', 'pred': '$18for_iter.3'}),), outgoing_phis={'$phi20.1': '$18for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={60: (), 20: ('$phi18.0', '$18for_iter.2')})\n", - "2024-10-16 10:10:46,456 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=20 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((20, {'value': '$phi20.1'}), (22, {'res': '$shape22.2'}), (24, {'res': '$i24.3'}), (26, {'index': '$i24.3', 'target': '$shape22.2', 'res': '$26binary_subscr.4'}), (28, {'res': '$main_shape28.5'}), (30, {'res': '$30load_global.6'}), (32, {'res': '$main_shape32.7'}), (34, {'func': '$30load_global.6', 'args': ['$main_shape32.7'], 'res': '$34call_function.8'}), (36, {'res': '$n36.9'}), (38, {'lhs': '$34call_function.8', 'rhs': '$n36.9', 'res': '$38binary_subtract.10'}), (40, {'res': '$i40.11'}), (42, {'lhs': '$38binary_subtract.10', 'rhs': '$i40.11', 'res': '$42binary_add.12'}), (44, {'index': '$42binary_add.12', 'target': '$main_shape28.5', 'res': '$44binary_subscr.13'}), (46, {'lhs': '$26binary_subscr.4', 'rhs': '$44binary_subscr.13', 'res': '$46compare_op.14'}), (48, {'pred': '$46compare_op.14'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={50: ('$phi20.0',), 58: ('$phi20.0',)})\n", - "2024-10-16 10:10:46,457 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=50 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((50, {'res': '$50load_global.1'}), (52, {'res': '$const52.2'}), (54, {'func': '$50load_global.1', 'args': ['$const52.2'], 'res': '$54call_function.3'}), (56, {'exc': '$54call_function.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:46,458 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=58 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((58, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={18: ('$phi58.0',)})\n", - "2024-10-16 10:10:46,458 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=60 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((60, {'res': '$const60.0'}), (62, {'retval': '$const60.0', 'castval': '$62return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:46,462 - numba.core.interpreter - DEBUG - label 0:\n", - " shape = arg(0, name=shape) ['shape']\n", - " main_shape = arg(1, name=main_shape) ['main_shape']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " n = call $2load_global.0(shape, func=$2load_global.0, args=[Var(shape, arrayobj.py:3523)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'n', 'shape']\n", - " $10load_global.3 = global(range: ) ['$10load_global.3']\n", - " $14call_function.5 = call $10load_global.3(n, func=$10load_global.3, args=[Var(n, arrayobj.py:3524)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_global.3', '$14call_function.5', 'n']\n", - " $16get_iter.6 = getiter(value=$14call_function.5) ['$14call_function.5', '$16get_iter.6']\n", - " $phi18.0 = $16get_iter.6 ['$16get_iter.6', '$phi18.0']\n", - " jump 18 []\n", - "label 18:\n", - " $18for_iter.1 = iternext(value=$phi18.0) ['$18for_iter.1', '$phi18.0']\n", - " $18for_iter.2 = pair_first(value=$18for_iter.1) ['$18for_iter.1', '$18for_iter.2']\n", - " $18for_iter.3 = pair_second(value=$18for_iter.1) ['$18for_iter.1', '$18for_iter.3']\n", - " $phi20.1 = $18for_iter.2 ['$18for_iter.2', '$phi20.1']\n", - " branch $18for_iter.3, 20, 60 ['$18for_iter.3']\n", - "label 20:\n", - " i = $phi20.1 ['$phi20.1', 'i']\n", - " $26binary_subscr.4 = getitem(value=shape, index=i, fn=) ['$26binary_subscr.4', 'i', 'shape']\n", - " $30load_global.6 = global(len: ) ['$30load_global.6']\n", - " $34call_function.8 = call $30load_global.6(main_shape, func=$30load_global.6, args=[Var(main_shape, arrayobj.py:3523)], kws=(), vararg=None, varkwarg=None, target=None) ['$30load_global.6', '$34call_function.8', 'main_shape']\n", - " $38binary_subtract.10 = $34call_function.8 - n ['$34call_function.8', '$38binary_subtract.10', 'n']\n", - " $42binary_add.12 = $38binary_subtract.10 + i ['$38binary_subtract.10', '$42binary_add.12', 'i']\n", - " $44binary_subscr.13 = getitem(value=main_shape, index=$42binary_add.12, fn=) ['$42binary_add.12', '$44binary_subscr.13', 'main_shape']\n", - " $46compare_op.14 = $26binary_subscr.4 != $44binary_subscr.13 ['$26binary_subscr.4', '$44binary_subscr.13', '$46compare_op.14']\n", - " bool48 = global(bool: ) ['bool48']\n", - " $48pred = call bool48($46compare_op.14, func=bool48, args=(Var($46compare_op.14, arrayobj.py:3526),), kws=(), vararg=None, varkwarg=None, target=None) ['$46compare_op.14', '$48pred', 'bool48']\n", - " branch $48pred, 50, 58 ['$48pred']\n", - "label 50:\n", - " $50load_global.1 = global(ValueError: ) ['$50load_global.1']\n", - " $const52.2 = const(str, nditer(): operands could not be broadcast together) ['$const52.2']\n", - " $54call_function.3 = call $50load_global.1($const52.2, func=$50load_global.1, args=[Var($const52.2, arrayobj.py:3527)], kws=(), vararg=None, varkwarg=None, target=None) ['$50load_global.1', '$54call_function.3', '$const52.2']\n", - " raise $54call_function.3 ['$54call_function.3']\n", - "label 58:\n", - " jump 18 []\n", - "label 60:\n", - " $const60.0 = const(NoneType, None) ['$const60.0']\n", - " $62return_value.1 = cast(value=$const60.0) ['$62return_value.1', '$const60.0']\n", - " return $62return_value.1 ['$62return_value.1']\n", - "\n", - "2024-10-16 10:10:46,486 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:46,487 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,488 - numba.core.ssa - DEBUG - on stmt: shape = arg(0, name=shape)\n", - "2024-10-16 10:10:46,489 - numba.core.ssa - DEBUG - on stmt: main_shape = arg(1, name=main_shape)\n", - "2024-10-16 10:10:46,489 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-10-16 10:10:46,490 - numba.core.ssa - DEBUG - on stmt: n = const(int, 1)\n", - "2024-10-16 10:10:46,491 - numba.core.ssa - DEBUG - on stmt: $10load_global.3 = global(range: )\n", - "2024-10-16 10:10:46,492 - numba.core.ssa - DEBUG - on stmt: $14call_function.5 = call $10load_global.3(n, func=$10load_global.3, args=[Var(n, arrayobj.py:3524)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:46,492 - numba.core.ssa - DEBUG - on stmt: $16get_iter.6 = getiter(value=$14call_function.5)\n", - "2024-10-16 10:10:46,493 - numba.core.ssa - DEBUG - on stmt: $phi18.0 = $16get_iter.6\n", - "2024-10-16 10:10:46,494 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:46,495 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 18\n", - "2024-10-16 10:10:46,498 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,499 - numba.core.ssa - DEBUG - on stmt: $18for_iter.1 = iternext(value=$phi18.0)\n", - "2024-10-16 10:10:46,500 - numba.core.ssa - DEBUG - on stmt: $18for_iter.2 = pair_first(value=$18for_iter.1)\n", - "2024-10-16 10:10:46,500 - numba.core.ssa - DEBUG - on stmt: $18for_iter.3 = pair_second(value=$18for_iter.1)\n", - "2024-10-16 10:10:46,501 - numba.core.ssa - DEBUG - on stmt: $phi20.1 = $18for_iter.2\n", - "2024-10-16 10:10:46,502 - numba.core.ssa - DEBUG - on stmt: branch $18for_iter.3, 20, 60\n", - "2024-10-16 10:10:46,503 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 20\n", - "2024-10-16 10:10:46,504 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,504 - numba.core.ssa - DEBUG - on stmt: i = $phi20.1\n", - "2024-10-16 10:10:46,505 - numba.core.ssa - DEBUG - on stmt: $26binary_subscr.4 = getitem(value=shape, index=i, fn=)\n", - "2024-10-16 10:10:46,506 - numba.core.ssa - DEBUG - on stmt: $30load_global.6 = global(len: )\n", - "2024-10-16 10:10:46,507 - numba.core.ssa - DEBUG - on stmt: $34call_function.8 = const(int, 1)\n", - "2024-10-16 10:10:46,508 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.10 = $34call_function.8 - n\n", - "2024-10-16 10:10:46,508 - numba.core.ssa - DEBUG - on stmt: $42binary_add.12 = $38binary_subtract.10 + i\n", - "2024-10-16 10:10:46,509 - numba.core.ssa - DEBUG - on stmt: $44binary_subscr.13 = getitem(value=main_shape, index=$42binary_add.12, fn=)\n", - "2024-10-16 10:10:46,513 - numba.core.ssa - DEBUG - on stmt: $46compare_op.14 = $26binary_subscr.4 != $44binary_subscr.13\n", - "2024-10-16 10:10:46,514 - numba.core.ssa - DEBUG - on stmt: bool48 = global(bool: )\n", - "2024-10-16 10:10:46,515 - numba.core.ssa - DEBUG - on stmt: $48pred = call bool48($46compare_op.14, func=bool48, args=(Var($46compare_op.14, arrayobj.py:3526),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:46,516 - numba.core.ssa - DEBUG - on stmt: branch $48pred, 50, 58\n", - "2024-10-16 10:10:46,516 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 50\n", - "2024-10-16 10:10:46,517 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,518 - numba.core.ssa - DEBUG - on stmt: $50load_global.1 = global(ValueError: )\n", - "2024-10-16 10:10:46,519 - numba.core.ssa - DEBUG - on stmt: $const52.2 = const(str, nditer(): operands could not be broadcast together)\n", - "2024-10-16 10:10:46,519 - numba.core.ssa - DEBUG - on stmt: $54call_function.3 = call $50load_global.1($const52.2, func=$50load_global.1, args=[Var($const52.2, arrayobj.py:3527)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:10:46,520 - numba.core.ssa - DEBUG - on stmt: raise ('nditer(): operands could not be broadcast together')\n", - "2024-10-16 10:10:46,521 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 58\n", - "2024-10-16 10:10:46,522 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,523 - numba.core.ssa - DEBUG - on stmt: jump 18\n", - "2024-10-16 10:10:46,524 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 60\n", - "2024-10-16 10:10:46,524 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,525 - numba.core.ssa - DEBUG - on stmt: $const60.0 = const(NoneType, None)\n", - "2024-10-16 10:10:46,526 - numba.core.ssa - DEBUG - on stmt: $62return_value.1 = cast(value=$const60.0)\n", - "2024-10-16 10:10:46,527 - numba.core.ssa - DEBUG - on stmt: return $62return_value.1\n", - "2024-10-16 10:10:46,528 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_global.3': [],\n", - " '$14call_function.5': [],\n", - " '$16get_iter.6': [],\n", - " '$18for_iter.1': [],\n", - " '$18for_iter.2': [],\n", - " '$18for_iter.3': [],\n", - " '$26binary_subscr.4': [],\n", - " '$2load_global.0': [],\n", - " '$30load_global.6': [],\n", - " '$34call_function.8': [],\n", - " '$38binary_subtract.10': [],\n", - " '$42binary_add.12': [],\n", - " '$44binary_subscr.13': [],\n", - " '$46compare_op.14': [],\n", - " '$48pred': [],\n", - " '$50load_global.1': [],\n", - " '$54call_function.3': [],\n", - " '$62return_value.1': [],\n", - " '$const52.2': [],\n", - " '$const60.0': [],\n", - " '$phi18.0': [],\n", - " '$phi20.1': [],\n", - " 'bool48': [],\n", - " 'i': [],\n", - " 'main_shape': [],\n", - " 'n': [],\n", - " 'shape': []})\n", - "2024-10-16 10:10:46,529 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:10:46,976 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=1)\n", - " 2\tLOAD_FAST(arg=0, lineno=1)\n", - " 4\tLOAD_CONST(arg=1, lineno=1)\n", - " 6\tBINARY_SUBTRACT(arg=None, lineno=1)\n", - " 8\tRETURN_VALUE(arg=None, lineno=1)\n", - "2024-10-16 10:10:46,977 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:10:46,978 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:10:46,978 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:10:46,979 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=1)\n", - "2024-10-16 10:10:46,979 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,980 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=1)\n", - "2024-10-16 10:10:46,981 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:10:46,981 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_CONST(arg=1, lineno=1)\n", - "2024-10-16 10:10:46,982 - numba.core.byteflow - DEBUG - stack ['$tof_indices_12.0']\n", - "2024-10-16 10:10:46,982 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=BINARY_SUBTRACT(arg=None, lineno=1)\n", - "2024-10-16 10:10:46,983 - numba.core.byteflow - DEBUG - stack ['$tof_indices_12.0', '$const4.1']\n", - "2024-10-16 10:10:46,984 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=1)\n", - "2024-10-16 10:10:46,984 - numba.core.byteflow - DEBUG - stack ['$6binary_subtract.2']\n", - "2024-10-16 10:10:46,985 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:10:46,986 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:10:46,986 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:10:46,987 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:10:46,988 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:10:46,988 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:10:46,989 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:10:46,990 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:10:46,990 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:10:46,991 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$tof_indices_12.0'}), (4, {'res': '$const4.1'}), (6, {'lhs': '$tof_indices_12.0', 'rhs': '$const4.1', 'res': '$6binary_subtract.2'}), (8, {'retval': '$6binary_subtract.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:10:46,992 - numba.core.interpreter - DEBUG - label 0:\n", - " tof_indices_1 = arg(0, name=tof_indices_1) ['tof_indices_1']\n", - " $const4.1 = const(int, 1) ['$const4.1']\n", - " $6binary_subtract.2 = tof_indices_1 - $const4.1 ['$6binary_subtract.2', '$const4.1', 'tof_indices_1']\n", - " $8return_value.3 = cast(value=$6binary_subtract.2) ['$6binary_subtract.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:10:46,998 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:10:46,999 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:10:46,999 - numba.core.ssa - DEBUG - on stmt: tof_indices_1 = arg(0, name=tof_indices_1)\n", - "2024-10-16 10:10:47,000 - numba.core.ssa - DEBUG - on stmt: $const4.1 = const(int, 1)\n", - "2024-10-16 10:10:47,001 - numba.core.ssa - DEBUG - on stmt: $6binary_subtract.2 = tof_indices_1 - $const4.1\n", - "2024-10-16 10:10:47,001 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6binary_subtract.2)\n", - "2024-10-16 10:10:47,002 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:10:47,003 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$6binary_subtract.2': [],\n", - " '$8return_value.3': [],\n", - " '$const4.1': [],\n", - " 'tof_indices_1': []})\n", - "2024-10-16 10:10:47,003 - numba.core.ssa - DEBUG - SSA violators set()\n", - "100%|██████████| 16759/16759 [00:25<00:00, 667.82it/s] \n", - "2024-10-16 10:11:05,821 - root - INFO - Indexing /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d...\n", - "2024-10-16 10:11:06,029 - root - INFO - Opening handle for /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "2024-10-16 10:11:06,178 - root - INFO - Fetching mobility values from /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "2024-10-16 10:11:06,181 - root - INFO - Closing handle for /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "2024-10-16 10:11:06,183 - root - INFO - Opening handle for /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "2024-10-16 10:11:06,195 - root - INFO - Fetching mz values from /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "2024-10-16 10:11:06,217 - root - INFO - Closing handle for /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "2024-10-16 10:11:06,219 - root - INFO - Indexing quadrupole dimension\n", - "2024-10-16 10:11:07,162 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=2960)\n", - " 2\tBUILD_LIST(arg=0, lineno=3027)\n", - " 4\tSTORE_FAST(arg=14, lineno=3027)\n", - " 6\tLOAD_CONST(arg=1, lineno=3028)\n", - " 8\tSTORE_FAST(arg=15, lineno=3028)\n", - " 10\tLOAD_CONST(arg=1, lineno=3029)\n", - " 12\tSTORE_FAST(arg=16, lineno=3029)\n", - " 14\tLOAD_CONST(arg=1, lineno=3030)\n", - " 16\tSTORE_FAST(arg=17, lineno=3030)\n", - " 18\tLOAD_CONST(arg=2, lineno=3031)\n", - " 20\tSTORE_FAST(arg=18, lineno=3031)\n", - " 22\tLOAD_FAST(arg=8, lineno=3032)\n", - " 24\tLOAD_CONST(arg=3, lineno=3032)\n", - " 26\tLOAD_CONST(arg=1, lineno=3032)\n", - " 28\tBUILD_SLICE(arg=2, lineno=3032)\n", - " 30\tBINARY_SUBSCR(arg=None, lineno=3032)\n", - " 32\tLOAD_METHOD(arg=0, lineno=3032)\n", - " 34\tLOAD_FAST(arg=6, lineno=3033)\n", - " 36\tLOAD_FAST(arg=7, lineno=3034)\n", - " 38\tCALL_METHOD(arg=2, lineno=3032)\n", - " 40\tSTORE_FAST(arg=19, lineno=3032)\n", - " 42\tLOAD_FAST(arg=8, lineno=3036)\n", - " 44\tLOAD_CONST(arg=4, lineno=3036)\n", - " 46\tLOAD_CONST(arg=3, lineno=3036)\n", - " 48\tBUILD_SLICE(arg=2, lineno=3036)\n", - " 50\tBINARY_SUBSCR(arg=None, lineno=3036)\n", - " 52\tLOAD_METHOD(arg=0, lineno=3036)\n", - " 54\tLOAD_FAST(arg=6, lineno=3037)\n", - " 56\tLOAD_FAST(arg=7, lineno=3038)\n", - " 58\tCALL_METHOD(arg=2, lineno=3036)\n", - " 60\tSTORE_FAST(arg=20, lineno=3036)\n", - " 62\tLOAD_FAST(arg=0, lineno=3040)\n", - " 64\tGET_ITER(arg=None, lineno=3040)\n", - "> 66\tFOR_ITER(arg=202, lineno=3040)\n", - " 68\tUNPACK_SEQUENCE(arg=3, lineno=3040)\n", - " 70\tSTORE_FAST(arg=21, lineno=3040)\n", - " 72\tSTORE_FAST(arg=22, lineno=3040)\n", - " 74\tSTORE_FAST(arg=23, lineno=3040)\n", - " 76\tLOAD_GLOBAL(arg=1, lineno=3041)\n", - " 78\tLOAD_FAST(arg=19, lineno=3042)\n", - " 80\tLOAD_GLOBAL(arg=2, lineno=3042)\n", - " 82\tLOAD_FAST(arg=21, lineno=3042)\n", - " 84\tLOAD_FAST(arg=22, lineno=3042)\n", - " 86\tLOAD_FAST(arg=23, lineno=3042)\n", - " 88\tCALL_FUNCTION(arg=3, lineno=3042)\n", - " 90\tBINARY_SUBSCR(arg=None, lineno=3042)\n", - " 92\tLOAD_FAST(arg=20, lineno=3043)\n", - " 94\tLOAD_GLOBAL(arg=2, lineno=3043)\n", - " 96\tLOAD_FAST(arg=21, lineno=3043)\n", - " 98\tLOAD_FAST(arg=22, lineno=3043)\n", - " 100\tLOAD_FAST(arg=23, lineno=3043)\n", - " 102\tCALL_FUNCTION(arg=3, lineno=3043)\n", - " 104\tBINARY_SUBSCR(arg=None, lineno=3043)\n", - " 106\tCALL_FUNCTION(arg=2, lineno=3041)\n", - " 108\tGET_ITER(arg=None, lineno=3041)\n", - "> 110\tFOR_ITER(arg=179, lineno=3041)\n", - " 112\tUNPACK_SEQUENCE(arg=2, lineno=3041)\n", - " 114\tSTORE_FAST(arg=24, lineno=3041)\n", - " 116\tSTORE_FAST(arg=25, lineno=3041)\n", - " 118\tLOAD_FAST(arg=1, lineno=3045)\n", - " 120\tGET_ITER(arg=None, lineno=3045)\n", - "> 122\tFOR_ITER(arg=172, lineno=3045)\n", - " 124\tUNPACK_SEQUENCE(arg=3, lineno=3045)\n", - " 126\tSTORE_FAST(arg=26, lineno=3045)\n", - " 128\tSTORE_FAST(arg=27, lineno=3045)\n", - " 130\tSTORE_FAST(arg=28, lineno=3045)\n", - " 132\tLOAD_GLOBAL(arg=1, lineno=3046)\n", - " 134\tLOAD_FAST(arg=24, lineno=3047)\n", - " 136\tLOAD_GLOBAL(arg=2, lineno=3047)\n", - " 138\tLOAD_FAST(arg=26, lineno=3047)\n", - " 140\tLOAD_FAST(arg=27, lineno=3047)\n", - " 142\tLOAD_FAST(arg=28, lineno=3047)\n", - " 144\tCALL_FUNCTION(arg=3, lineno=3047)\n", - " 146\tBINARY_SUBSCR(arg=None, lineno=3047)\n", - " 148\tLOAD_FAST(arg=25, lineno=3048)\n", - " 150\tLOAD_GLOBAL(arg=2, lineno=3048)\n", - " 152\tLOAD_FAST(arg=26, lineno=3048)\n", - " 154\tLOAD_FAST(arg=27, lineno=3048)\n", - " 156\tLOAD_FAST(arg=28, lineno=3048)\n", - " 158\tCALL_FUNCTION(arg=3, lineno=3048)\n", - " 160\tBINARY_SUBSCR(arg=None, lineno=3048)\n", - " 162\tCALL_FUNCTION(arg=2, lineno=3046)\n", - " 164\tGET_ITER(arg=None, lineno=3046)\n", - "> 166\tFOR_ITER(arg=149, lineno=3046)\n", - " 168\tUNPACK_SEQUENCE(arg=2, lineno=3046)\n", - " 170\tSTORE_FAST(arg=29, lineno=3046)\n", - " 172\tSTORE_FAST(arg=30, lineno=3046)\n", - " 174\tLOAD_FAST(arg=29, lineno=3050)\n", - " 176\tLOAD_FAST(arg=30, lineno=3050)\n", - " 178\tCOMPARE_OP(arg=2, lineno=3050)\n", - " 180\tPOP_JUMP_IF_FALSE(arg=93, lineno=3050)\n", - " 182\tJUMP_ABSOLUTE(arg=84, lineno=3051)\n", - "> 184\tLOAD_FAST(arg=17, lineno=3052)\n", - " 186\tLOAD_FAST(arg=30, lineno=3052)\n", - " 188\tCOMPARE_OP(arg=0, lineno=3052)\n", - " 190\tPOP_JUMP_IF_FALSE(arg=111, lineno=3052)\n", - "> 192\tLOAD_FAST(arg=16, lineno=3053)\n", - " 194\tLOAD_CONST(arg=4, lineno=3053)\n", - " 196\tINPLACE_ADD(arg=None, lineno=3053)\n", - " 198\tSTORE_FAST(arg=16, lineno=3053)\n", - " 200\tLOAD_FAST(arg=11, lineno=3054)\n", - " 202\tLOAD_FAST(arg=16, lineno=3054)\n", - " 204\tLOAD_CONST(arg=4, lineno=3054)\n", - " 206\tBINARY_ADD(arg=None, lineno=3054)\n", - " 208\tBINARY_SUBSCR(arg=None, lineno=3054)\n", - " 210\tSTORE_FAST(arg=17, lineno=3054)\n", - " 212\tLOAD_FAST(arg=17, lineno=3052)\n", - " 214\tLOAD_FAST(arg=30, lineno=3052)\n", - " 216\tCOMPARE_OP(arg=0, lineno=3052)\n", - " 218\tPOP_JUMP_IF_TRUE(arg=97, lineno=3052)\n", - "> 220\tLOAD_FAST(arg=15, lineno=3055)\n", - " 222\tLOAD_FAST(arg=16, lineno=3055)\n", - " 224\tCOMPARE_OP(arg=3, lineno=3055)\n", - " 226\tPOP_JUMP_IF_FALSE(arg=146, lineno=3055)\n", - " 228\tLOAD_FAST(arg=16, lineno=3056)\n", - " 230\tSTORE_FAST(arg=15, lineno=3056)\n", - " 232\tLOAD_GLOBAL(arg=3, lineno=3057)\n", - " 234\tLOAD_FAST(arg=10, lineno=3058)\n", - " 236\tLOAD_FAST(arg=15, lineno=3058)\n", - " 238\tLOAD_CONST(arg=5, lineno=3058)\n", - " 240\tBUILD_TUPLE(arg=2, lineno=3058)\n", - " 242\tBINARY_SUBSCR(arg=None, lineno=3058)\n", - " 244\tLOAD_FAST(arg=10, lineno=3059)\n", - " 246\tLOAD_FAST(arg=15, lineno=3059)\n", - " 248\tLOAD_CONST(arg=4, lineno=3059)\n", - " 250\tBUILD_TUPLE(arg=2, lineno=3059)\n", - " 252\tBINARY_SUBSCR(arg=None, lineno=3059)\n", - " 254\tLOAD_FAST(arg=4, lineno=3060)\n", - " 256\tCALL_FUNCTION(arg=3, lineno=3057)\n", - " 258\tPOP_JUMP_IF_TRUE(arg=134, lineno=3057)\n", - " 260\tLOAD_CONST(arg=6, lineno=3062)\n", - " 262\tSTORE_FAST(arg=18, lineno=3062)\n", - " 264\tJUMP_FORWARD(arg=12, lineno=3062)\n", - "> 266\tLOAD_GLOBAL(arg=4, lineno=3063)\n", - " 268\tLOAD_FAST(arg=9, lineno=3064)\n", - " 270\tLOAD_FAST(arg=15, lineno=3064)\n", - " 272\tBINARY_SUBSCR(arg=None, lineno=3064)\n", - " 274\tLOAD_FAST(arg=2, lineno=3065)\n", - " 276\tCALL_FUNCTION(arg=2, lineno=3063)\n", - " 278\tPOP_JUMP_IF_TRUE(arg=144, lineno=3063)\n", - " 280\tLOAD_CONST(arg=6, lineno=3067)\n", - " 282\tSTORE_FAST(arg=18, lineno=3067)\n", - " 284\tJUMP_FORWARD(arg=2, lineno=3067)\n", - "> 286\tLOAD_CONST(arg=2, lineno=3069)\n", - " 288\tSTORE_FAST(arg=18, lineno=3069)\n", - "> 290\tLOAD_FAST(arg=18, lineno=3070)\n", - " 292\tPOP_JUMP_IF_TRUE(arg=149, lineno=3070)\n", - " 294\tJUMP_ABSOLUTE(arg=84, lineno=3071)\n", - "> 296\tLOAD_FAST(arg=29, lineno=3072)\n", - " 298\tSTORE_FAST(arg=31, lineno=3072)\n", - " 300\tLOAD_FAST(arg=3, lineno=3073)\n", - " 302\tGET_ITER(arg=None, lineno=3073)\n", - "> 304\tFOR_ITER(arg=79, lineno=3073)\n", - " 306\tUNPACK_SEQUENCE(arg=3, lineno=3073)\n", - " 308\tSTORE_FAST(arg=32, lineno=3073)\n", - " 310\tSTORE_FAST(arg=33, lineno=3073)\n", - " 312\tSTORE_FAST(arg=34, lineno=3073)\n", - " 314\tLOAD_FAST(arg=31, lineno=3074)\n", - " 316\tLOAD_GLOBAL(arg=5, lineno=3074)\n", - " 318\tLOAD_METHOD(arg=6, lineno=3074)\n", - " 320\tLOAD_FAST(arg=12, lineno=3075)\n", - " 322\tLOAD_FAST(arg=31, lineno=3075)\n", - " 324\tLOAD_FAST(arg=30, lineno=3075)\n", - " 326\tBUILD_SLICE(arg=2, lineno=3075)\n", - " 328\tBINARY_SUBSCR(arg=None, lineno=3075)\n", - " 330\tLOAD_FAST(arg=32, lineno=3076)\n", - " 332\tCALL_METHOD(arg=2, lineno=3074)\n", - " 334\tINPLACE_ADD(arg=None, lineno=3074)\n", - " 336\tSTORE_FAST(arg=31, lineno=3074)\n", - " 338\tLOAD_FAST(arg=12, lineno=3078)\n", - " 340\tLOAD_FAST(arg=31, lineno=3078)\n", - " 342\tBINARY_SUBSCR(arg=None, lineno=3078)\n", - " 344\tSTORE_FAST(arg=35, lineno=3078)\n", - " 346\tLOAD_FAST(arg=35, lineno=3079)\n", - " 348\tLOAD_FAST(arg=33, lineno=3079)\n", - " 350\tCOMPARE_OP(arg=0, lineno=3079)\n", - " 352\tPOP_JUMP_IF_FALSE(arg=232, lineno=3079)\n", - " 354\tLOAD_FAST(arg=31, lineno=3079)\n", - " 356\tLOAD_FAST(arg=30, lineno=3079)\n", - " 358\tCOMPARE_OP(arg=0, lineno=3079)\n", - " 360\tPOP_JUMP_IF_FALSE(arg=232, lineno=3079)\n", - "> 362\tLOAD_FAST(arg=35, lineno=3080)\n", - " 364\tLOAD_GLOBAL(arg=7, lineno=3080)\n", - " 366\tLOAD_FAST(arg=32, lineno=3081)\n", - " 368\tLOAD_FAST(arg=33, lineno=3082)\n", - " 370\tLOAD_FAST(arg=34, lineno=3083)\n", - " 372\tCALL_FUNCTION(arg=3, lineno=3080)\n", - " 374\tCONTAINS_OP(arg=0, lineno=3080)\n", - " 376\tPOP_JUMP_IF_FALSE(arg=216, lineno=3080)\n", - " 378\tLOAD_FAST(arg=13, lineno=3085)\n", - " 380\tLOAD_FAST(arg=31, lineno=3085)\n", - " 382\tBINARY_SUBSCR(arg=None, lineno=3085)\n", - " 384\tSTORE_FAST(arg=36, lineno=3085)\n", - " 386\tLOAD_FAST(arg=5, lineno=3089)\n", - " 388\tGET_ITER(arg=None, lineno=3086)\n", - "> 390\tFOR_ITER(arg=19, lineno=3086)\n", - " 392\tUNPACK_SEQUENCE(arg=2, lineno=3086)\n", - " 394\tSTORE_FAST(arg=37, lineno=3087)\n", - " 396\tSTORE_FAST(arg=38, lineno=3088)\n", - " 398\tLOAD_FAST(arg=37, lineno=3090)\n", - " 400\tLOAD_FAST(arg=36, lineno=3090)\n", - " 402\tCOMPARE_OP(arg=1, lineno=3090)\n", - " 404\tPOP_JUMP_IF_FALSE(arg=215, lineno=3090)\n", - " 406\tLOAD_FAST(arg=36, lineno=3091)\n", - " 408\tLOAD_FAST(arg=38, lineno=3091)\n", - " 410\tCOMPARE_OP(arg=1, lineno=3091)\n", - " 412\tPOP_JUMP_IF_FALSE(arg=215, lineno=3091)\n", - " 414\tLOAD_FAST(arg=14, lineno=3092)\n", - " 416\tLOAD_METHOD(arg=8, lineno=3092)\n", - " 418\tLOAD_FAST(arg=31, lineno=3092)\n", - " 420\tCALL_METHOD(arg=1, lineno=3092)\n", - " 422\tPOP_TOP(arg=None, lineno=3092)\n", - " 424\tPOP_TOP(arg=None, lineno=3093)\n", - " 426\tJUMP_FORWARD(arg=1, lineno=3093)\n", - "> 428\tJUMP_ABSOLUTE(arg=196, lineno=3093)\n", - "> 430\tLOAD_FAST(arg=31, lineno=3094)\n", - " 432\tLOAD_CONST(arg=4, lineno=3094)\n", - " 434\tINPLACE_ADD(arg=None, lineno=3094)\n", - " 436\tSTORE_FAST(arg=31, lineno=3094)\n", - " 438\tLOAD_FAST(arg=12, lineno=3095)\n", - " 440\tLOAD_FAST(arg=31, lineno=3095)\n", - " 442\tBINARY_SUBSCR(arg=None, lineno=3095)\n", - " 444\tSTORE_FAST(arg=35, lineno=3095)\n", - " 446\tLOAD_FAST(arg=35, lineno=3079)\n", - " 448\tLOAD_FAST(arg=33, lineno=3079)\n", - " 450\tCOMPARE_OP(arg=0, lineno=3079)\n", - " 452\tPOP_JUMP_IF_FALSE(arg=232, lineno=3079)\n", - " 454\tLOAD_FAST(arg=31, lineno=3079)\n", - " 456\tLOAD_FAST(arg=30, lineno=3079)\n", - " 458\tCOMPARE_OP(arg=0, lineno=3079)\n", - " 460\tPOP_JUMP_IF_TRUE(arg=182, lineno=3079)\n", - "> 462\tJUMP_ABSOLUTE(arg=153, lineno=3079)\n", - "> 464\tJUMP_ABSOLUTE(arg=84, lineno=3073)\n", - "> 466\tJUMP_ABSOLUTE(arg=62, lineno=3046)\n", - "> 468\tJUMP_ABSOLUTE(arg=56, lineno=3045)\n", - "> 470\tJUMP_ABSOLUTE(arg=34, lineno=3041)\n", - "> 472\tLOAD_GLOBAL(arg=5, lineno=3096)\n", - " 474\tLOAD_METHOD(arg=9, lineno=3096)\n", - " 476\tLOAD_FAST(arg=14, lineno=3096)\n", - " 478\tCALL_METHOD(arg=1, lineno=3096)\n", - " 480\tRETURN_VALUE(arg=None, lineno=3096)\n", - "2024-10-16 10:11:07,164 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:07,165 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:07,165 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:07,166 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=2960)\n", - "2024-10-16 10:11:07,167 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,167 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=BUILD_LIST(arg=0, lineno=3027)\n", - "2024-10-16 10:11:07,168 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,169 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=STORE_FAST(arg=14, lineno=3027)\n", - "2024-10-16 10:11:07,170 - numba.core.byteflow - DEBUG - stack ['$2build_list.0']\n", - "2024-10-16 10:11:07,170 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_CONST(arg=1, lineno=3028)\n", - "2024-10-16 10:11:07,171 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,172 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=15, lineno=3028)\n", - "2024-10-16 10:11:07,172 - numba.core.byteflow - DEBUG - stack ['$const6.1']\n", - "2024-10-16 10:11:07,173 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_CONST(arg=1, lineno=3029)\n", - "2024-10-16 10:11:07,173 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,174 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=STORE_FAST(arg=16, lineno=3029)\n", - "2024-10-16 10:11:07,175 - numba.core.byteflow - DEBUG - stack ['$const10.2']\n", - "2024-10-16 10:11:07,177 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_CONST(arg=1, lineno=3030)\n", - "2024-10-16 10:11:07,177 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,178 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=STORE_FAST(arg=17, lineno=3030)\n", - "2024-10-16 10:11:07,179 - numba.core.byteflow - DEBUG - stack ['$const14.3']\n", - "2024-10-16 10:11:07,179 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=2, lineno=3031)\n", - "2024-10-16 10:11:07,180 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,181 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=STORE_FAST(arg=18, lineno=3031)\n", - "2024-10-16 10:11:07,181 - numba.core.byteflow - DEBUG - stack ['$const18.4']\n", - "2024-10-16 10:11:07,182 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=8, lineno=3032)\n", - "2024-10-16 10:11:07,183 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,184 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_CONST(arg=3, lineno=3032)\n", - "2024-10-16 10:11:07,184 - numba.core.byteflow - DEBUG - stack ['$push_indptr22.5']\n", - "2024-10-16 10:11:07,185 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_CONST(arg=1, lineno=3032)\n", - "2024-10-16 10:11:07,185 - numba.core.byteflow - DEBUG - stack ['$push_indptr22.5', '$const24.6']\n", - "2024-10-16 10:11:07,186 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=BUILD_SLICE(arg=2, lineno=3032)\n", - "2024-10-16 10:11:07,187 - numba.core.byteflow - DEBUG - stack ['$push_indptr22.5', '$const24.6', '$const26.7']\n", - "2024-10-16 10:11:07,188 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=BINARY_SUBSCR(arg=None, lineno=3032)\n", - "2024-10-16 10:11:07,188 - numba.core.byteflow - DEBUG - stack ['$push_indptr22.5', '$28build_slice.9']\n", - "2024-10-16 10:11:07,189 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_METHOD(arg=0, lineno=3032)\n", - "2024-10-16 10:11:07,190 - numba.core.byteflow - DEBUG - stack ['$30binary_subscr.10']\n", - "2024-10-16 10:11:07,190 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=6, lineno=3033)\n", - "2024-10-16 10:11:07,191 - numba.core.byteflow - DEBUG - stack ['$32load_method.11']\n", - "2024-10-16 10:11:07,192 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_FAST(arg=7, lineno=3034)\n", - "2024-10-16 10:11:07,192 - numba.core.byteflow - DEBUG - stack ['$32load_method.11', '$frame_max_index34.12']\n", - "2024-10-16 10:11:07,193 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=CALL_METHOD(arg=2, lineno=3032)\n", - "2024-10-16 10:11:07,194 - numba.core.byteflow - DEBUG - stack ['$32load_method.11', '$frame_max_index34.12', '$scan_max_index36.13']\n", - "2024-10-16 10:11:07,194 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=STORE_FAST(arg=19, lineno=3032)\n", - "2024-10-16 10:11:07,195 - numba.core.byteflow - DEBUG - stack ['$38call_method.14']\n", - "2024-10-16 10:11:07,196 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_FAST(arg=8, lineno=3036)\n", - "2024-10-16 10:11:07,196 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,197 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=LOAD_CONST(arg=4, lineno=3036)\n", - "2024-10-16 10:11:07,198 - numba.core.byteflow - DEBUG - stack ['$push_indptr42.15']\n", - "2024-10-16 10:11:07,198 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_CONST(arg=3, lineno=3036)\n", - "2024-10-16 10:11:07,199 - numba.core.byteflow - DEBUG - stack ['$push_indptr42.15', '$const44.16']\n", - "2024-10-16 10:11:07,200 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=BUILD_SLICE(arg=2, lineno=3036)\n", - "2024-10-16 10:11:07,200 - numba.core.byteflow - DEBUG - stack ['$push_indptr42.15', '$const44.16', '$const46.17']\n", - "2024-10-16 10:11:07,201 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=BINARY_SUBSCR(arg=None, lineno=3036)\n", - "2024-10-16 10:11:07,202 - numba.core.byteflow - DEBUG - stack ['$push_indptr42.15', '$48build_slice.19']\n", - "2024-10-16 10:11:07,202 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=LOAD_METHOD(arg=0, lineno=3036)\n", - "2024-10-16 10:11:07,203 - numba.core.byteflow - DEBUG - stack ['$50binary_subscr.20']\n", - "2024-10-16 10:11:07,204 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=LOAD_FAST(arg=6, lineno=3037)\n", - "2024-10-16 10:11:07,204 - numba.core.byteflow - DEBUG - stack ['$52load_method.21']\n", - "2024-10-16 10:11:07,205 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_FAST(arg=7, lineno=3038)\n", - "2024-10-16 10:11:07,206 - numba.core.byteflow - DEBUG - stack ['$52load_method.21', '$frame_max_index54.22']\n", - "2024-10-16 10:11:07,206 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=CALL_METHOD(arg=2, lineno=3036)\n", - "2024-10-16 10:11:07,207 - numba.core.byteflow - DEBUG - stack ['$52load_method.21', '$frame_max_index54.22', '$scan_max_index56.23']\n", - "2024-10-16 10:11:07,208 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=STORE_FAST(arg=20, lineno=3036)\n", - "2024-10-16 10:11:07,208 - numba.core.byteflow - DEBUG - stack ['$58call_method.24']\n", - "2024-10-16 10:11:07,209 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_FAST(arg=0, lineno=3040)\n", - "2024-10-16 10:11:07,210 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,210 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=GET_ITER(arg=None, lineno=3040)\n", - "2024-10-16 10:11:07,211 - numba.core.byteflow - DEBUG - stack ['$frame_slices62.25']\n", - "2024-10-16 10:11:07,212 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=66, stack=('$64get_iter.26',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,212 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=66 nstack_initial=1)])\n", - "2024-10-16 10:11:07,213 - numba.core.byteflow - DEBUG - stack: ['$phi66.0']\n", - "2024-10-16 10:11:07,214 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=66 nstack_initial=1)\n", - "2024-10-16 10:11:07,214 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=FOR_ITER(arg=202, lineno=3040)\n", - "2024-10-16 10:11:07,215 - numba.core.byteflow - DEBUG - stack ['$phi66.0']\n", - "2024-10-16 10:11:07,216 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=472, stack=(), blockstack=(), npush=0), Edge(pc=68, stack=('$phi66.0', '$66for_iter.2'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,217 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=472 nstack_initial=0), State(pc_initial=68 nstack_initial=2)])\n", - "2024-10-16 10:11:07,217 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:07,218 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=472 nstack_initial=0)\n", - "2024-10-16 10:11:07,218 - numba.core.byteflow - DEBUG - dispatch pc=472, inst=LOAD_GLOBAL(arg=5, lineno=3096)\n", - "2024-10-16 10:11:07,219 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:07,220 - numba.core.byteflow - DEBUG - dispatch pc=474, inst=LOAD_METHOD(arg=9, lineno=3096)\n", - "2024-10-16 10:11:07,220 - numba.core.byteflow - DEBUG - stack ['$472load_global.0']\n", - "2024-10-16 10:11:07,221 - numba.core.byteflow - DEBUG - dispatch pc=476, inst=LOAD_FAST(arg=14, lineno=3096)\n", - "2024-10-16 10:11:07,222 - numba.core.byteflow - DEBUG - stack ['$474load_method.1']\n", - "2024-10-16 10:11:07,222 - numba.core.byteflow - DEBUG - dispatch pc=478, inst=CALL_METHOD(arg=1, lineno=3096)\n", - "2024-10-16 10:11:07,223 - numba.core.byteflow - DEBUG - stack ['$474load_method.1', '$result476.2']\n", - "2024-10-16 10:11:07,224 - numba.core.byteflow - DEBUG - dispatch pc=480, inst=RETURN_VALUE(arg=None, lineno=3096)\n", - "2024-10-16 10:11:07,225 - numba.core.byteflow - DEBUG - stack ['$478call_method.3']\n", - "2024-10-16 10:11:07,225 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:07,226 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=68 nstack_initial=2)])\n", - "2024-10-16 10:11:07,226 - numba.core.byteflow - DEBUG - stack: ['$phi68.0', '$phi68.1']\n", - "2024-10-16 10:11:07,227 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=68 nstack_initial=2)\n", - "2024-10-16 10:11:07,228 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=UNPACK_SEQUENCE(arg=3, lineno=3040)\n", - "2024-10-16 10:11:07,228 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$phi68.1']\n", - "2024-10-16 10:11:07,229 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=STORE_FAST(arg=21, lineno=3040)\n", - "2024-10-16 10:11:07,230 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$68unpack_sequence.4', '$68unpack_sequence.3', '$68unpack_sequence.2']\n", - "2024-10-16 10:11:07,230 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=STORE_FAST(arg=22, lineno=3040)\n", - "2024-10-16 10:11:07,231 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$68unpack_sequence.4', '$68unpack_sequence.3']\n", - "2024-10-16 10:11:07,232 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=STORE_FAST(arg=23, lineno=3040)\n", - "2024-10-16 10:11:07,232 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$68unpack_sequence.4']\n", - "2024-10-16 10:11:07,233 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=LOAD_GLOBAL(arg=1, lineno=3041)\n", - "2024-10-16 10:11:07,234 - numba.core.byteflow - DEBUG - stack ['$phi68.0']\n", - "2024-10-16 10:11:07,234 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=19, lineno=3042)\n", - "2024-10-16 10:11:07,235 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6']\n", - "2024-10-16 10:11:07,236 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_GLOBAL(arg=2, lineno=3042)\n", - "2024-10-16 10:11:07,236 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$starts78.7']\n", - "2024-10-16 10:11:07,237 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=LOAD_FAST(arg=21, lineno=3042)\n", - "2024-10-16 10:11:07,238 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$starts78.7', '$80load_global.8']\n", - "2024-10-16 10:11:07,238 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=LOAD_FAST(arg=22, lineno=3042)\n", - "2024-10-16 10:11:07,239 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$starts78.7', '$80load_global.8', '$frame_start82.9']\n", - "2024-10-16 10:11:07,240 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=23, lineno=3042)\n", - "2024-10-16 10:11:07,240 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$starts78.7', '$80load_global.8', '$frame_start82.9', '$frame_stop84.10']\n", - "2024-10-16 10:11:07,241 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=CALL_FUNCTION(arg=3, lineno=3042)\n", - "2024-10-16 10:11:07,242 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$starts78.7', '$80load_global.8', '$frame_start82.9', '$frame_stop84.10', '$frame_step86.11']\n", - "2024-10-16 10:11:07,242 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=BINARY_SUBSCR(arg=None, lineno=3042)\n", - "2024-10-16 10:11:07,243 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$starts78.7', '$88call_function.12']\n", - "2024-10-16 10:11:07,244 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=LOAD_FAST(arg=20, lineno=3043)\n", - "2024-10-16 10:11:07,244 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$90binary_subscr.13']\n", - "2024-10-16 10:11:07,245 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_GLOBAL(arg=2, lineno=3043)\n", - "2024-10-16 10:11:07,246 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$90binary_subscr.13', '$ends92.14']\n", - "2024-10-16 10:11:07,246 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=LOAD_FAST(arg=21, lineno=3043)\n", - "2024-10-16 10:11:07,247 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$90binary_subscr.13', '$ends92.14', '$94load_global.15']\n", - "2024-10-16 10:11:07,247 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=22, lineno=3043)\n", - "2024-10-16 10:11:07,248 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$90binary_subscr.13', '$ends92.14', '$94load_global.15', '$frame_start96.16']\n", - "2024-10-16 10:11:07,249 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=23, lineno=3043)\n", - "2024-10-16 10:11:07,249 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$90binary_subscr.13', '$ends92.14', '$94load_global.15', '$frame_start96.16', '$frame_stop98.17']\n", - "2024-10-16 10:11:07,250 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=CALL_FUNCTION(arg=3, lineno=3043)\n", - "2024-10-16 10:11:07,251 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$90binary_subscr.13', '$ends92.14', '$94load_global.15', '$frame_start96.16', '$frame_stop98.17', '$frame_step100.18']\n", - "2024-10-16 10:11:07,251 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=BINARY_SUBSCR(arg=None, lineno=3043)\n", - "2024-10-16 10:11:07,252 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$90binary_subscr.13', '$ends92.14', '$102call_function.19']\n", - "2024-10-16 10:11:07,252 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=CALL_FUNCTION(arg=2, lineno=3041)\n", - "2024-10-16 10:11:07,253 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$76load_global.6', '$90binary_subscr.13', '$104binary_subscr.20']\n", - "2024-10-16 10:11:07,254 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=GET_ITER(arg=None, lineno=3041)\n", - "2024-10-16 10:11:07,254 - numba.core.byteflow - DEBUG - stack ['$phi68.0', '$106call_function.21']\n", - "2024-10-16 10:11:07,255 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=110, stack=('$phi68.0', '$108get_iter.22'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,256 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=110 nstack_initial=2)])\n", - "2024-10-16 10:11:07,256 - numba.core.byteflow - DEBUG - stack: ['$phi110.0', '$phi110.1']\n", - "2024-10-16 10:11:07,257 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=110 nstack_initial=2)\n", - "2024-10-16 10:11:07,258 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=FOR_ITER(arg=179, lineno=3041)\n", - "2024-10-16 10:11:07,258 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$phi110.1']\n", - "2024-10-16 10:11:07,259 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=470, stack=('$phi110.0',), blockstack=(), npush=0), Edge(pc=112, stack=('$phi110.0', '$phi110.1', '$110for_iter.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,259 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=470 nstack_initial=1), State(pc_initial=112 nstack_initial=3)])\n", - "2024-10-16 10:11:07,260 - numba.core.byteflow - DEBUG - stack: ['$phi470.0']\n", - "2024-10-16 10:11:07,261 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=470 nstack_initial=1)\n", - "2024-10-16 10:11:07,261 - numba.core.byteflow - DEBUG - dispatch pc=470, inst=JUMP_ABSOLUTE(arg=34, lineno=3041)\n", - "2024-10-16 10:11:07,262 - numba.core.byteflow - DEBUG - stack ['$phi470.0']\n", - "2024-10-16 10:11:07,263 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=66, stack=('$phi470.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,263 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=112 nstack_initial=3), State(pc_initial=66 nstack_initial=1)])\n", - "2024-10-16 10:11:07,264 - numba.core.byteflow - DEBUG - stack: ['$phi112.0', '$phi112.1', '$phi112.2']\n", - "2024-10-16 10:11:07,264 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=112 nstack_initial=3)\n", - "2024-10-16 10:11:07,265 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=UNPACK_SEQUENCE(arg=2, lineno=3041)\n", - "2024-10-16 10:11:07,266 - numba.core.byteflow - DEBUG - stack ['$phi112.0', '$phi112.1', '$phi112.2']\n", - "2024-10-16 10:11:07,266 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=STORE_FAST(arg=24, lineno=3041)\n", - "2024-10-16 10:11:07,267 - numba.core.byteflow - DEBUG - stack ['$phi112.0', '$phi112.1', '$112unpack_sequence.4', '$112unpack_sequence.3']\n", - "2024-10-16 10:11:07,267 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=STORE_FAST(arg=25, lineno=3041)\n", - "2024-10-16 10:11:07,268 - numba.core.byteflow - DEBUG - stack ['$phi112.0', '$phi112.1', '$112unpack_sequence.4']\n", - "2024-10-16 10:11:07,269 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_FAST(arg=1, lineno=3045)\n", - "2024-10-16 10:11:07,269 - numba.core.byteflow - DEBUG - stack ['$phi112.0', '$phi112.1']\n", - "2024-10-16 10:11:07,270 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=GET_ITER(arg=None, lineno=3045)\n", - "2024-10-16 10:11:07,270 - numba.core.byteflow - DEBUG - stack ['$phi112.0', '$phi112.1', '$scan_slices118.6']\n", - "2024-10-16 10:11:07,271 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=122, stack=('$phi112.0', '$phi112.1', '$120get_iter.7'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,272 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=66 nstack_initial=1), State(pc_initial=122 nstack_initial=3)])\n", - "2024-10-16 10:11:07,272 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=122 nstack_initial=3)])\n", - "2024-10-16 10:11:07,273 - numba.core.byteflow - DEBUG - stack: ['$phi122.0', '$phi122.1', '$phi122.2']\n", - "2024-10-16 10:11:07,273 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=122 nstack_initial=3)\n", - "2024-10-16 10:11:07,274 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=FOR_ITER(arg=172, lineno=3045)\n", - "2024-10-16 10:11:07,275 - numba.core.byteflow - DEBUG - stack ['$phi122.0', '$phi122.1', '$phi122.2']\n", - "2024-10-16 10:11:07,275 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=468, stack=('$phi122.0', '$phi122.1'), blockstack=(), npush=0), Edge(pc=124, stack=('$phi122.0', '$phi122.1', '$phi122.2', '$122for_iter.4'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,276 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=468 nstack_initial=2), State(pc_initial=124 nstack_initial=4)])\n", - "2024-10-16 10:11:07,276 - numba.core.byteflow - DEBUG - stack: ['$phi468.0', '$phi468.1']\n", - "2024-10-16 10:11:07,277 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=468 nstack_initial=2)\n", - "2024-10-16 10:11:07,278 - numba.core.byteflow - DEBUG - dispatch pc=468, inst=JUMP_ABSOLUTE(arg=56, lineno=3045)\n", - "2024-10-16 10:11:07,278 - numba.core.byteflow - DEBUG - stack ['$phi468.0', '$phi468.1']\n", - "2024-10-16 10:11:07,279 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=110, stack=('$phi468.0', '$phi468.1'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,279 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=124 nstack_initial=4), State(pc_initial=110 nstack_initial=2)])\n", - "2024-10-16 10:11:07,280 - numba.core.byteflow - DEBUG - stack: ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3']\n", - "2024-10-16 10:11:07,281 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=124 nstack_initial=4)\n", - "2024-10-16 10:11:07,281 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=UNPACK_SEQUENCE(arg=3, lineno=3045)\n", - "2024-10-16 10:11:07,282 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3']\n", - "2024-10-16 10:11:07,283 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=STORE_FAST(arg=26, lineno=3045)\n", - "2024-10-16 10:11:07,314 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$124unpack_sequence.6', '$124unpack_sequence.5', '$124unpack_sequence.4']\n", - "2024-10-16 10:11:07,315 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=STORE_FAST(arg=27, lineno=3045)\n", - "2024-10-16 10:11:07,316 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$124unpack_sequence.6', '$124unpack_sequence.5']\n", - "2024-10-16 10:11:07,316 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=STORE_FAST(arg=28, lineno=3045)\n", - "2024-10-16 10:11:07,317 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$124unpack_sequence.6']\n", - "2024-10-16 10:11:07,318 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_GLOBAL(arg=1, lineno=3046)\n", - "2024-10-16 10:11:07,318 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2']\n", - "2024-10-16 10:11:07,319 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_FAST(arg=24, lineno=3047)\n", - "2024-10-16 10:11:07,320 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8']\n", - "2024-10-16 10:11:07,321 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=LOAD_GLOBAL(arg=2, lineno=3047)\n", - "2024-10-16 10:11:07,321 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$frame_start_slice134.9']\n", - "2024-10-16 10:11:07,322 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=LOAD_FAST(arg=26, lineno=3047)\n", - "2024-10-16 10:11:07,323 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$frame_start_slice134.9', '$136load_global.10']\n", - "2024-10-16 10:11:07,323 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=LOAD_FAST(arg=27, lineno=3047)\n", - "2024-10-16 10:11:07,324 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$frame_start_slice134.9', '$136load_global.10', '$scan_start138.11']\n", - "2024-10-16 10:11:07,324 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=28, lineno=3047)\n", - "2024-10-16 10:11:07,325 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$frame_start_slice134.9', '$136load_global.10', '$scan_start138.11', '$scan_stop140.12']\n", - "2024-10-16 10:11:07,326 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=CALL_FUNCTION(arg=3, lineno=3047)\n", - "2024-10-16 10:11:07,327 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$frame_start_slice134.9', '$136load_global.10', '$scan_start138.11', '$scan_stop140.12', '$scan_step142.13']\n", - "2024-10-16 10:11:07,327 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=BINARY_SUBSCR(arg=None, lineno=3047)\n", - "2024-10-16 10:11:07,328 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$frame_start_slice134.9', '$144call_function.14']\n", - "2024-10-16 10:11:07,328 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=25, lineno=3048)\n", - "2024-10-16 10:11:07,329 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$146binary_subscr.15']\n", - "2024-10-16 10:11:07,330 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=LOAD_GLOBAL(arg=2, lineno=3048)\n", - "2024-10-16 10:11:07,331 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$146binary_subscr.15', '$frame_end_slice148.16']\n", - "2024-10-16 10:11:07,331 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=LOAD_FAST(arg=26, lineno=3048)\n", - "2024-10-16 10:11:07,332 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$146binary_subscr.15', '$frame_end_slice148.16', '$150load_global.17']\n", - "2024-10-16 10:11:07,333 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_FAST(arg=27, lineno=3048)\n", - "2024-10-16 10:11:07,333 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$146binary_subscr.15', '$frame_end_slice148.16', '$150load_global.17', '$scan_start152.18']\n", - "2024-10-16 10:11:07,334 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=LOAD_FAST(arg=28, lineno=3048)\n", - "2024-10-16 10:11:07,334 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$146binary_subscr.15', '$frame_end_slice148.16', '$150load_global.17', '$scan_start152.18', '$scan_stop154.19']\n", - "2024-10-16 10:11:07,335 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=CALL_FUNCTION(arg=3, lineno=3048)\n", - "2024-10-16 10:11:07,335 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$146binary_subscr.15', '$frame_end_slice148.16', '$150load_global.17', '$scan_start152.18', '$scan_stop154.19', '$scan_step156.20']\n", - "2024-10-16 10:11:07,336 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=BINARY_SUBSCR(arg=None, lineno=3048)\n", - "2024-10-16 10:11:07,337 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$146binary_subscr.15', '$frame_end_slice148.16', '$158call_function.21']\n", - "2024-10-16 10:11:07,337 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=CALL_FUNCTION(arg=2, lineno=3046)\n", - "2024-10-16 10:11:07,338 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$132load_global.8', '$146binary_subscr.15', '$160binary_subscr.22']\n", - "2024-10-16 10:11:07,338 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=GET_ITER(arg=None, lineno=3046)\n", - "2024-10-16 10:11:07,339 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$162call_function.23']\n", - "2024-10-16 10:11:07,339 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=166, stack=('$phi124.0', '$phi124.1', '$phi124.2', '$164get_iter.24'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,340 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=110 nstack_initial=2), State(pc_initial=166 nstack_initial=4)])\n", - "2024-10-16 10:11:07,342 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=166 nstack_initial=4)])\n", - "2024-10-16 10:11:07,343 - numba.core.byteflow - DEBUG - stack: ['$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3']\n", - "2024-10-16 10:11:07,343 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=166 nstack_initial=4)\n", - "2024-10-16 10:11:07,344 - numba.core.byteflow - DEBUG - dispatch pc=166, inst=FOR_ITER(arg=149, lineno=3046)\n", - "2024-10-16 10:11:07,345 - numba.core.byteflow - DEBUG - stack ['$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3']\n", - "2024-10-16 10:11:07,345 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=466, stack=('$phi166.0', '$phi166.1', '$phi166.2'), blockstack=(), npush=0), Edge(pc=168, stack=('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$166for_iter.5'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,346 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=466 nstack_initial=3), State(pc_initial=168 nstack_initial=5)])\n", - "2024-10-16 10:11:07,346 - numba.core.byteflow - DEBUG - stack: ['$phi466.0', '$phi466.1', '$phi466.2']\n", - "2024-10-16 10:11:07,347 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=466 nstack_initial=3)\n", - "2024-10-16 10:11:07,348 - numba.core.byteflow - DEBUG - dispatch pc=466, inst=JUMP_ABSOLUTE(arg=62, lineno=3046)\n", - "2024-10-16 10:11:07,348 - numba.core.byteflow - DEBUG - stack ['$phi466.0', '$phi466.1', '$phi466.2']\n", - "2024-10-16 10:11:07,349 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=122, stack=('$phi466.0', '$phi466.1', '$phi466.2'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,351 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=168 nstack_initial=5), State(pc_initial=122 nstack_initial=3)])\n", - "2024-10-16 10:11:07,351 - numba.core.byteflow - DEBUG - stack: ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$phi168.4']\n", - "2024-10-16 10:11:07,352 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=168 nstack_initial=5)\n", - "2024-10-16 10:11:07,353 - numba.core.byteflow - DEBUG - dispatch pc=168, inst=UNPACK_SEQUENCE(arg=2, lineno=3046)\n", - "2024-10-16 10:11:07,353 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$phi168.4']\n", - "2024-10-16 10:11:07,354 - numba.core.byteflow - DEBUG - dispatch pc=170, inst=STORE_FAST(arg=29, lineno=3046)\n", - "2024-10-16 10:11:07,354 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$168unpack_sequence.6', '$168unpack_sequence.5']\n", - "2024-10-16 10:11:07,355 - numba.core.byteflow - DEBUG - dispatch pc=172, inst=STORE_FAST(arg=30, lineno=3046)\n", - "2024-10-16 10:11:07,356 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$168unpack_sequence.6']\n", - "2024-10-16 10:11:07,356 - numba.core.byteflow - DEBUG - dispatch pc=174, inst=LOAD_FAST(arg=29, lineno=3050)\n", - "2024-10-16 10:11:07,357 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3']\n", - "2024-10-16 10:11:07,357 - numba.core.byteflow - DEBUG - dispatch pc=176, inst=LOAD_FAST(arg=30, lineno=3050)\n", - "2024-10-16 10:11:07,358 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$sparse_start174.8']\n", - "2024-10-16 10:11:07,358 - numba.core.byteflow - DEBUG - dispatch pc=178, inst=COMPARE_OP(arg=2, lineno=3050)\n", - "2024-10-16 10:11:07,359 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$sparse_start174.8', '$sparse_end176.9']\n", - "2024-10-16 10:11:07,360 - numba.core.byteflow - DEBUG - dispatch pc=180, inst=POP_JUMP_IF_FALSE(arg=93, lineno=3050)\n", - "2024-10-16 10:11:07,360 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$178compare_op.10']\n", - "2024-10-16 10:11:07,361 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=182, stack=('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3'), blockstack=(), npush=0), Edge(pc=184, stack=('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,361 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=122 nstack_initial=3), State(pc_initial=182 nstack_initial=4), State(pc_initial=184 nstack_initial=4)])\n", - "2024-10-16 10:11:07,362 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=182 nstack_initial=4), State(pc_initial=184 nstack_initial=4)])\n", - "2024-10-16 10:11:07,363 - numba.core.byteflow - DEBUG - stack: ['$phi182.0', '$phi182.1', '$phi182.2', '$phi182.3']\n", - "2024-10-16 10:11:07,363 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=182 nstack_initial=4)\n", - "2024-10-16 10:11:07,364 - numba.core.byteflow - DEBUG - dispatch pc=182, inst=JUMP_ABSOLUTE(arg=84, lineno=3051)\n", - "2024-10-16 10:11:07,364 - numba.core.byteflow - DEBUG - stack ['$phi182.0', '$phi182.1', '$phi182.2', '$phi182.3']\n", - "2024-10-16 10:11:07,365 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=166, stack=('$phi182.0', '$phi182.1', '$phi182.2', '$phi182.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,365 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=184 nstack_initial=4), State(pc_initial=166 nstack_initial=4)])\n", - "2024-10-16 10:11:07,366 - numba.core.byteflow - DEBUG - stack: ['$phi184.0', '$phi184.1', '$phi184.2', '$phi184.3']\n", - "2024-10-16 10:11:07,367 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=184 nstack_initial=4)\n", - "2024-10-16 10:11:07,367 - numba.core.byteflow - DEBUG - dispatch pc=184, inst=LOAD_FAST(arg=17, lineno=3052)\n", - "2024-10-16 10:11:07,368 - numba.core.byteflow - DEBUG - stack ['$phi184.0', '$phi184.1', '$phi184.2', '$phi184.3']\n", - "2024-10-16 10:11:07,368 - numba.core.byteflow - DEBUG - dispatch pc=186, inst=LOAD_FAST(arg=30, lineno=3052)\n", - "2024-10-16 10:11:07,369 - numba.core.byteflow - DEBUG - stack ['$phi184.0', '$phi184.1', '$phi184.2', '$phi184.3', '$quad_end184.4']\n", - "2024-10-16 10:11:07,369 - numba.core.byteflow - DEBUG - dispatch pc=188, inst=COMPARE_OP(arg=0, lineno=3052)\n", - "2024-10-16 10:11:07,370 - numba.core.byteflow - DEBUG - stack ['$phi184.0', '$phi184.1', '$phi184.2', '$phi184.3', '$quad_end184.4', '$sparse_end186.5']\n", - "2024-10-16 10:11:07,370 - numba.core.byteflow - DEBUG - dispatch pc=190, inst=POP_JUMP_IF_FALSE(arg=111, lineno=3052)\n", - "2024-10-16 10:11:07,371 - numba.core.byteflow - DEBUG - stack ['$phi184.0', '$phi184.1', '$phi184.2', '$phi184.3', '$188compare_op.6']\n", - "2024-10-16 10:11:07,372 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=192, stack=('$phi184.0', '$phi184.1', '$phi184.2', '$phi184.3'), blockstack=(), npush=0), Edge(pc=220, stack=('$phi184.0', '$phi184.1', '$phi184.2', '$phi184.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,372 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=166 nstack_initial=4), State(pc_initial=192 nstack_initial=4), State(pc_initial=220 nstack_initial=4)])\n", - "2024-10-16 10:11:07,373 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=192 nstack_initial=4), State(pc_initial=220 nstack_initial=4)])\n", - "2024-10-16 10:11:07,374 - numba.core.byteflow - DEBUG - stack: ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3']\n", - "2024-10-16 10:11:07,374 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=192 nstack_initial=4)\n", - "2024-10-16 10:11:07,375 - numba.core.byteflow - DEBUG - dispatch pc=192, inst=LOAD_FAST(arg=16, lineno=3053)\n", - "2024-10-16 10:11:07,375 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3']\n", - "2024-10-16 10:11:07,376 - numba.core.byteflow - DEBUG - dispatch pc=194, inst=LOAD_CONST(arg=4, lineno=3053)\n", - "2024-10-16 10:11:07,376 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$new_quad_index192.4']\n", - "2024-10-16 10:11:07,377 - numba.core.byteflow - DEBUG - dispatch pc=196, inst=INPLACE_ADD(arg=None, lineno=3053)\n", - "2024-10-16 10:11:07,377 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$new_quad_index192.4', '$const194.5']\n", - "2024-10-16 10:11:07,378 - numba.core.byteflow - DEBUG - dispatch pc=198, inst=STORE_FAST(arg=16, lineno=3053)\n", - "2024-10-16 10:11:07,379 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$196inplace_add.6']\n", - "2024-10-16 10:11:07,379 - numba.core.byteflow - DEBUG - dispatch pc=200, inst=LOAD_FAST(arg=11, lineno=3054)\n", - "2024-10-16 10:11:07,380 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3']\n", - "2024-10-16 10:11:07,380 - numba.core.byteflow - DEBUG - dispatch pc=202, inst=LOAD_FAST(arg=16, lineno=3054)\n", - "2024-10-16 10:11:07,381 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$quad_indptr200.7']\n", - "2024-10-16 10:11:07,382 - numba.core.byteflow - DEBUG - dispatch pc=204, inst=LOAD_CONST(arg=4, lineno=3054)\n", - "2024-10-16 10:11:07,382 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$quad_indptr200.7', '$new_quad_index202.8']\n", - "2024-10-16 10:11:07,383 - numba.core.byteflow - DEBUG - dispatch pc=206, inst=BINARY_ADD(arg=None, lineno=3054)\n", - "2024-10-16 10:11:07,383 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$quad_indptr200.7', '$new_quad_index202.8', '$const204.9']\n", - "2024-10-16 10:11:07,384 - numba.core.byteflow - DEBUG - dispatch pc=208, inst=BINARY_SUBSCR(arg=None, lineno=3054)\n", - "2024-10-16 10:11:07,384 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$quad_indptr200.7', '$206binary_add.10']\n", - "2024-10-16 10:11:07,385 - numba.core.byteflow - DEBUG - dispatch pc=210, inst=STORE_FAST(arg=17, lineno=3054)\n", - "2024-10-16 10:11:07,386 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$208binary_subscr.11']\n", - "2024-10-16 10:11:07,386 - numba.core.byteflow - DEBUG - dispatch pc=212, inst=LOAD_FAST(arg=17, lineno=3052)\n", - "2024-10-16 10:11:07,387 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3']\n", - "2024-10-16 10:11:07,387 - numba.core.byteflow - DEBUG - dispatch pc=214, inst=LOAD_FAST(arg=30, lineno=3052)\n", - "2024-10-16 10:11:07,388 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$quad_end212.12']\n", - "2024-10-16 10:11:07,388 - numba.core.byteflow - DEBUG - dispatch pc=216, inst=COMPARE_OP(arg=0, lineno=3052)\n", - "2024-10-16 10:11:07,389 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$quad_end212.12', '$sparse_end214.13']\n", - "2024-10-16 10:11:07,390 - numba.core.byteflow - DEBUG - dispatch pc=218, inst=POP_JUMP_IF_TRUE(arg=97, lineno=3052)\n", - "2024-10-16 10:11:07,390 - numba.core.byteflow - DEBUG - stack ['$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3', '$216compare_op.14']\n", - "2024-10-16 10:11:07,391 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=220, stack=('$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3'), blockstack=(), npush=0), Edge(pc=192, stack=('$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,391 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=220 nstack_initial=4), State(pc_initial=220 nstack_initial=4), State(pc_initial=192 nstack_initial=4)])\n", - "2024-10-16 10:11:07,392 - numba.core.byteflow - DEBUG - stack: ['$phi220.0', '$phi220.1', '$phi220.2', '$phi220.3']\n", - "2024-10-16 10:11:07,393 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=220 nstack_initial=4)\n", - "2024-10-16 10:11:07,393 - numba.core.byteflow - DEBUG - dispatch pc=220, inst=LOAD_FAST(arg=15, lineno=3055)\n", - "2024-10-16 10:11:07,394 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$phi220.2', '$phi220.3']\n", - "2024-10-16 10:11:07,394 - numba.core.byteflow - DEBUG - dispatch pc=222, inst=LOAD_FAST(arg=16, lineno=3055)\n", - "2024-10-16 10:11:07,395 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$phi220.2', '$phi220.3', '$quad_index220.4']\n", - "2024-10-16 10:11:07,395 - numba.core.byteflow - DEBUG - dispatch pc=224, inst=COMPARE_OP(arg=3, lineno=3055)\n", - "2024-10-16 10:11:07,396 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$phi220.2', '$phi220.3', '$quad_index220.4', '$new_quad_index222.5']\n", - "2024-10-16 10:11:07,396 - numba.core.byteflow - DEBUG - dispatch pc=226, inst=POP_JUMP_IF_FALSE(arg=146, lineno=3055)\n", - "2024-10-16 10:11:07,397 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$phi220.2', '$phi220.3', '$224compare_op.6']\n", - "2024-10-16 10:11:07,398 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=228, stack=('$phi220.0', '$phi220.1', '$phi220.2', '$phi220.3'), blockstack=(), npush=0), Edge(pc=290, stack=('$phi220.0', '$phi220.1', '$phi220.2', '$phi220.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,398 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=220 nstack_initial=4), State(pc_initial=192 nstack_initial=4), State(pc_initial=228 nstack_initial=4), State(pc_initial=290 nstack_initial=4)])\n", - "2024-10-16 10:11:07,399 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=192 nstack_initial=4), State(pc_initial=228 nstack_initial=4), State(pc_initial=290 nstack_initial=4)])\n", - "2024-10-16 10:11:07,400 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=228 nstack_initial=4), State(pc_initial=290 nstack_initial=4)])\n", - "2024-10-16 10:11:07,400 - numba.core.byteflow - DEBUG - stack: ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3']\n", - "2024-10-16 10:11:07,401 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=228 nstack_initial=4)\n", - "2024-10-16 10:11:07,401 - numba.core.byteflow - DEBUG - dispatch pc=228, inst=LOAD_FAST(arg=16, lineno=3056)\n", - "2024-10-16 10:11:07,402 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3']\n", - "2024-10-16 10:11:07,402 - numba.core.byteflow - DEBUG - dispatch pc=230, inst=STORE_FAST(arg=15, lineno=3056)\n", - "2024-10-16 10:11:07,403 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$new_quad_index228.4']\n", - "2024-10-16 10:11:07,404 - numba.core.byteflow - DEBUG - dispatch pc=232, inst=LOAD_GLOBAL(arg=3, lineno=3057)\n", - "2024-10-16 10:11:07,404 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3']\n", - "2024-10-16 10:11:07,405 - numba.core.byteflow - DEBUG - dispatch pc=234, inst=LOAD_FAST(arg=10, lineno=3058)\n", - "2024-10-16 10:11:07,405 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5']\n", - "2024-10-16 10:11:07,406 - numba.core.byteflow - DEBUG - dispatch pc=236, inst=LOAD_FAST(arg=15, lineno=3058)\n", - "2024-10-16 10:11:07,406 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$quad_mz_values234.6']\n", - "2024-10-16 10:11:07,407 - numba.core.byteflow - DEBUG - dispatch pc=238, inst=LOAD_CONST(arg=5, lineno=3058)\n", - "2024-10-16 10:11:07,407 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$quad_mz_values234.6', '$quad_index236.7']\n", - "2024-10-16 10:11:07,408 - numba.core.byteflow - DEBUG - dispatch pc=240, inst=BUILD_TUPLE(arg=2, lineno=3058)\n", - "2024-10-16 10:11:07,408 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$quad_mz_values234.6', '$quad_index236.7', '$const238.8']\n", - "2024-10-16 10:11:07,409 - numba.core.byteflow - DEBUG - dispatch pc=242, inst=BINARY_SUBSCR(arg=None, lineno=3058)\n", - "2024-10-16 10:11:07,409 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$quad_mz_values234.6', '$240build_tuple.9']\n", - "2024-10-16 10:11:07,410 - numba.core.byteflow - DEBUG - dispatch pc=244, inst=LOAD_FAST(arg=10, lineno=3059)\n", - "2024-10-16 10:11:07,410 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$242binary_subscr.10']\n", - "2024-10-16 10:11:07,411 - numba.core.byteflow - DEBUG - dispatch pc=246, inst=LOAD_FAST(arg=15, lineno=3059)\n", - "2024-10-16 10:11:07,411 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$242binary_subscr.10', '$quad_mz_values244.11']\n", - "2024-10-16 10:11:07,412 - numba.core.byteflow - DEBUG - dispatch pc=248, inst=LOAD_CONST(arg=4, lineno=3059)\n", - "2024-10-16 10:11:07,412 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$242binary_subscr.10', '$quad_mz_values244.11', '$quad_index246.12']\n", - "2024-10-16 10:11:07,413 - numba.core.byteflow - DEBUG - dispatch pc=250, inst=BUILD_TUPLE(arg=2, lineno=3059)\n", - "2024-10-16 10:11:07,413 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$242binary_subscr.10', '$quad_mz_values244.11', '$quad_index246.12', '$const248.13']\n", - "2024-10-16 10:11:07,414 - numba.core.byteflow - DEBUG - dispatch pc=252, inst=BINARY_SUBSCR(arg=None, lineno=3059)\n", - "2024-10-16 10:11:07,414 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$242binary_subscr.10', '$quad_mz_values244.11', '$250build_tuple.14']\n", - "2024-10-16 10:11:07,415 - numba.core.byteflow - DEBUG - dispatch pc=254, inst=LOAD_FAST(arg=4, lineno=3060)\n", - "2024-10-16 10:11:07,415 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$242binary_subscr.10', '$252binary_subscr.15']\n", - "2024-10-16 10:11:07,416 - numba.core.byteflow - DEBUG - dispatch pc=256, inst=CALL_FUNCTION(arg=3, lineno=3057)\n", - "2024-10-16 10:11:07,416 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$232load_global.5', '$242binary_subscr.10', '$252binary_subscr.15', '$quad_slices254.16']\n", - "2024-10-16 10:11:07,416 - numba.core.byteflow - DEBUG - dispatch pc=258, inst=POP_JUMP_IF_TRUE(arg=134, lineno=3057)\n", - "2024-10-16 10:11:07,417 - numba.core.byteflow - DEBUG - stack ['$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3', '$256call_function.17']\n", - "2024-10-16 10:11:07,417 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=260, stack=('$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3'), blockstack=(), npush=0), Edge(pc=266, stack=('$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,418 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=290 nstack_initial=4), State(pc_initial=260 nstack_initial=4), State(pc_initial=266 nstack_initial=4)])\n", - "2024-10-16 10:11:07,418 - numba.core.byteflow - DEBUG - stack: ['$phi290.0', '$phi290.1', '$phi290.2', '$phi290.3']\n", - "2024-10-16 10:11:07,419 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=290 nstack_initial=4)\n", - "2024-10-16 10:11:07,419 - numba.core.byteflow - DEBUG - dispatch pc=290, inst=LOAD_FAST(arg=18, lineno=3070)\n", - "2024-10-16 10:11:07,420 - numba.core.byteflow - DEBUG - stack ['$phi290.0', '$phi290.1', '$phi290.2', '$phi290.3']\n", - "2024-10-16 10:11:07,420 - numba.core.byteflow - DEBUG - dispatch pc=292, inst=POP_JUMP_IF_TRUE(arg=149, lineno=3070)\n", - "2024-10-16 10:11:07,421 - numba.core.byteflow - DEBUG - stack ['$phi290.0', '$phi290.1', '$phi290.2', '$phi290.3', '$is_valid_quad_index290.4']\n", - "2024-10-16 10:11:07,421 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=294, stack=('$phi290.0', '$phi290.1', '$phi290.2', '$phi290.3'), blockstack=(), npush=0), Edge(pc=296, stack=('$phi290.0', '$phi290.1', '$phi290.2', '$phi290.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,422 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=260 nstack_initial=4), State(pc_initial=266 nstack_initial=4), State(pc_initial=294 nstack_initial=4), State(pc_initial=296 nstack_initial=4)])\n", - "2024-10-16 10:11:07,422 - numba.core.byteflow - DEBUG - stack: ['$phi260.0', '$phi260.1', '$phi260.2', '$phi260.3']\n", - "2024-10-16 10:11:07,422 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=260 nstack_initial=4)\n", - "2024-10-16 10:11:07,423 - numba.core.byteflow - DEBUG - dispatch pc=260, inst=LOAD_CONST(arg=6, lineno=3062)\n", - "2024-10-16 10:11:07,423 - numba.core.byteflow - DEBUG - stack ['$phi260.0', '$phi260.1', '$phi260.2', '$phi260.3']\n", - "2024-10-16 10:11:07,424 - numba.core.byteflow - DEBUG - dispatch pc=262, inst=STORE_FAST(arg=18, lineno=3062)\n", - "2024-10-16 10:11:07,424 - numba.core.byteflow - DEBUG - stack ['$phi260.0', '$phi260.1', '$phi260.2', '$phi260.3', '$const260.4']\n", - "2024-10-16 10:11:07,425 - numba.core.byteflow - DEBUG - dispatch pc=264, inst=JUMP_FORWARD(arg=12, lineno=3062)\n", - "2024-10-16 10:11:07,425 - numba.core.byteflow - DEBUG - stack ['$phi260.0', '$phi260.1', '$phi260.2', '$phi260.3']\n", - "2024-10-16 10:11:07,426 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=290, stack=('$phi260.0', '$phi260.1', '$phi260.2', '$phi260.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,426 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=266 nstack_initial=4), State(pc_initial=294 nstack_initial=4), State(pc_initial=296 nstack_initial=4), State(pc_initial=290 nstack_initial=4)])\n", - "2024-10-16 10:11:07,427 - numba.core.byteflow - DEBUG - stack: ['$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3']\n", - "2024-10-16 10:11:07,427 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=266 nstack_initial=4)\n", - "2024-10-16 10:11:07,428 - numba.core.byteflow - DEBUG - dispatch pc=266, inst=LOAD_GLOBAL(arg=4, lineno=3063)\n", - "2024-10-16 10:11:07,428 - numba.core.byteflow - DEBUG - stack ['$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3']\n", - "2024-10-16 10:11:07,429 - numba.core.byteflow - DEBUG - dispatch pc=268, inst=LOAD_FAST(arg=9, lineno=3064)\n", - "2024-10-16 10:11:07,429 - numba.core.byteflow - DEBUG - stack ['$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3', '$266load_global.4']\n", - "2024-10-16 10:11:07,429 - numba.core.byteflow - DEBUG - dispatch pc=270, inst=LOAD_FAST(arg=15, lineno=3064)\n", - "2024-10-16 10:11:07,430 - numba.core.byteflow - DEBUG - stack ['$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3', '$266load_global.4', '$precursor_indices268.5']\n", - "2024-10-16 10:11:07,430 - numba.core.byteflow - DEBUG - dispatch pc=272, inst=BINARY_SUBSCR(arg=None, lineno=3064)\n", - "2024-10-16 10:11:07,431 - numba.core.byteflow - DEBUG - stack ['$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3', '$266load_global.4', '$precursor_indices268.5', '$quad_index270.6']\n", - "2024-10-16 10:11:07,431 - numba.core.byteflow - DEBUG - dispatch pc=274, inst=LOAD_FAST(arg=2, lineno=3065)\n", - "2024-10-16 10:11:07,432 - numba.core.byteflow - DEBUG - stack ['$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3', '$266load_global.4', '$272binary_subscr.7']\n", - "2024-10-16 10:11:07,432 - numba.core.byteflow - DEBUG - dispatch pc=276, inst=CALL_FUNCTION(arg=2, lineno=3063)\n", - "2024-10-16 10:11:07,432 - numba.core.byteflow - DEBUG - stack ['$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3', '$266load_global.4', '$272binary_subscr.7', '$precursor_slices274.8']\n", - "2024-10-16 10:11:07,433 - numba.core.byteflow - DEBUG - dispatch pc=278, inst=POP_JUMP_IF_TRUE(arg=144, lineno=3063)\n", - "2024-10-16 10:11:07,433 - numba.core.byteflow - DEBUG - stack ['$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3', '$276call_function.9']\n", - "2024-10-16 10:11:07,434 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=280, stack=('$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3'), blockstack=(), npush=0), Edge(pc=286, stack=('$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,434 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=294 nstack_initial=4), State(pc_initial=296 nstack_initial=4), State(pc_initial=290 nstack_initial=4), State(pc_initial=280 nstack_initial=4), State(pc_initial=286 nstack_initial=4)])\n", - "2024-10-16 10:11:07,435 - numba.core.byteflow - DEBUG - stack: ['$phi294.0', '$phi294.1', '$phi294.2', '$phi294.3']\n", - "2024-10-16 10:11:07,435 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=294 nstack_initial=4)\n", - "2024-10-16 10:11:07,436 - numba.core.byteflow - DEBUG - dispatch pc=294, inst=JUMP_ABSOLUTE(arg=84, lineno=3071)\n", - "2024-10-16 10:11:07,436 - numba.core.byteflow - DEBUG - stack ['$phi294.0', '$phi294.1', '$phi294.2', '$phi294.3']\n", - "2024-10-16 10:11:07,436 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=166, stack=('$phi294.0', '$phi294.1', '$phi294.2', '$phi294.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,437 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=296 nstack_initial=4), State(pc_initial=290 nstack_initial=4), State(pc_initial=280 nstack_initial=4), State(pc_initial=286 nstack_initial=4), State(pc_initial=166 nstack_initial=4)])\n", - "2024-10-16 10:11:07,437 - numba.core.byteflow - DEBUG - stack: ['$phi296.0', '$phi296.1', '$phi296.2', '$phi296.3']\n", - "2024-10-16 10:11:07,438 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=296 nstack_initial=4)\n", - "2024-10-16 10:11:07,438 - numba.core.byteflow - DEBUG - dispatch pc=296, inst=LOAD_FAST(arg=29, lineno=3072)\n", - "2024-10-16 10:11:07,439 - numba.core.byteflow - DEBUG - stack ['$phi296.0', '$phi296.1', '$phi296.2', '$phi296.3']\n", - "2024-10-16 10:11:07,439 - numba.core.byteflow - DEBUG - dispatch pc=298, inst=STORE_FAST(arg=31, lineno=3072)\n", - "2024-10-16 10:11:07,440 - numba.core.byteflow - DEBUG - stack ['$phi296.0', '$phi296.1', '$phi296.2', '$phi296.3', '$sparse_start296.4']\n", - "2024-10-16 10:11:07,440 - numba.core.byteflow - DEBUG - dispatch pc=300, inst=LOAD_FAST(arg=3, lineno=3073)\n", - "2024-10-16 10:11:07,441 - numba.core.byteflow - DEBUG - stack ['$phi296.0', '$phi296.1', '$phi296.2', '$phi296.3']\n", - "2024-10-16 10:11:07,441 - numba.core.byteflow - DEBUG - dispatch pc=302, inst=GET_ITER(arg=None, lineno=3073)\n", - "2024-10-16 10:11:07,441 - numba.core.byteflow - DEBUG - stack ['$phi296.0', '$phi296.1', '$phi296.2', '$phi296.3', '$tof_slices300.5']\n", - "2024-10-16 10:11:07,442 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=304, stack=('$phi296.0', '$phi296.1', '$phi296.2', '$phi296.3', '$302get_iter.6'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,442 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=290 nstack_initial=4), State(pc_initial=280 nstack_initial=4), State(pc_initial=286 nstack_initial=4), State(pc_initial=166 nstack_initial=4), State(pc_initial=304 nstack_initial=5)])\n", - "2024-10-16 10:11:07,443 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=280 nstack_initial=4), State(pc_initial=286 nstack_initial=4), State(pc_initial=166 nstack_initial=4), State(pc_initial=304 nstack_initial=5)])\n", - "2024-10-16 10:11:07,443 - numba.core.byteflow - DEBUG - stack: ['$phi280.0', '$phi280.1', '$phi280.2', '$phi280.3']\n", - "2024-10-16 10:11:07,444 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=280 nstack_initial=4)\n", - "2024-10-16 10:11:07,444 - numba.core.byteflow - DEBUG - dispatch pc=280, inst=LOAD_CONST(arg=6, lineno=3067)\n", - "2024-10-16 10:11:07,444 - numba.core.byteflow - DEBUG - stack ['$phi280.0', '$phi280.1', '$phi280.2', '$phi280.3']\n", - "2024-10-16 10:11:07,445 - numba.core.byteflow - DEBUG - dispatch pc=282, inst=STORE_FAST(arg=18, lineno=3067)\n", - "2024-10-16 10:11:07,445 - numba.core.byteflow - DEBUG - stack ['$phi280.0', '$phi280.1', '$phi280.2', '$phi280.3', '$const280.4']\n", - "2024-10-16 10:11:07,446 - numba.core.byteflow - DEBUG - dispatch pc=284, inst=JUMP_FORWARD(arg=2, lineno=3067)\n", - "2024-10-16 10:11:07,446 - numba.core.byteflow - DEBUG - stack ['$phi280.0', '$phi280.1', '$phi280.2', '$phi280.3']\n", - "2024-10-16 10:11:07,447 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=290, stack=('$phi280.0', '$phi280.1', '$phi280.2', '$phi280.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,447 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=286 nstack_initial=4), State(pc_initial=166 nstack_initial=4), State(pc_initial=304 nstack_initial=5), State(pc_initial=290 nstack_initial=4)])\n", - "2024-10-16 10:11:07,447 - numba.core.byteflow - DEBUG - stack: ['$phi286.0', '$phi286.1', '$phi286.2', '$phi286.3']\n", - "2024-10-16 10:11:07,448 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=286 nstack_initial=4)\n", - "2024-10-16 10:11:07,448 - numba.core.byteflow - DEBUG - dispatch pc=286, inst=LOAD_CONST(arg=2, lineno=3069)\n", - "2024-10-16 10:11:07,449 - numba.core.byteflow - DEBUG - stack ['$phi286.0', '$phi286.1', '$phi286.2', '$phi286.3']\n", - "2024-10-16 10:11:07,449 - numba.core.byteflow - DEBUG - dispatch pc=288, inst=STORE_FAST(arg=18, lineno=3069)\n", - "2024-10-16 10:11:07,450 - numba.core.byteflow - DEBUG - stack ['$phi286.0', '$phi286.1', '$phi286.2', '$phi286.3', '$const286.4']\n", - "2024-10-16 10:11:07,450 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=290, stack=('$phi286.0', '$phi286.1', '$phi286.2', '$phi286.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,450 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=166 nstack_initial=4), State(pc_initial=304 nstack_initial=5), State(pc_initial=290 nstack_initial=4), State(pc_initial=290 nstack_initial=4)])\n", - "2024-10-16 10:11:07,451 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=304 nstack_initial=5), State(pc_initial=290 nstack_initial=4), State(pc_initial=290 nstack_initial=4)])\n", - "2024-10-16 10:11:07,451 - numba.core.byteflow - DEBUG - stack: ['$phi304.0', '$phi304.1', '$phi304.2', '$phi304.3', '$phi304.4']\n", - "2024-10-16 10:11:07,452 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=304 nstack_initial=5)\n", - "2024-10-16 10:11:07,452 - numba.core.byteflow - DEBUG - dispatch pc=304, inst=FOR_ITER(arg=79, lineno=3073)\n", - "2024-10-16 10:11:07,453 - numba.core.byteflow - DEBUG - stack ['$phi304.0', '$phi304.1', '$phi304.2', '$phi304.3', '$phi304.4']\n", - "2024-10-16 10:11:07,453 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=464, stack=('$phi304.0', '$phi304.1', '$phi304.2', '$phi304.3'), blockstack=(), npush=0), Edge(pc=306, stack=('$phi304.0', '$phi304.1', '$phi304.2', '$phi304.3', '$phi304.4', '$304for_iter.6'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,453 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=290 nstack_initial=4), State(pc_initial=290 nstack_initial=4), State(pc_initial=464 nstack_initial=4), State(pc_initial=306 nstack_initial=6)])\n", - "2024-10-16 10:11:07,454 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=290 nstack_initial=4), State(pc_initial=464 nstack_initial=4), State(pc_initial=306 nstack_initial=6)])\n", - "2024-10-16 10:11:07,454 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=464 nstack_initial=4), State(pc_initial=306 nstack_initial=6)])\n", - "2024-10-16 10:11:07,455 - numba.core.byteflow - DEBUG - stack: ['$phi464.0', '$phi464.1', '$phi464.2', '$phi464.3']\n", - "2024-10-16 10:11:07,455 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=464 nstack_initial=4)\n", - "2024-10-16 10:11:07,456 - numba.core.byteflow - DEBUG - dispatch pc=464, inst=JUMP_ABSOLUTE(arg=84, lineno=3073)\n", - "2024-10-16 10:11:07,456 - numba.core.byteflow - DEBUG - stack ['$phi464.0', '$phi464.1', '$phi464.2', '$phi464.3']\n", - "2024-10-16 10:11:07,456 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=166, stack=('$phi464.0', '$phi464.1', '$phi464.2', '$phi464.3'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,457 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=306 nstack_initial=6), State(pc_initial=166 nstack_initial=4)])\n", - "2024-10-16 10:11:07,457 - numba.core.byteflow - DEBUG - stack: ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$phi306.5']\n", - "2024-10-16 10:11:07,458 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=306 nstack_initial=6)\n", - "2024-10-16 10:11:07,458 - numba.core.byteflow - DEBUG - dispatch pc=306, inst=UNPACK_SEQUENCE(arg=3, lineno=3073)\n", - "2024-10-16 10:11:07,459 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$phi306.5']\n", - "2024-10-16 10:11:07,459 - numba.core.byteflow - DEBUG - dispatch pc=308, inst=STORE_FAST(arg=32, lineno=3073)\n", - "2024-10-16 10:11:07,459 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$306unpack_sequence.8', '$306unpack_sequence.7', '$306unpack_sequence.6']\n", - "2024-10-16 10:11:07,460 - numba.core.byteflow - DEBUG - dispatch pc=310, inst=STORE_FAST(arg=33, lineno=3073)\n", - "2024-10-16 10:11:07,460 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$306unpack_sequence.8', '$306unpack_sequence.7']\n", - "2024-10-16 10:11:07,461 - numba.core.byteflow - DEBUG - dispatch pc=312, inst=STORE_FAST(arg=34, lineno=3073)\n", - "2024-10-16 10:11:07,461 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$306unpack_sequence.8']\n", - "2024-10-16 10:11:07,461 - numba.core.byteflow - DEBUG - dispatch pc=314, inst=LOAD_FAST(arg=31, lineno=3074)\n", - "2024-10-16 10:11:07,462 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4']\n", - "2024-10-16 10:11:07,462 - numba.core.byteflow - DEBUG - dispatch pc=316, inst=LOAD_GLOBAL(arg=5, lineno=3074)\n", - "2024-10-16 10:11:07,463 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10']\n", - "2024-10-16 10:11:07,463 - numba.core.byteflow - DEBUG - dispatch pc=318, inst=LOAD_METHOD(arg=6, lineno=3074)\n", - "2024-10-16 10:11:07,463 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10', '$316load_global.11']\n", - "2024-10-16 10:11:07,464 - numba.core.byteflow - DEBUG - dispatch pc=320, inst=LOAD_FAST(arg=12, lineno=3075)\n", - "2024-10-16 10:11:07,464 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10', '$318load_method.12']\n", - "2024-10-16 10:11:07,465 - numba.core.byteflow - DEBUG - dispatch pc=322, inst=LOAD_FAST(arg=31, lineno=3075)\n", - "2024-10-16 10:11:07,465 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10', '$318load_method.12', '$tof_indices320.13']\n", - "2024-10-16 10:11:07,465 - numba.core.byteflow - DEBUG - dispatch pc=324, inst=LOAD_FAST(arg=30, lineno=3075)\n", - "2024-10-16 10:11:07,466 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10', '$318load_method.12', '$tof_indices320.13', '$idx322.14']\n", - "2024-10-16 10:11:07,466 - numba.core.byteflow - DEBUG - dispatch pc=326, inst=BUILD_SLICE(arg=2, lineno=3075)\n", - "2024-10-16 10:11:07,467 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10', '$318load_method.12', '$tof_indices320.13', '$idx322.14', '$sparse_end324.15']\n", - "2024-10-16 10:11:07,467 - numba.core.byteflow - DEBUG - dispatch pc=328, inst=BINARY_SUBSCR(arg=None, lineno=3075)\n", - "2024-10-16 10:11:07,468 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10', '$318load_method.12', '$tof_indices320.13', '$326build_slice.17']\n", - "2024-10-16 10:11:07,468 - numba.core.byteflow - DEBUG - dispatch pc=330, inst=LOAD_FAST(arg=32, lineno=3076)\n", - "2024-10-16 10:11:07,468 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10', '$318load_method.12', '$328binary_subscr.18']\n", - "2024-10-16 10:11:07,469 - numba.core.byteflow - DEBUG - dispatch pc=332, inst=CALL_METHOD(arg=2, lineno=3074)\n", - "2024-10-16 10:11:07,469 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10', '$318load_method.12', '$328binary_subscr.18', '$tof_start330.19']\n", - "2024-10-16 10:11:07,470 - numba.core.byteflow - DEBUG - dispatch pc=334, inst=INPLACE_ADD(arg=None, lineno=3074)\n", - "2024-10-16 10:11:07,470 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$idx314.10', '$332call_method.20']\n", - "2024-10-16 10:11:07,470 - numba.core.byteflow - DEBUG - dispatch pc=336, inst=STORE_FAST(arg=31, lineno=3074)\n", - "2024-10-16 10:11:07,471 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$334inplace_add.21']\n", - "2024-10-16 10:11:07,471 - numba.core.byteflow - DEBUG - dispatch pc=338, inst=LOAD_FAST(arg=12, lineno=3078)\n", - "2024-10-16 10:11:07,472 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4']\n", - "2024-10-16 10:11:07,472 - numba.core.byteflow - DEBUG - dispatch pc=340, inst=LOAD_FAST(arg=31, lineno=3078)\n", - "2024-10-16 10:11:07,472 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$tof_indices338.22']\n", - "2024-10-16 10:11:07,473 - numba.core.byteflow - DEBUG - dispatch pc=342, inst=BINARY_SUBSCR(arg=None, lineno=3078)\n", - "2024-10-16 10:11:07,473 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$tof_indices338.22', '$idx340.23']\n", - "2024-10-16 10:11:07,474 - numba.core.byteflow - DEBUG - dispatch pc=344, inst=STORE_FAST(arg=35, lineno=3078)\n", - "2024-10-16 10:11:07,474 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$342binary_subscr.24']\n", - "2024-10-16 10:11:07,474 - numba.core.byteflow - DEBUG - dispatch pc=346, inst=LOAD_FAST(arg=35, lineno=3079)\n", - "2024-10-16 10:11:07,475 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4']\n", - "2024-10-16 10:11:07,475 - numba.core.byteflow - DEBUG - dispatch pc=348, inst=LOAD_FAST(arg=33, lineno=3079)\n", - "2024-10-16 10:11:07,475 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$tof_value346.25']\n", - "2024-10-16 10:11:07,476 - numba.core.byteflow - DEBUG - dispatch pc=350, inst=COMPARE_OP(arg=0, lineno=3079)\n", - "2024-10-16 10:11:07,476 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$tof_value346.25', '$tof_stop348.26']\n", - "2024-10-16 10:11:07,477 - numba.core.byteflow - DEBUG - dispatch pc=352, inst=POP_JUMP_IF_FALSE(arg=232, lineno=3079)\n", - "2024-10-16 10:11:07,477 - numba.core.byteflow - DEBUG - stack ['$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4', '$350compare_op.27']\n", - "2024-10-16 10:11:07,477 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=354, stack=('$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4'), blockstack=(), npush=0), Edge(pc=462, stack=('$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,478 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=166 nstack_initial=4), State(pc_initial=354 nstack_initial=5), State(pc_initial=462 nstack_initial=5)])\n", - "2024-10-16 10:11:07,478 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=354 nstack_initial=5), State(pc_initial=462 nstack_initial=5)])\n", - "2024-10-16 10:11:07,479 - numba.core.byteflow - DEBUG - stack: ['$phi354.0', '$phi354.1', '$phi354.2', '$phi354.3', '$phi354.4']\n", - "2024-10-16 10:11:07,479 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=354 nstack_initial=5)\n", - "2024-10-16 10:11:07,480 - numba.core.byteflow - DEBUG - dispatch pc=354, inst=LOAD_FAST(arg=31, lineno=3079)\n", - "2024-10-16 10:11:07,480 - numba.core.byteflow - DEBUG - stack ['$phi354.0', '$phi354.1', '$phi354.2', '$phi354.3', '$phi354.4']\n", - "2024-10-16 10:11:07,480 - numba.core.byteflow - DEBUG - dispatch pc=356, inst=LOAD_FAST(arg=30, lineno=3079)\n", - "2024-10-16 10:11:07,481 - numba.core.byteflow - DEBUG - stack ['$phi354.0', '$phi354.1', '$phi354.2', '$phi354.3', '$phi354.4', '$idx354.5']\n", - "2024-10-16 10:11:07,481 - numba.core.byteflow - DEBUG - dispatch pc=358, inst=COMPARE_OP(arg=0, lineno=3079)\n", - "2024-10-16 10:11:07,481 - numba.core.byteflow - DEBUG - stack ['$phi354.0', '$phi354.1', '$phi354.2', '$phi354.3', '$phi354.4', '$idx354.5', '$sparse_end356.6']\n", - "2024-10-16 10:11:07,482 - numba.core.byteflow - DEBUG - dispatch pc=360, inst=POP_JUMP_IF_FALSE(arg=232, lineno=3079)\n", - "2024-10-16 10:11:07,482 - numba.core.byteflow - DEBUG - stack ['$phi354.0', '$phi354.1', '$phi354.2', '$phi354.3', '$phi354.4', '$358compare_op.7']\n", - "2024-10-16 10:11:07,483 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=362, stack=('$phi354.0', '$phi354.1', '$phi354.2', '$phi354.3', '$phi354.4'), blockstack=(), npush=0), Edge(pc=462, stack=('$phi354.0', '$phi354.1', '$phi354.2', '$phi354.3', '$phi354.4'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,483 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=462 nstack_initial=5), State(pc_initial=362 nstack_initial=5), State(pc_initial=462 nstack_initial=5)])\n", - "2024-10-16 10:11:07,483 - numba.core.byteflow - DEBUG - stack: ['$phi462.0', '$phi462.1', '$phi462.2', '$phi462.3', '$phi462.4']\n", - "2024-10-16 10:11:07,484 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=462 nstack_initial=5)\n", - "2024-10-16 10:11:07,484 - numba.core.byteflow - DEBUG - dispatch pc=462, inst=JUMP_ABSOLUTE(arg=153, lineno=3079)\n", - "2024-10-16 10:11:07,512 - numba.core.byteflow - DEBUG - stack ['$phi462.0', '$phi462.1', '$phi462.2', '$phi462.3', '$phi462.4']\n", - "2024-10-16 10:11:07,513 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=304, stack=('$phi462.0', '$phi462.1', '$phi462.2', '$phi462.3', '$phi462.4'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,513 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=362 nstack_initial=5), State(pc_initial=462 nstack_initial=5), State(pc_initial=304 nstack_initial=5)])\n", - "2024-10-16 10:11:07,514 - numba.core.byteflow - DEBUG - stack: ['$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4']\n", - "2024-10-16 10:11:07,514 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=362 nstack_initial=5)\n", - "2024-10-16 10:11:07,515 - numba.core.byteflow - DEBUG - dispatch pc=362, inst=LOAD_FAST(arg=35, lineno=3080)\n", - "2024-10-16 10:11:07,516 - numba.core.byteflow - DEBUG - stack ['$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4']\n", - "2024-10-16 10:11:07,516 - numba.core.byteflow - DEBUG - dispatch pc=364, inst=LOAD_GLOBAL(arg=7, lineno=3080)\n", - "2024-10-16 10:11:07,517 - numba.core.byteflow - DEBUG - stack ['$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4', '$tof_value362.5']\n", - "2024-10-16 10:11:07,517 - numba.core.byteflow - DEBUG - dispatch pc=366, inst=LOAD_FAST(arg=32, lineno=3081)\n", - "2024-10-16 10:11:07,518 - numba.core.byteflow - DEBUG - stack ['$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4', '$tof_value362.5', '$364load_global.6']\n", - "2024-10-16 10:11:07,518 - numba.core.byteflow - DEBUG - dispatch pc=368, inst=LOAD_FAST(arg=33, lineno=3082)\n", - "2024-10-16 10:11:07,519 - numba.core.byteflow - DEBUG - stack ['$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4', '$tof_value362.5', '$364load_global.6', '$tof_start366.7']\n", - "2024-10-16 10:11:07,520 - numba.core.byteflow - DEBUG - dispatch pc=370, inst=LOAD_FAST(arg=34, lineno=3083)\n", - "2024-10-16 10:11:07,521 - numba.core.byteflow - DEBUG - stack ['$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4', '$tof_value362.5', '$364load_global.6', '$tof_start366.7', '$tof_stop368.8']\n", - "2024-10-16 10:11:07,521 - numba.core.byteflow - DEBUG - dispatch pc=372, inst=CALL_FUNCTION(arg=3, lineno=3080)\n", - "2024-10-16 10:11:07,522 - numba.core.byteflow - DEBUG - stack ['$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4', '$tof_value362.5', '$364load_global.6', '$tof_start366.7', '$tof_stop368.8', '$tof_step370.9']\n", - "2024-10-16 10:11:07,522 - numba.core.byteflow - DEBUG - dispatch pc=374, inst=CONTAINS_OP(arg=0, lineno=3080)\n", - "2024-10-16 10:11:07,523 - numba.core.byteflow - DEBUG - stack ['$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4', '$tof_value362.5', '$372call_function.10']\n", - "2024-10-16 10:11:07,523 - numba.core.byteflow - DEBUG - dispatch pc=376, inst=POP_JUMP_IF_FALSE(arg=216, lineno=3080)\n", - "2024-10-16 10:11:07,525 - numba.core.byteflow - DEBUG - stack ['$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4', '$374contains_op.11']\n", - "2024-10-16 10:11:07,525 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=378, stack=('$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4'), blockstack=(), npush=0), Edge(pc=430, stack=('$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,526 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=462 nstack_initial=5), State(pc_initial=304 nstack_initial=5), State(pc_initial=378 nstack_initial=5), State(pc_initial=430 nstack_initial=5)])\n", - "2024-10-16 10:11:07,527 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=304 nstack_initial=5), State(pc_initial=378 nstack_initial=5), State(pc_initial=430 nstack_initial=5)])\n", - "2024-10-16 10:11:07,527 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=378 nstack_initial=5), State(pc_initial=430 nstack_initial=5)])\n", - "2024-10-16 10:11:07,528 - numba.core.byteflow - DEBUG - stack: ['$phi378.0', '$phi378.1', '$phi378.2', '$phi378.3', '$phi378.4']\n", - "2024-10-16 10:11:07,528 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=378 nstack_initial=5)\n", - "2024-10-16 10:11:07,529 - numba.core.byteflow - DEBUG - dispatch pc=378, inst=LOAD_FAST(arg=13, lineno=3085)\n", - "2024-10-16 10:11:07,529 - numba.core.byteflow - DEBUG - stack ['$phi378.0', '$phi378.1', '$phi378.2', '$phi378.3', '$phi378.4']\n", - "2024-10-16 10:11:07,530 - numba.core.byteflow - DEBUG - dispatch pc=380, inst=LOAD_FAST(arg=31, lineno=3085)\n", - "2024-10-16 10:11:07,530 - numba.core.byteflow - DEBUG - stack ['$phi378.0', '$phi378.1', '$phi378.2', '$phi378.3', '$phi378.4', '$intensities378.5']\n", - "2024-10-16 10:11:07,531 - numba.core.byteflow - DEBUG - dispatch pc=382, inst=BINARY_SUBSCR(arg=None, lineno=3085)\n", - "2024-10-16 10:11:07,532 - numba.core.byteflow - DEBUG - stack ['$phi378.0', '$phi378.1', '$phi378.2', '$phi378.3', '$phi378.4', '$intensities378.5', '$idx380.6']\n", - "2024-10-16 10:11:07,532 - numba.core.byteflow - DEBUG - dispatch pc=384, inst=STORE_FAST(arg=36, lineno=3085)\n", - "2024-10-16 10:11:07,533 - numba.core.byteflow - DEBUG - stack ['$phi378.0', '$phi378.1', '$phi378.2', '$phi378.3', '$phi378.4', '$382binary_subscr.7']\n", - "2024-10-16 10:11:07,534 - numba.core.byteflow - DEBUG - dispatch pc=386, inst=LOAD_FAST(arg=5, lineno=3089)\n", - "2024-10-16 10:11:07,534 - numba.core.byteflow - DEBUG - stack ['$phi378.0', '$phi378.1', '$phi378.2', '$phi378.3', '$phi378.4']\n", - "2024-10-16 10:11:07,535 - numba.core.byteflow - DEBUG - dispatch pc=388, inst=GET_ITER(arg=None, lineno=3086)\n", - "2024-10-16 10:11:07,536 - numba.core.byteflow - DEBUG - stack ['$phi378.0', '$phi378.1', '$phi378.2', '$phi378.3', '$phi378.4', '$intensity_slices386.8']\n", - "2024-10-16 10:11:07,536 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=390, stack=('$phi378.0', '$phi378.1', '$phi378.2', '$phi378.3', '$phi378.4', '$388get_iter.9'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,537 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=430 nstack_initial=5), State(pc_initial=390 nstack_initial=6)])\n", - "2024-10-16 10:11:07,537 - numba.core.byteflow - DEBUG - stack: ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4']\n", - "2024-10-16 10:11:07,538 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=430 nstack_initial=5)\n", - "2024-10-16 10:11:07,538 - numba.core.byteflow - DEBUG - dispatch pc=430, inst=LOAD_FAST(arg=31, lineno=3094)\n", - "2024-10-16 10:11:07,540 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4']\n", - "2024-10-16 10:11:07,540 - numba.core.byteflow - DEBUG - dispatch pc=432, inst=LOAD_CONST(arg=4, lineno=3094)\n", - "2024-10-16 10:11:07,541 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4', '$idx430.5']\n", - "2024-10-16 10:11:07,541 - numba.core.byteflow - DEBUG - dispatch pc=434, inst=INPLACE_ADD(arg=None, lineno=3094)\n", - "2024-10-16 10:11:07,542 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4', '$idx430.5', '$const432.6']\n", - "2024-10-16 10:11:07,543 - numba.core.byteflow - DEBUG - dispatch pc=436, inst=STORE_FAST(arg=31, lineno=3094)\n", - "2024-10-16 10:11:07,543 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4', '$434inplace_add.7']\n", - "2024-10-16 10:11:07,544 - numba.core.byteflow - DEBUG - dispatch pc=438, inst=LOAD_FAST(arg=12, lineno=3095)\n", - "2024-10-16 10:11:07,545 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4']\n", - "2024-10-16 10:11:07,545 - numba.core.byteflow - DEBUG - dispatch pc=440, inst=LOAD_FAST(arg=31, lineno=3095)\n", - "2024-10-16 10:11:07,546 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4', '$tof_indices438.8']\n", - "2024-10-16 10:11:07,546 - numba.core.byteflow - DEBUG - dispatch pc=442, inst=BINARY_SUBSCR(arg=None, lineno=3095)\n", - "2024-10-16 10:11:07,547 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4', '$tof_indices438.8', '$idx440.9']\n", - "2024-10-16 10:11:07,548 - numba.core.byteflow - DEBUG - dispatch pc=444, inst=STORE_FAST(arg=35, lineno=3095)\n", - "2024-10-16 10:11:07,549 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4', '$442binary_subscr.10']\n", - "2024-10-16 10:11:07,549 - numba.core.byteflow - DEBUG - dispatch pc=446, inst=LOAD_FAST(arg=35, lineno=3079)\n", - "2024-10-16 10:11:07,550 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4']\n", - "2024-10-16 10:11:07,550 - numba.core.byteflow - DEBUG - dispatch pc=448, inst=LOAD_FAST(arg=33, lineno=3079)\n", - "2024-10-16 10:11:07,551 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4', '$tof_value446.11']\n", - "2024-10-16 10:11:07,552 - numba.core.byteflow - DEBUG - dispatch pc=450, inst=COMPARE_OP(arg=0, lineno=3079)\n", - "2024-10-16 10:11:07,552 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4', '$tof_value446.11', '$tof_stop448.12']\n", - "2024-10-16 10:11:07,553 - numba.core.byteflow - DEBUG - dispatch pc=452, inst=POP_JUMP_IF_FALSE(arg=232, lineno=3079)\n", - "2024-10-16 10:11:07,554 - numba.core.byteflow - DEBUG - stack ['$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4', '$450compare_op.13']\n", - "2024-10-16 10:11:07,554 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=454, stack=('$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4'), blockstack=(), npush=0), Edge(pc=462, stack=('$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,555 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=390 nstack_initial=6), State(pc_initial=454 nstack_initial=5), State(pc_initial=462 nstack_initial=5)])\n", - "2024-10-16 10:11:07,556 - numba.core.byteflow - DEBUG - stack: ['$phi390.0', '$phi390.1', '$phi390.2', '$phi390.3', '$phi390.4', '$phi390.5']\n", - "2024-10-16 10:11:07,556 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=390 nstack_initial=6)\n", - "2024-10-16 10:11:07,557 - numba.core.byteflow - DEBUG - dispatch pc=390, inst=FOR_ITER(arg=19, lineno=3086)\n", - "2024-10-16 10:11:07,558 - numba.core.byteflow - DEBUG - stack ['$phi390.0', '$phi390.1', '$phi390.2', '$phi390.3', '$phi390.4', '$phi390.5']\n", - "2024-10-16 10:11:07,558 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=430, stack=('$phi390.0', '$phi390.1', '$phi390.2', '$phi390.3', '$phi390.4'), blockstack=(), npush=0), Edge(pc=392, stack=('$phi390.0', '$phi390.1', '$phi390.2', '$phi390.3', '$phi390.4', '$phi390.5', '$390for_iter.7'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,559 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=454 nstack_initial=5), State(pc_initial=462 nstack_initial=5), State(pc_initial=430 nstack_initial=5), State(pc_initial=392 nstack_initial=7)])\n", - "2024-10-16 10:11:07,559 - numba.core.byteflow - DEBUG - stack: ['$phi454.0', '$phi454.1', '$phi454.2', '$phi454.3', '$phi454.4']\n", - "2024-10-16 10:11:07,560 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=454 nstack_initial=5)\n", - "2024-10-16 10:11:07,561 - numba.core.byteflow - DEBUG - dispatch pc=454, inst=LOAD_FAST(arg=31, lineno=3079)\n", - "2024-10-16 10:11:07,561 - numba.core.byteflow - DEBUG - stack ['$phi454.0', '$phi454.1', '$phi454.2', '$phi454.3', '$phi454.4']\n", - "2024-10-16 10:11:07,562 - numba.core.byteflow - DEBUG - dispatch pc=456, inst=LOAD_FAST(arg=30, lineno=3079)\n", - "2024-10-16 10:11:07,563 - numba.core.byteflow - DEBUG - stack ['$phi454.0', '$phi454.1', '$phi454.2', '$phi454.3', '$phi454.4', '$idx454.5']\n", - "2024-10-16 10:11:07,563 - numba.core.byteflow - DEBUG - dispatch pc=458, inst=COMPARE_OP(arg=0, lineno=3079)\n", - "2024-10-16 10:11:07,564 - numba.core.byteflow - DEBUG - stack ['$phi454.0', '$phi454.1', '$phi454.2', '$phi454.3', '$phi454.4', '$idx454.5', '$sparse_end456.6']\n", - "2024-10-16 10:11:07,565 - numba.core.byteflow - DEBUG - dispatch pc=460, inst=POP_JUMP_IF_TRUE(arg=182, lineno=3079)\n", - "2024-10-16 10:11:07,565 - numba.core.byteflow - DEBUG - stack ['$phi454.0', '$phi454.1', '$phi454.2', '$phi454.3', '$phi454.4', '$458compare_op.7']\n", - "2024-10-16 10:11:07,566 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=462, stack=('$phi454.0', '$phi454.1', '$phi454.2', '$phi454.3', '$phi454.4'), blockstack=(), npush=0), Edge(pc=362, stack=('$phi454.0', '$phi454.1', '$phi454.2', '$phi454.3', '$phi454.4'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,567 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=462 nstack_initial=5), State(pc_initial=430 nstack_initial=5), State(pc_initial=392 nstack_initial=7), State(pc_initial=462 nstack_initial=5), State(pc_initial=362 nstack_initial=5)])\n", - "2024-10-16 10:11:07,567 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=430 nstack_initial=5), State(pc_initial=392 nstack_initial=7), State(pc_initial=462 nstack_initial=5), State(pc_initial=362 nstack_initial=5)])\n", - "2024-10-16 10:11:07,568 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=392 nstack_initial=7), State(pc_initial=462 nstack_initial=5), State(pc_initial=362 nstack_initial=5)])\n", - "2024-10-16 10:11:07,569 - numba.core.byteflow - DEBUG - stack: ['$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5', '$phi392.6']\n", - "2024-10-16 10:11:07,569 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=392 nstack_initial=7)\n", - "2024-10-16 10:11:07,570 - numba.core.byteflow - DEBUG - dispatch pc=392, inst=UNPACK_SEQUENCE(arg=2, lineno=3086)\n", - "2024-10-16 10:11:07,571 - numba.core.byteflow - DEBUG - stack ['$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5', '$phi392.6']\n", - "2024-10-16 10:11:07,571 - numba.core.byteflow - DEBUG - dispatch pc=394, inst=STORE_FAST(arg=37, lineno=3087)\n", - "2024-10-16 10:11:07,572 - numba.core.byteflow - DEBUG - stack ['$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5', '$392unpack_sequence.8', '$392unpack_sequence.7']\n", - "2024-10-16 10:11:07,572 - numba.core.byteflow - DEBUG - dispatch pc=396, inst=STORE_FAST(arg=38, lineno=3088)\n", - "2024-10-16 10:11:07,573 - numba.core.byteflow - DEBUG - stack ['$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5', '$392unpack_sequence.8']\n", - "2024-10-16 10:11:07,574 - numba.core.byteflow - DEBUG - dispatch pc=398, inst=LOAD_FAST(arg=37, lineno=3090)\n", - "2024-10-16 10:11:07,574 - numba.core.byteflow - DEBUG - stack ['$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5']\n", - "2024-10-16 10:11:07,575 - numba.core.byteflow - DEBUG - dispatch pc=400, inst=LOAD_FAST(arg=36, lineno=3090)\n", - "2024-10-16 10:11:07,576 - numba.core.byteflow - DEBUG - stack ['$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5', '$low_intensity398.10']\n", - "2024-10-16 10:11:07,576 - numba.core.byteflow - DEBUG - dispatch pc=402, inst=COMPARE_OP(arg=1, lineno=3090)\n", - "2024-10-16 10:11:07,577 - numba.core.byteflow - DEBUG - stack ['$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5', '$low_intensity398.10', '$intensity400.11']\n", - "2024-10-16 10:11:07,578 - numba.core.byteflow - DEBUG - dispatch pc=404, inst=POP_JUMP_IF_FALSE(arg=215, lineno=3090)\n", - "2024-10-16 10:11:07,578 - numba.core.byteflow - DEBUG - stack ['$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5', '$402compare_op.12']\n", - "2024-10-16 10:11:07,579 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=406, stack=('$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5'), blockstack=(), npush=0), Edge(pc=428, stack=('$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,580 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=462 nstack_initial=5), State(pc_initial=362 nstack_initial=5), State(pc_initial=406 nstack_initial=6), State(pc_initial=428 nstack_initial=6)])\n", - "2024-10-16 10:11:07,580 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=362 nstack_initial=5), State(pc_initial=406 nstack_initial=6), State(pc_initial=428 nstack_initial=6)])\n", - "2024-10-16 10:11:07,581 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=406 nstack_initial=6), State(pc_initial=428 nstack_initial=6)])\n", - "2024-10-16 10:11:07,581 - numba.core.byteflow - DEBUG - stack: ['$phi406.0', '$phi406.1', '$phi406.2', '$phi406.3', '$phi406.4', '$phi406.5']\n", - "2024-10-16 10:11:07,582 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=406 nstack_initial=6)\n", - "2024-10-16 10:11:07,583 - numba.core.byteflow - DEBUG - dispatch pc=406, inst=LOAD_FAST(arg=36, lineno=3091)\n", - "2024-10-16 10:11:07,583 - numba.core.byteflow - DEBUG - stack ['$phi406.0', '$phi406.1', '$phi406.2', '$phi406.3', '$phi406.4', '$phi406.5']\n", - "2024-10-16 10:11:07,584 - numba.core.byteflow - DEBUG - dispatch pc=408, inst=LOAD_FAST(arg=38, lineno=3091)\n", - "2024-10-16 10:11:07,585 - numba.core.byteflow - DEBUG - stack ['$phi406.0', '$phi406.1', '$phi406.2', '$phi406.3', '$phi406.4', '$phi406.5', '$intensity406.6']\n", - "2024-10-16 10:11:07,585 - numba.core.byteflow - DEBUG - dispatch pc=410, inst=COMPARE_OP(arg=1, lineno=3091)\n", - "2024-10-16 10:11:07,586 - numba.core.byteflow - DEBUG - stack ['$phi406.0', '$phi406.1', '$phi406.2', '$phi406.3', '$phi406.4', '$phi406.5', '$intensity406.6', '$high_intensity408.7']\n", - "2024-10-16 10:11:07,587 - numba.core.byteflow - DEBUG - dispatch pc=412, inst=POP_JUMP_IF_FALSE(arg=215, lineno=3091)\n", - "2024-10-16 10:11:07,587 - numba.core.byteflow - DEBUG - stack ['$phi406.0', '$phi406.1', '$phi406.2', '$phi406.3', '$phi406.4', '$phi406.5', '$410compare_op.8']\n", - "2024-10-16 10:11:07,588 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=414, stack=('$phi406.0', '$phi406.1', '$phi406.2', '$phi406.3', '$phi406.4', '$phi406.5'), blockstack=(), npush=0), Edge(pc=428, stack=('$phi406.0', '$phi406.1', '$phi406.2', '$phi406.3', '$phi406.4', '$phi406.5'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,589 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=428 nstack_initial=6), State(pc_initial=414 nstack_initial=6), State(pc_initial=428 nstack_initial=6)])\n", - "2024-10-16 10:11:07,589 - numba.core.byteflow - DEBUG - stack: ['$phi428.0', '$phi428.1', '$phi428.2', '$phi428.3', '$phi428.4', '$phi428.5']\n", - "2024-10-16 10:11:07,590 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=428 nstack_initial=6)\n", - "2024-10-16 10:11:07,591 - numba.core.byteflow - DEBUG - dispatch pc=428, inst=JUMP_ABSOLUTE(arg=196, lineno=3093)\n", - "2024-10-16 10:11:07,591 - numba.core.byteflow - DEBUG - stack ['$phi428.0', '$phi428.1', '$phi428.2', '$phi428.3', '$phi428.4', '$phi428.5']\n", - "2024-10-16 10:11:07,592 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=390, stack=('$phi428.0', '$phi428.1', '$phi428.2', '$phi428.3', '$phi428.4', '$phi428.5'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,593 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=414 nstack_initial=6), State(pc_initial=428 nstack_initial=6), State(pc_initial=390 nstack_initial=6)])\n", - "2024-10-16 10:11:07,593 - numba.core.byteflow - DEBUG - stack: ['$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4', '$phi414.5']\n", - "2024-10-16 10:11:07,594 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=414 nstack_initial=6)\n", - "2024-10-16 10:11:07,595 - numba.core.byteflow - DEBUG - dispatch pc=414, inst=LOAD_FAST(arg=14, lineno=3092)\n", - "2024-10-16 10:11:07,596 - numba.core.byteflow - DEBUG - stack ['$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4', '$phi414.5']\n", - "2024-10-16 10:11:07,596 - numba.core.byteflow - DEBUG - dispatch pc=416, inst=LOAD_METHOD(arg=8, lineno=3092)\n", - "2024-10-16 10:11:07,597 - numba.core.byteflow - DEBUG - stack ['$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4', '$phi414.5', '$result414.6']\n", - "2024-10-16 10:11:07,597 - numba.core.byteflow - DEBUG - dispatch pc=418, inst=LOAD_FAST(arg=31, lineno=3092)\n", - "2024-10-16 10:11:07,598 - numba.core.byteflow - DEBUG - stack ['$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4', '$phi414.5', '$416load_method.7']\n", - "2024-10-16 10:11:07,598 - numba.core.byteflow - DEBUG - dispatch pc=420, inst=CALL_METHOD(arg=1, lineno=3092)\n", - "2024-10-16 10:11:07,599 - numba.core.byteflow - DEBUG - stack ['$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4', '$phi414.5', '$416load_method.7', '$idx418.8']\n", - "2024-10-16 10:11:07,600 - numba.core.byteflow - DEBUG - dispatch pc=422, inst=POP_TOP(arg=None, lineno=3092)\n", - "2024-10-16 10:11:07,601 - numba.core.byteflow - DEBUG - stack ['$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4', '$phi414.5', '$420call_method.9']\n", - "2024-10-16 10:11:07,601 - numba.core.byteflow - DEBUG - dispatch pc=424, inst=POP_TOP(arg=None, lineno=3093)\n", - "2024-10-16 10:11:07,602 - numba.core.byteflow - DEBUG - stack ['$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4', '$phi414.5']\n", - "2024-10-16 10:11:07,602 - numba.core.byteflow - DEBUG - dispatch pc=426, inst=JUMP_FORWARD(arg=1, lineno=3093)\n", - "2024-10-16 10:11:07,603 - numba.core.byteflow - DEBUG - stack ['$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4']\n", - "2024-10-16 10:11:07,603 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=430, stack=('$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:07,605 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=428 nstack_initial=6), State(pc_initial=390 nstack_initial=6), State(pc_initial=430 nstack_initial=5)])\n", - "2024-10-16 10:11:07,605 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=390 nstack_initial=6), State(pc_initial=430 nstack_initial=5)])\n", - "2024-10-16 10:11:07,606 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=430 nstack_initial=5)])\n", - "2024-10-16 10:11:07,606 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:07,608 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=66 nstack_initial=1): {'$phi66.0'},\n", - " State(pc_initial=68 nstack_initial=2): {'$phi68.1'},\n", - " State(pc_initial=110 nstack_initial=2): {'$phi110.1'},\n", - " State(pc_initial=112 nstack_initial=3): {'$phi112.2'},\n", - " State(pc_initial=122 nstack_initial=3): {'$phi122.2'},\n", - " State(pc_initial=124 nstack_initial=4): {'$phi124.3'},\n", - " State(pc_initial=166 nstack_initial=4): {'$phi166.3'},\n", - " State(pc_initial=168 nstack_initial=5): {'$phi168.4'},\n", - " State(pc_initial=182 nstack_initial=4): set(),\n", - " State(pc_initial=184 nstack_initial=4): set(),\n", - " State(pc_initial=192 nstack_initial=4): set(),\n", - " State(pc_initial=220 nstack_initial=4): set(),\n", - " State(pc_initial=228 nstack_initial=4): set(),\n", - " State(pc_initial=260 nstack_initial=4): set(),\n", - " State(pc_initial=266 nstack_initial=4): set(),\n", - " State(pc_initial=280 nstack_initial=4): set(),\n", - " State(pc_initial=286 nstack_initial=4): set(),\n", - " State(pc_initial=290 nstack_initial=4): set(),\n", - " State(pc_initial=294 nstack_initial=4): set(),\n", - " State(pc_initial=296 nstack_initial=4): set(),\n", - " State(pc_initial=304 nstack_initial=5): {'$phi304.4'},\n", - " State(pc_initial=306 nstack_initial=6): {'$phi306.5'},\n", - " State(pc_initial=354 nstack_initial=5): set(),\n", - " State(pc_initial=362 nstack_initial=5): set(),\n", - " State(pc_initial=378 nstack_initial=5): set(),\n", - " State(pc_initial=390 nstack_initial=6): {'$phi390.5'},\n", - " State(pc_initial=392 nstack_initial=7): {'$phi392.6'},\n", - " State(pc_initial=406 nstack_initial=6): set(),\n", - " State(pc_initial=414 nstack_initial=6): set(),\n", - " State(pc_initial=428 nstack_initial=6): set(),\n", - " State(pc_initial=430 nstack_initial=5): set(),\n", - " State(pc_initial=454 nstack_initial=5): set(),\n", - " State(pc_initial=462 nstack_initial=5): set(),\n", - " State(pc_initial=464 nstack_initial=4): set(),\n", - " State(pc_initial=466 nstack_initial=3): set(),\n", - " State(pc_initial=468 nstack_initial=2): set(),\n", - " State(pc_initial=470 nstack_initial=1): set(),\n", - " State(pc_initial=472 nstack_initial=0): set()})\n", - "2024-10-16 10:11:07,609 - numba.core.byteflow - DEBUG - defmap: {'$phi110.1': State(pc_initial=68 nstack_initial=2),\n", - " '$phi112.2': State(pc_initial=110 nstack_initial=2),\n", - " '$phi122.2': State(pc_initial=112 nstack_initial=3),\n", - " '$phi124.3': State(pc_initial=122 nstack_initial=3),\n", - " '$phi166.3': State(pc_initial=124 nstack_initial=4),\n", - " '$phi168.4': State(pc_initial=166 nstack_initial=4),\n", - " '$phi304.4': State(pc_initial=296 nstack_initial=4),\n", - " '$phi306.5': State(pc_initial=304 nstack_initial=5),\n", - " '$phi390.5': State(pc_initial=378 nstack_initial=5),\n", - " '$phi392.6': State(pc_initial=390 nstack_initial=6),\n", - " '$phi66.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi68.1': State(pc_initial=66 nstack_initial=1)}\n", - "2024-10-16 10:11:07,610 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi110.0': {('$phi468.0',\n", - " State(pc_initial=468 nstack_initial=2)),\n", - " ('$phi68.0', State(pc_initial=68 nstack_initial=2))},\n", - " '$phi110.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi468.1',\n", - " State(pc_initial=468 nstack_initial=2))},\n", - " '$phi112.0': {('$phi110.0',\n", - " State(pc_initial=110 nstack_initial=2))},\n", - " '$phi112.1': {('$phi110.1',\n", - " State(pc_initial=110 nstack_initial=2))},\n", - " '$phi112.2': {('$110for_iter.3',\n", - " State(pc_initial=110 nstack_initial=2))},\n", - " '$phi122.0': {('$phi112.0',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi466.0',\n", - " State(pc_initial=466 nstack_initial=3))},\n", - " '$phi122.1': {('$phi112.1',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi466.1',\n", - " State(pc_initial=466 nstack_initial=3))},\n", - " '$phi122.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi466.2',\n", - " State(pc_initial=466 nstack_initial=3))},\n", - " '$phi124.0': {('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi124.1': {('$phi122.1',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi124.2': {('$phi122.2',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi124.3': {('$122for_iter.4',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi166.0': {('$phi124.0',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi182.0',\n", - " State(pc_initial=182 nstack_initial=4)),\n", - " ('$phi294.0',\n", - " State(pc_initial=294 nstack_initial=4)),\n", - " ('$phi464.0',\n", - " State(pc_initial=464 nstack_initial=4))},\n", - " '$phi166.1': {('$phi124.1',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi182.1',\n", - " State(pc_initial=182 nstack_initial=4)),\n", - " ('$phi294.1',\n", - " State(pc_initial=294 nstack_initial=4)),\n", - " ('$phi464.1',\n", - " State(pc_initial=464 nstack_initial=4))},\n", - " '$phi166.2': {('$phi124.2',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi182.2',\n", - " State(pc_initial=182 nstack_initial=4)),\n", - " ('$phi294.2',\n", - " State(pc_initial=294 nstack_initial=4)),\n", - " ('$phi464.2',\n", - " State(pc_initial=464 nstack_initial=4))},\n", - " '$phi166.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi182.3',\n", - " State(pc_initial=182 nstack_initial=4)),\n", - " ('$phi294.3',\n", - " State(pc_initial=294 nstack_initial=4)),\n", - " ('$phi464.3',\n", - " State(pc_initial=464 nstack_initial=4))},\n", - " '$phi168.0': {('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi168.1': {('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi168.2': {('$phi166.2',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi168.3': {('$phi166.3',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi168.4': {('$166for_iter.5',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi182.0': {('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=5))},\n", - " '$phi182.1': {('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=5))},\n", - " '$phi182.2': {('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=5))},\n", - " '$phi182.3': {('$phi168.3',\n", - " State(pc_initial=168 nstack_initial=5))},\n", - " '$phi184.0': {('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=5))},\n", - " '$phi184.1': {('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=5))},\n", - " '$phi184.2': {('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=5))},\n", - " '$phi184.3': {('$phi168.3',\n", - " State(pc_initial=168 nstack_initial=5))},\n", - " '$phi192.0': {('$phi184.0',\n", - " State(pc_initial=184 nstack_initial=4)),\n", - " ('$phi192.0',\n", - " State(pc_initial=192 nstack_initial=4))},\n", - " '$phi192.1': {('$phi184.1',\n", - " State(pc_initial=184 nstack_initial=4)),\n", - " ('$phi192.1',\n", - " State(pc_initial=192 nstack_initial=4))},\n", - " '$phi192.2': {('$phi184.2',\n", - " State(pc_initial=184 nstack_initial=4)),\n", - " ('$phi192.2',\n", - " State(pc_initial=192 nstack_initial=4))},\n", - " '$phi192.3': {('$phi184.3',\n", - " State(pc_initial=184 nstack_initial=4)),\n", - " ('$phi192.3',\n", - " State(pc_initial=192 nstack_initial=4))},\n", - " '$phi220.0': {('$phi184.0',\n", - " State(pc_initial=184 nstack_initial=4)),\n", - " ('$phi192.0',\n", - " State(pc_initial=192 nstack_initial=4))},\n", - " '$phi220.1': {('$phi184.1',\n", - " State(pc_initial=184 nstack_initial=4)),\n", - " ('$phi192.1',\n", - " State(pc_initial=192 nstack_initial=4))},\n", - " '$phi220.2': {('$phi184.2',\n", - " State(pc_initial=184 nstack_initial=4)),\n", - " ('$phi192.2',\n", - " State(pc_initial=192 nstack_initial=4))},\n", - " '$phi220.3': {('$phi184.3',\n", - " State(pc_initial=184 nstack_initial=4)),\n", - " ('$phi192.3',\n", - " State(pc_initial=192 nstack_initial=4))},\n", - " '$phi228.0': {('$phi220.0',\n", - " State(pc_initial=220 nstack_initial=4))},\n", - " '$phi228.1': {('$phi220.1',\n", - " State(pc_initial=220 nstack_initial=4))},\n", - " '$phi228.2': {('$phi220.2',\n", - " State(pc_initial=220 nstack_initial=4))},\n", - " '$phi228.3': {('$phi220.3',\n", - " State(pc_initial=220 nstack_initial=4))},\n", - " '$phi260.0': {('$phi228.0',\n", - " State(pc_initial=228 nstack_initial=4))},\n", - " '$phi260.1': {('$phi228.1',\n", - " State(pc_initial=228 nstack_initial=4))},\n", - " '$phi260.2': {('$phi228.2',\n", - " State(pc_initial=228 nstack_initial=4))},\n", - " '$phi260.3': {('$phi228.3',\n", - " State(pc_initial=228 nstack_initial=4))},\n", - " '$phi266.0': {('$phi228.0',\n", - " State(pc_initial=228 nstack_initial=4))},\n", - " '$phi266.1': {('$phi228.1',\n", - " State(pc_initial=228 nstack_initial=4))},\n", - " '$phi266.2': {('$phi228.2',\n", - " State(pc_initial=228 nstack_initial=4))},\n", - " '$phi266.3': {('$phi228.3',\n", - " State(pc_initial=228 nstack_initial=4))},\n", - " '$phi280.0': {('$phi266.0',\n", - " State(pc_initial=266 nstack_initial=4))},\n", - " '$phi280.1': {('$phi266.1',\n", - " State(pc_initial=266 nstack_initial=4))},\n", - " '$phi280.2': {('$phi266.2',\n", - " State(pc_initial=266 nstack_initial=4))},\n", - " '$phi280.3': {('$phi266.3',\n", - " State(pc_initial=266 nstack_initial=4))},\n", - " '$phi286.0': {('$phi266.0',\n", - " State(pc_initial=266 nstack_initial=4))},\n", - " '$phi286.1': {('$phi266.1',\n", - " State(pc_initial=266 nstack_initial=4))},\n", - " '$phi286.2': {('$phi266.2',\n", - " State(pc_initial=266 nstack_initial=4))},\n", - " '$phi286.3': {('$phi266.3',\n", - " State(pc_initial=266 nstack_initial=4))},\n", - " '$phi290.0': {('$phi220.0',\n", - " State(pc_initial=220 nstack_initial=4)),\n", - " ('$phi260.0',\n", - " State(pc_initial=260 nstack_initial=4)),\n", - " ('$phi280.0',\n", - " State(pc_initial=280 nstack_initial=4)),\n", - " ('$phi286.0',\n", - " State(pc_initial=286 nstack_initial=4))},\n", - " '$phi290.1': {('$phi220.1',\n", - " State(pc_initial=220 nstack_initial=4)),\n", - " ('$phi260.1',\n", - " State(pc_initial=260 nstack_initial=4)),\n", - " ('$phi280.1',\n", - " State(pc_initial=280 nstack_initial=4)),\n", - " ('$phi286.1',\n", - " State(pc_initial=286 nstack_initial=4))},\n", - " '$phi290.2': {('$phi220.2',\n", - " State(pc_initial=220 nstack_initial=4)),\n", - " ('$phi260.2',\n", - " State(pc_initial=260 nstack_initial=4)),\n", - " ('$phi280.2',\n", - " State(pc_initial=280 nstack_initial=4)),\n", - " ('$phi286.2',\n", - " State(pc_initial=286 nstack_initial=4))},\n", - " '$phi290.3': {('$phi220.3',\n", - " State(pc_initial=220 nstack_initial=4)),\n", - " ('$phi260.3',\n", - " State(pc_initial=260 nstack_initial=4)),\n", - " ('$phi280.3',\n", - " State(pc_initial=280 nstack_initial=4)),\n", - " ('$phi286.3',\n", - " State(pc_initial=286 nstack_initial=4))},\n", - " '$phi294.0': {('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4))},\n", - " '$phi294.1': {('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4))},\n", - " '$phi294.2': {('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4))},\n", - " '$phi294.3': {('$phi290.3',\n", - " State(pc_initial=290 nstack_initial=4))},\n", - " '$phi296.0': {('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4))},\n", - " '$phi296.1': {('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4))},\n", - " '$phi296.2': {('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4))},\n", - " '$phi296.3': {('$phi290.3',\n", - " State(pc_initial=290 nstack_initial=4))},\n", - " '$phi304.0': {('$phi296.0',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi462.0',\n", - " State(pc_initial=462 nstack_initial=5))},\n", - " '$phi304.1': {('$phi296.1',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi462.1',\n", - " State(pc_initial=462 nstack_initial=5))},\n", - " '$phi304.2': {('$phi296.2',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi462.2',\n", - " State(pc_initial=462 nstack_initial=5))},\n", - " '$phi304.3': {('$phi296.3',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi462.3',\n", - " State(pc_initial=462 nstack_initial=5))},\n", - " '$phi304.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi462.4',\n", - " State(pc_initial=462 nstack_initial=5))},\n", - " '$phi306.0': {('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi306.1': {('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi306.2': {('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi306.3': {('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi306.4': {('$phi304.4',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi306.5': {('$304for_iter.6',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi354.0': {('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6))},\n", - " '$phi354.1': {('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6))},\n", - " '$phi354.2': {('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6))},\n", - " '$phi354.3': {('$phi306.3',\n", - " State(pc_initial=306 nstack_initial=6))},\n", - " '$phi354.4': {('$phi306.4',\n", - " State(pc_initial=306 nstack_initial=6))},\n", - " '$phi362.0': {('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi362.1': {('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi362.2': {('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi362.3': {('$phi354.3',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.3',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi362.4': {('$phi354.4',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.4',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi378.0': {('$phi362.0',\n", - " State(pc_initial=362 nstack_initial=5))},\n", - " '$phi378.1': {('$phi362.1',\n", - " State(pc_initial=362 nstack_initial=5))},\n", - " '$phi378.2': {('$phi362.2',\n", - " State(pc_initial=362 nstack_initial=5))},\n", - " '$phi378.3': {('$phi362.3',\n", - " State(pc_initial=362 nstack_initial=5))},\n", - " '$phi378.4': {('$phi362.4',\n", - " State(pc_initial=362 nstack_initial=5))},\n", - " '$phi390.0': {('$phi378.0',\n", - " State(pc_initial=378 nstack_initial=5)),\n", - " ('$phi428.0',\n", - " State(pc_initial=428 nstack_initial=6))},\n", - " '$phi390.1': {('$phi378.1',\n", - " State(pc_initial=378 nstack_initial=5)),\n", - " ('$phi428.1',\n", - " State(pc_initial=428 nstack_initial=6))},\n", - " '$phi390.2': {('$phi378.2',\n", - " State(pc_initial=378 nstack_initial=5)),\n", - " ('$phi428.2',\n", - " State(pc_initial=428 nstack_initial=6))},\n", - " '$phi390.3': {('$phi378.3',\n", - " State(pc_initial=378 nstack_initial=5)),\n", - " ('$phi428.3',\n", - " State(pc_initial=428 nstack_initial=6))},\n", - " '$phi390.4': {('$phi378.4',\n", - " State(pc_initial=378 nstack_initial=5)),\n", - " ('$phi428.4',\n", - " State(pc_initial=428 nstack_initial=6))},\n", - " '$phi390.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5)),\n", - " ('$phi428.5',\n", - " State(pc_initial=428 nstack_initial=6))},\n", - " '$phi392.0': {('$phi390.0',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi392.1': {('$phi390.1',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi392.2': {('$phi390.2',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi392.3': {('$phi390.3',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi392.4': {('$phi390.4',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi392.5': {('$phi390.5',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi392.6': {('$390for_iter.7',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi406.0': {('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi406.1': {('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi406.2': {('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi406.3': {('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi406.4': {('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi406.5': {('$phi392.5',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi414.0': {('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi414.1': {('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi414.2': {('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi414.3': {('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi414.4': {('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi414.5': {('$phi406.5',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi428.0': {('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi428.1': {('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi428.2': {('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi428.3': {('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi428.4': {('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi428.5': {('$phi392.5',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.5',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi430.0': {('$phi362.0',\n", - " State(pc_initial=362 nstack_initial=5)),\n", - " ('$phi390.0',\n", - " State(pc_initial=390 nstack_initial=6)),\n", - " ('$phi414.0',\n", - " State(pc_initial=414 nstack_initial=6))},\n", - " '$phi430.1': {('$phi362.1',\n", - " State(pc_initial=362 nstack_initial=5)),\n", - " ('$phi390.1',\n", - " State(pc_initial=390 nstack_initial=6)),\n", - " ('$phi414.1',\n", - " State(pc_initial=414 nstack_initial=6))},\n", - " '$phi430.2': {('$phi362.2',\n", - " State(pc_initial=362 nstack_initial=5)),\n", - " ('$phi390.2',\n", - " State(pc_initial=390 nstack_initial=6)),\n", - " ('$phi414.2',\n", - " State(pc_initial=414 nstack_initial=6))},\n", - " '$phi430.3': {('$phi362.3',\n", - " State(pc_initial=362 nstack_initial=5)),\n", - " ('$phi390.3',\n", - " State(pc_initial=390 nstack_initial=6)),\n", - " ('$phi414.3',\n", - " State(pc_initial=414 nstack_initial=6))},\n", - " '$phi430.4': {('$phi362.4',\n", - " State(pc_initial=362 nstack_initial=5)),\n", - " ('$phi390.4',\n", - " State(pc_initial=390 nstack_initial=6)),\n", - " ('$phi414.4',\n", - " State(pc_initial=414 nstack_initial=6))},\n", - " '$phi454.0': {('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi454.1': {('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi454.2': {('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi454.3': {('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi454.4': {('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi462.0': {('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi462.1': {('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi462.2': {('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi462.3': {('$phi306.3',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.3',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.3',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi462.4': {('$phi306.4',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.4',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.4',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi464.0': {('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi464.1': {('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi464.2': {('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi464.3': {('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi466.0': {('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi466.1': {('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi466.2': {('$phi166.2',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi468.0': {('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi468.1': {('$phi122.1',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi470.0': {('$phi110.0',\n", - " State(pc_initial=110 nstack_initial=2))},\n", - " '$phi66.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi470.0',\n", - " State(pc_initial=470 nstack_initial=1))},\n", - " '$phi68.0': {('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi68.1': {('$66for_iter.2',\n", - " State(pc_initial=66 nstack_initial=1))}})\n", - "2024-10-16 10:11:07,628 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi110.0': {('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi110.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi122.1',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi112.0': {('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi112.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi122.1',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi112.2': {('$110for_iter.3',\n", - " State(pc_initial=110 nstack_initial=2))},\n", - " '$phi122.0': {('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=4)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi122.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi122.1',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi122.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi166.2',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi124.0': {('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=4)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi124.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi124.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi166.2',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi124.3': {('$122for_iter.4',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi166.0': {('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=4)),\n", - " ('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi166.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=4)),\n", - " ('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi166.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi166.2',\n", - " State(pc_initial=166 nstack_initial=4)),\n", - " ('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi166.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi168.3',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.3',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi168.0': {('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi168.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi168.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi168.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi168.3',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.3',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi168.4': {('$166for_iter.5',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi182.0': {('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi182.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi182.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi182.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi290.3',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi184.0': {('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi184.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi184.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi184.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi290.3',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi192.0': {('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi192.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi192.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi192.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi290.3',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi220.0': {('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi220.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi220.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi220.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi290.3',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi228.0': {('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi228.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi228.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi228.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi290.3',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi260.0': {('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 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" ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi304.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi304.3',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi306.3',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.3',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.3',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi304.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi306.4',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.4',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.4',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi306.0': {('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - 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" ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi354.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi354.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi354.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi354.3',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.3',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi354.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi354.4',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.4',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi362.0': {('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi362.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi362.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi362.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi362.4': 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State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi390.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi390.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi390.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi390.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi390.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5)),\n", - " ('$phi392.5',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.5',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi392.0': {('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi392.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi392.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi392.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi392.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi392.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5)),\n", - " ('$phi392.5',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.5',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi392.6': {('$390for_iter.7',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi406.0': {('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi406.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi406.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi406.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi406.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi406.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5)),\n", - " ('$phi406.5',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi414.0': {('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi414.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi414.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi414.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi414.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi414.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi428.0': {('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi428.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi428.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi428.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi428.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi428.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi430.0': {('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi430.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi430.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi430.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi430.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.4',\n", - " State(pc_initial=430 nstack_initial=5))},\n", - " '$phi454.0': {('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi454.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi454.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi454.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi454.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi462.0': {('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi462.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi462.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi462.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi462.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi464.0': {('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi464.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi464.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi464.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi306.3',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.3',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.3',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi466.0': {('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi466.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi466.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi468.0': {('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=4)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi468.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi470.0': {('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi66.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0', State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi66.0', State(pc_initial=66 nstack_initial=1))},\n", - " '$phi68.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi68.1': {('$66for_iter.2',\n", - " State(pc_initial=66 nstack_initial=1))}})\n", - "2024-10-16 10:11:07,649 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi110.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi110.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi112.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi112.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi112.2': {('$110for_iter.3',\n", - " State(pc_initial=110 nstack_initial=2))},\n", - " '$phi122.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi122.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi122.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi124.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi124.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.1',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.1',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi124.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.2',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.2',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi124.3': {('$122for_iter.4',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi166.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi166.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi166.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi166.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi306.3',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.3',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.3',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi168.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi168.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi168.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi168.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi306.3',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.3',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.3',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi168.4': {('$166for_iter.5',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi182.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi182.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi182.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.2',\n", - " 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- " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi294.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi294.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi294.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi306.3',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.3',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.3',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi296.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi296.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi296.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi296.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi306.3',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.3',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.3',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.3',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi304.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi304.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi304.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi304.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi304.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi306.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi306.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi306.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi306.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi306.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi306.5': {('$304for_iter.6',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi354.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi354.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi354.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi354.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi354.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi362.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi362.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi362.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi362.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi362.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi378.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi378.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi378.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi378.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi378.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.4',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi390.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi390.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi390.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi390.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi390.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi390.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi392.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi392.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi392.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi392.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi392.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi392.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi392.6': {('$390for_iter.7',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi406.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi406.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi406.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi406.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi406.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi406.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi414.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi414.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi414.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi414.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi414.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4)),\n", - " ('$phi392.4',\n", - " State(pc_initial=392 nstack_initial=7))},\n", - " '$phi414.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi428.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi428.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi428.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi428.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi428.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi428.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi430.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi430.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi430.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi430.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi430.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi454.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi454.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi454.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi454.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi454.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi462.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi462.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi462.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi462.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi462.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi464.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi464.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi464.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi464.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi466.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi122.0',\n", - " State(pc_initial=122 nstack_initial=3)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi466.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi466.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi468.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi468.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi470.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.0',\n", - " State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi66.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi168.0', State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.0', State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi68.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi168.0', State(pc_initial=168 nstack_initial=5)),\n", - " ('$phi290.0', State(pc_initial=290 nstack_initial=4)),\n", - " ('$phi304.0',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi68.1': {('$66for_iter.2',\n", - " State(pc_initial=66 nstack_initial=1))}})\n", - "2024-10-16 10:11:07,669 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi110.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi110.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi112.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi112.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi112.2': {('$110for_iter.3',\n", - " State(pc_initial=110 nstack_initial=2))},\n", - " '$phi122.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi122.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi122.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi124.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.0',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi124.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi306.1',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.1',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.1',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.1',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi124.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi306.2',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.2',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6)),\n", - " ('$phi430.2',\n", - " State(pc_initial=430 nstack_initial=5)),\n", - " ('$phi454.2',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi124.3': {('$122for_iter.4',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi166.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi166.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi166.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi166.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi168.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi168.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi168.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi168.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi168.4': {('$166for_iter.5',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi182.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi182.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi182.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi182.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi184.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi184.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi184.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi184.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi192.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi192.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi192.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi192.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi220.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi220.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi220.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi220.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi228.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi228.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi228.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi228.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi260.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi260.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi260.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi260.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi266.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi266.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi266.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi266.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi280.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi280.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi280.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi280.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi286.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi286.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi286.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi286.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi290.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi290.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi290.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi290.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi294.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi294.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi294.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi294.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi296.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi296.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2)),\n", - " ('$phi392.1',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.1',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi296.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3)),\n", - " ('$phi392.2',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.2',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi296.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi392.3',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.3',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi304.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi304.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi304.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi304.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi304.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi306.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi306.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi306.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi306.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi306.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi306.5': {('$304for_iter.6',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi354.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi354.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi354.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi354.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi354.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi362.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6))},\n", - " '$phi362.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi362.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi362.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi362.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi378.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi378.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi378.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi378.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi378.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi390.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi390.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi390.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi390.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi390.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi390.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi392.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi392.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi392.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi392.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi392.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi392.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi392.6': {('$390for_iter.7',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi406.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi406.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi406.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi406.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi406.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi406.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi414.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi414.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi414.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi414.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi414.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi414.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi428.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi428.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi428.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi428.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi428.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi428.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi430.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi430.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi430.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi430.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi430.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi454.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi306.0',\n", - " State(pc_initial=306 nstack_initial=6)),\n", - " ('$phi354.0',\n", - " State(pc_initial=354 nstack_initial=5)),\n", - " ('$phi454.0',\n", - " State(pc_initial=454 nstack_initial=5))},\n", - " '$phi454.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi454.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi454.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi454.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi462.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi462.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi462.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi462.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi462.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi464.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi464.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi464.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi464.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi466.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi466.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi466.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi468.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi468.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi470.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0',\n", - " State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi66.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0', State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi68.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi392.0', State(pc_initial=392 nstack_initial=7)),\n", - " ('$phi406.0',\n", - " State(pc_initial=406 nstack_initial=6))},\n", - " '$phi68.1': {('$66for_iter.2',\n", - " State(pc_initial=66 nstack_initial=1))}})\n", - "2024-10-16 10:11:07,683 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi110.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi110.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi112.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi112.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi112.2': {('$110for_iter.3',\n", - " State(pc_initial=110 nstack_initial=2))},\n", - " '$phi122.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi122.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi122.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi124.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi124.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi124.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi124.3': {('$122for_iter.4',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi166.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi166.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi166.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi166.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi168.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi168.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi168.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi168.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi168.4': {('$166for_iter.5',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi182.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi182.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi182.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi182.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi184.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi184.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi184.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi184.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi192.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi192.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi192.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi192.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi220.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi220.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi220.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi220.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi228.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi228.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi228.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi228.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi260.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi260.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi260.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi260.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi266.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi266.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi266.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi266.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi280.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi280.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi280.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi280.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi286.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi286.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi286.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi286.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi290.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi290.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi290.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi290.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi294.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi294.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi294.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi294.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi296.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi296.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi296.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi296.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi304.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi304.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi304.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi304.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi304.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi306.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi306.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi306.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi306.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi306.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi306.5': {('$304for_iter.6',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi354.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi354.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi354.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi354.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi354.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi362.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi362.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi362.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi362.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi362.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi378.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi378.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi378.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi378.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi378.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi390.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi390.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi390.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi390.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi390.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi390.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi392.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi392.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi392.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi392.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi392.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi392.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi392.6': {('$390for_iter.7',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi406.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi406.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi406.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi406.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi406.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi406.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi414.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi414.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi414.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi414.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi414.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi414.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi428.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi428.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi428.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi428.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi428.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi428.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi430.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi430.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi430.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi430.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi430.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi454.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi454.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi454.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi454.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi454.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi462.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi462.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi462.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi462.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi462.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi464.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi464.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi464.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi464.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi466.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi466.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi466.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi468.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi468.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi470.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi66.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi68.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi68.1': {('$66for_iter.2',\n", - " State(pc_initial=66 nstack_initial=1))}})\n", - "2024-10-16 10:11:07,691 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi110.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi110.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi112.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi112.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi112.2': {('$110for_iter.3',\n", - " State(pc_initial=110 nstack_initial=2))},\n", - " '$phi122.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi122.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi122.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi124.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi124.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi124.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi124.3': {('$122for_iter.4',\n", - " State(pc_initial=122 nstack_initial=3))},\n", - " '$phi166.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi166.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi166.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi166.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi168.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi168.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi168.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi168.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi168.4': {('$166for_iter.5',\n", - " State(pc_initial=166 nstack_initial=4))},\n", - " '$phi182.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi182.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi182.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi182.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi184.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi184.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi184.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi184.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi192.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi192.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi192.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi192.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi220.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi220.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi220.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi220.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi228.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi228.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi228.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi228.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi260.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi260.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi260.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi260.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi266.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi266.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi266.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi266.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi280.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi280.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi280.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi280.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi286.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi286.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi286.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi286.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi290.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi290.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi290.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi290.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi294.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi294.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi294.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi294.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi296.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi296.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi296.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi296.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi304.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi304.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi304.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi304.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi304.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi306.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi306.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi306.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi306.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi306.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi306.5': {('$304for_iter.6',\n", - " State(pc_initial=304 nstack_initial=5))},\n", - " '$phi354.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi354.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi354.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi354.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi354.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi362.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi362.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi362.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi362.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi362.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi378.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi378.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi378.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi378.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi378.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi390.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi390.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi390.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi390.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi390.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi390.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi392.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi392.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi392.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi392.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi392.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi392.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi392.6': {('$390for_iter.7',\n", - " State(pc_initial=390 nstack_initial=6))},\n", - " '$phi406.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi406.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi406.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi406.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi406.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi406.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi414.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi414.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi414.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi414.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi414.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi414.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi428.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi428.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi428.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi428.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi428.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi428.5': {('$388get_iter.9',\n", - " State(pc_initial=378 nstack_initial=5))},\n", - " '$phi430.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi430.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi430.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi430.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi430.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi454.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi454.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi454.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi454.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi454.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi462.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi462.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi462.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi462.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi462.4': {('$302get_iter.6',\n", - " State(pc_initial=296 nstack_initial=4))},\n", - " '$phi464.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi464.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi464.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi464.3': {('$164get_iter.24',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi466.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi466.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi466.2': {('$120get_iter.7',\n", - " State(pc_initial=112 nstack_initial=3))},\n", - " '$phi468.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi468.1': {('$108get_iter.22',\n", - " State(pc_initial=68 nstack_initial=2))},\n", - " '$phi470.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi66.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi68.0': {('$64get_iter.26',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi68.1': {('$66for_iter.2',\n", - " State(pc_initial=66 nstack_initial=1))}})\n", - "2024-10-16 10:11:07,698 - numba.core.byteflow - DEBUG - keep phismap: {'$phi110.1': {('$108get_iter.22', State(pc_initial=68 nstack_initial=2))},\n", - " '$phi112.2': {('$110for_iter.3', State(pc_initial=110 nstack_initial=2))},\n", - " '$phi122.2': {('$120get_iter.7', State(pc_initial=112 nstack_initial=3))},\n", - " '$phi124.3': {('$122for_iter.4', State(pc_initial=122 nstack_initial=3))},\n", - " '$phi166.3': {('$164get_iter.24', State(pc_initial=124 nstack_initial=4))},\n", - " '$phi168.4': {('$166for_iter.5', State(pc_initial=166 nstack_initial=4))},\n", - " '$phi304.4': {('$302get_iter.6', State(pc_initial=296 nstack_initial=4))},\n", - " '$phi306.5': {('$304for_iter.6', State(pc_initial=304 nstack_initial=5))},\n", - " '$phi390.5': {('$388get_iter.9', State(pc_initial=378 nstack_initial=5))},\n", - " '$phi392.6': {('$390for_iter.7', State(pc_initial=390 nstack_initial=6))},\n", - " '$phi66.0': {('$64get_iter.26', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi68.1': {('$66for_iter.2', State(pc_initial=66 nstack_initial=1))}}\n", - "2024-10-16 10:11:07,700 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi66.0': '$64get_iter.26'},\n", - " State(pc_initial=66 nstack_initial=1): {'$phi68.1': '$66for_iter.2'},\n", - " State(pc_initial=68 nstack_initial=2): {'$phi110.1': '$108get_iter.22'},\n", - " State(pc_initial=110 nstack_initial=2): {'$phi112.2': '$110for_iter.3'},\n", - " State(pc_initial=112 nstack_initial=3): {'$phi122.2': '$120get_iter.7'},\n", - " State(pc_initial=122 nstack_initial=3): {'$phi124.3': '$122for_iter.4'},\n", - " State(pc_initial=124 nstack_initial=4): {'$phi166.3': '$164get_iter.24'},\n", - " State(pc_initial=166 nstack_initial=4): {'$phi168.4': '$166for_iter.5'},\n", - " State(pc_initial=296 nstack_initial=4): {'$phi304.4': '$302get_iter.6'},\n", - " State(pc_initial=304 nstack_initial=5): {'$phi306.5': '$304for_iter.6'},\n", - " State(pc_initial=378 nstack_initial=5): {'$phi390.5': '$388get_iter.9'},\n", - " State(pc_initial=390 nstack_initial=6): {'$phi392.6': '$390for_iter.7'}})\n", - "2024-10-16 10:11:07,701 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:07,702 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'items': [], 'res': '$2build_list.0'}), (4, {'value': '$2build_list.0'}), (6, {'res': '$const6.1'}), (8, {'value': '$const6.1'}), (10, {'res': '$const10.2'}), (12, {'value': '$const10.2'}), (14, {'res': '$const14.3'}), (16, {'value': '$const14.3'}), (18, {'res': '$const18.4'}), (20, {'value': '$const18.4'}), (22, {'res': '$push_indptr22.5'}), (24, {'res': '$const24.6'}), (26, {'res': '$const26.7'}), (28, {'start': '$const24.6', 'stop': '$const26.7', 'step': None, 'res': '$28build_slice.9', 'slicevar': '$28build_slice.8'}), (30, {'index': '$28build_slice.9', 'target': '$push_indptr22.5', 'res': '$30binary_subscr.10'}), (32, {'item': '$30binary_subscr.10', 'res': '$32load_method.11'}), (34, {'res': '$frame_max_index34.12'}), (36, {'res': '$scan_max_index36.13'}), (38, {'func': '$32load_method.11', 'args': ['$frame_max_index34.12', '$scan_max_index36.13'], 'res': '$38call_method.14'}), (40, {'value': '$38call_method.14'}), (42, {'res': '$push_indptr42.15'}), (44, {'res': '$const44.16'}), (46, {'res': '$const46.17'}), (48, {'start': '$const44.16', 'stop': '$const46.17', 'step': None, 'res': '$48build_slice.19', 'slicevar': '$48build_slice.18'}), (50, {'index': '$48build_slice.19', 'target': '$push_indptr42.15', 'res': '$50binary_subscr.20'}), (52, {'item': '$50binary_subscr.20', 'res': '$52load_method.21'}), (54, {'res': '$frame_max_index54.22'}), (56, {'res': '$scan_max_index56.23'}), (58, {'func': '$52load_method.21', 'args': ['$frame_max_index54.22', '$scan_max_index56.23'], 'res': '$58call_method.24'}), (60, {'value': '$58call_method.24'}), (62, {'res': '$frame_slices62.25'}), (64, {'value': '$frame_slices62.25', 'res': '$64get_iter.26'})), outgoing_phis={'$phi66.0': '$64get_iter.26'}, blockstack=(), active_try_block=None, outgoing_edgepushed={66: ('$64get_iter.26',)})\n", - "2024-10-16 10:11:07,703 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=66 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((66, {'iterator': '$phi66.0', 'pair': '$66for_iter.1', 'indval': '$66for_iter.2', 'pred': '$66for_iter.3'}),), outgoing_phis={'$phi68.1': '$66for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={472: (), 68: ('$phi66.0', '$66for_iter.2')})\n", - "2024-10-16 10:11:07,704 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=68 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((68, {'iterable': '$phi68.1', 'stores': ['$68unpack_sequence.2', '$68unpack_sequence.3', '$68unpack_sequence.4'], 'tupleobj': '$68unpack_sequence.5'}), (70, {'value': '$68unpack_sequence.2'}), (72, {'value': '$68unpack_sequence.3'}), (74, {'value': '$68unpack_sequence.4'}), (76, {'res': '$76load_global.6'}), (78, {'res': '$starts78.7'}), (80, {'res': '$80load_global.8'}), (82, {'res': '$frame_start82.9'}), (84, {'res': '$frame_stop84.10'}), (86, {'res': '$frame_step86.11'}), (88, {'func': '$80load_global.8', 'args': ['$frame_start82.9', '$frame_stop84.10', '$frame_step86.11'], 'res': '$88call_function.12'}), (90, {'index': '$88call_function.12', 'target': '$starts78.7', 'res': '$90binary_subscr.13'}), (92, {'res': '$ends92.14'}), (94, {'res': '$94load_global.15'}), (96, {'res': '$frame_start96.16'}), (98, {'res': '$frame_stop98.17'}), (100, {'res': '$frame_step100.18'}), (102, {'func': '$94load_global.15', 'args': ['$frame_start96.16', '$frame_stop98.17', '$frame_step100.18'], 'res': '$102call_function.19'}), (104, {'index': '$102call_function.19', 'target': '$ends92.14', 'res': '$104binary_subscr.20'}), (106, {'func': '$76load_global.6', 'args': ['$90binary_subscr.13', '$104binary_subscr.20'], 'res': '$106call_function.21'}), (108, {'value': '$106call_function.21', 'res': '$108get_iter.22'})), outgoing_phis={'$phi110.1': '$108get_iter.22'}, blockstack=(), active_try_block=None, outgoing_edgepushed={110: ('$phi68.0', '$108get_iter.22')})\n", - "2024-10-16 10:11:07,705 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=110 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((110, {'iterator': '$phi110.1', 'pair': '$110for_iter.2', 'indval': '$110for_iter.3', 'pred': '$110for_iter.4'}),), outgoing_phis={'$phi112.2': '$110for_iter.3'}, blockstack=(), active_try_block=None, outgoing_edgepushed={470: ('$phi110.0',), 112: ('$phi110.0', '$phi110.1', '$110for_iter.3')})\n", - "2024-10-16 10:11:07,706 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=112 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((112, {'iterable': '$phi112.2', 'stores': ['$112unpack_sequence.3', '$112unpack_sequence.4'], 'tupleobj': '$112unpack_sequence.5'}), (114, {'value': '$112unpack_sequence.3'}), (116, {'value': '$112unpack_sequence.4'}), (118, {'res': '$scan_slices118.6'}), (120, {'value': '$scan_slices118.6', 'res': '$120get_iter.7'})), outgoing_phis={'$phi122.2': '$120get_iter.7'}, blockstack=(), active_try_block=None, outgoing_edgepushed={122: ('$phi112.0', '$phi112.1', '$120get_iter.7')})\n", - "2024-10-16 10:11:07,707 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=122 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((122, {'iterator': '$phi122.2', 'pair': '$122for_iter.3', 'indval': '$122for_iter.4', 'pred': '$122for_iter.5'}),), outgoing_phis={'$phi124.3': '$122for_iter.4'}, blockstack=(), active_try_block=None, outgoing_edgepushed={468: ('$phi122.0', '$phi122.1'), 124: ('$phi122.0', '$phi122.1', '$phi122.2', '$122for_iter.4')})\n", - "2024-10-16 10:11:07,708 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=124 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((124, {'iterable': '$phi124.3', 'stores': ['$124unpack_sequence.4', '$124unpack_sequence.5', '$124unpack_sequence.6'], 'tupleobj': '$124unpack_sequence.7'}), (126, {'value': '$124unpack_sequence.4'}), (128, {'value': '$124unpack_sequence.5'}), (130, {'value': '$124unpack_sequence.6'}), (132, {'res': '$132load_global.8'}), (134, {'res': '$frame_start_slice134.9'}), (136, {'res': '$136load_global.10'}), (138, {'res': '$scan_start138.11'}), (140, {'res': '$scan_stop140.12'}), (142, {'res': '$scan_step142.13'}), (144, {'func': '$136load_global.10', 'args': ['$scan_start138.11', '$scan_stop140.12', '$scan_step142.13'], 'res': '$144call_function.14'}), (146, {'index': '$144call_function.14', 'target': '$frame_start_slice134.9', 'res': '$146binary_subscr.15'}), (148, {'res': '$frame_end_slice148.16'}), (150, {'res': '$150load_global.17'}), (152, {'res': '$scan_start152.18'}), (154, {'res': '$scan_stop154.19'}), (156, {'res': '$scan_step156.20'}), (158, {'func': '$150load_global.17', 'args': ['$scan_start152.18', '$scan_stop154.19', '$scan_step156.20'], 'res': '$158call_function.21'}), (160, {'index': '$158call_function.21', 'target': '$frame_end_slice148.16', 'res': '$160binary_subscr.22'}), (162, {'func': '$132load_global.8', 'args': ['$146binary_subscr.15', '$160binary_subscr.22'], 'res': '$162call_function.23'}), (164, {'value': '$162call_function.23', 'res': '$164get_iter.24'})), outgoing_phis={'$phi166.3': '$164get_iter.24'}, blockstack=(), active_try_block=None, outgoing_edgepushed={166: ('$phi124.0', '$phi124.1', '$phi124.2', '$164get_iter.24')})\n", - "2024-10-16 10:11:07,709 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=166 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((166, {'iterator': '$phi166.3', 'pair': '$166for_iter.4', 'indval': '$166for_iter.5', 'pred': '$166for_iter.6'}),), outgoing_phis={'$phi168.4': '$166for_iter.5'}, blockstack=(), active_try_block=None, outgoing_edgepushed={466: ('$phi166.0', '$phi166.1', '$phi166.2'), 168: ('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$166for_iter.5')})\n", - "2024-10-16 10:11:07,710 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=168 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((168, {'iterable': '$phi168.4', 'stores': ['$168unpack_sequence.5', '$168unpack_sequence.6'], 'tupleobj': '$168unpack_sequence.7'}), (170, {'value': '$168unpack_sequence.5'}), (172, {'value': '$168unpack_sequence.6'}), (174, {'res': '$sparse_start174.8'}), (176, {'res': '$sparse_end176.9'}), (178, {'lhs': '$sparse_start174.8', 'rhs': '$sparse_end176.9', 'res': '$178compare_op.10'}), (180, {'pred': '$178compare_op.10'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={182: ('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3'), 184: ('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3')})\n", - "2024-10-16 10:11:07,710 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=182 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((182, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={166: ('$phi182.0', '$phi182.1', '$phi182.2', '$phi182.3')})\n", - "2024-10-16 10:11:07,711 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=184 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((184, {'res': '$quad_end184.4'}), (186, {'res': '$sparse_end186.5'}), (188, {'lhs': '$quad_end184.4', 'rhs': '$sparse_end186.5', 'res': '$188compare_op.6'}), (190, {'pred': '$188compare_op.6'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={192: ('$phi184.0', '$phi184.1', '$phi184.2', '$phi184.3'), 220: ('$phi184.0', '$phi184.1', '$phi184.2', '$phi184.3')})\n", - "2024-10-16 10:11:07,712 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=192 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((192, {'res': '$new_quad_index192.4'}), (194, {'res': '$const194.5'}), (196, {'lhs': '$new_quad_index192.4', 'rhs': '$const194.5', 'res': '$196inplace_add.6'}), (198, {'value': '$196inplace_add.6'}), (200, {'res': '$quad_indptr200.7'}), (202, {'res': '$new_quad_index202.8'}), (204, {'res': '$const204.9'}), (206, {'lhs': '$new_quad_index202.8', 'rhs': '$const204.9', 'res': '$206binary_add.10'}), (208, {'index': '$206binary_add.10', 'target': '$quad_indptr200.7', 'res': '$208binary_subscr.11'}), (210, {'value': '$208binary_subscr.11'}), (212, {'res': '$quad_end212.12'}), (214, {'res': '$sparse_end214.13'}), (216, {'lhs': '$quad_end212.12', 'rhs': '$sparse_end214.13', 'res': '$216compare_op.14'}), (218, {'pred': '$216compare_op.14'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={220: ('$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3'), 192: ('$phi192.0', '$phi192.1', '$phi192.2', '$phi192.3')})\n", - "2024-10-16 10:11:07,713 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=220 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((220, {'res': '$quad_index220.4'}), (222, {'res': '$new_quad_index222.5'}), (224, {'lhs': '$quad_index220.4', 'rhs': '$new_quad_index222.5', 'res': '$224compare_op.6'}), (226, {'pred': '$224compare_op.6'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={228: ('$phi220.0', '$phi220.1', '$phi220.2', '$phi220.3'), 290: ('$phi220.0', '$phi220.1', '$phi220.2', '$phi220.3')})\n", - "2024-10-16 10:11:07,714 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=228 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((228, {'res': '$new_quad_index228.4'}), (230, {'value': '$new_quad_index228.4'}), (232, {'res': '$232load_global.5'}), (234, {'res': '$quad_mz_values234.6'}), (236, {'res': '$quad_index236.7'}), (238, {'res': '$const238.8'}), (240, {'items': ['$quad_index236.7', '$const238.8'], 'res': '$240build_tuple.9'}), (242, {'index': '$240build_tuple.9', 'target': '$quad_mz_values234.6', 'res': '$242binary_subscr.10'}), (244, {'res': '$quad_mz_values244.11'}), (246, {'res': '$quad_index246.12'}), (248, {'res': '$const248.13'}), (250, {'items': ['$quad_index246.12', '$const248.13'], 'res': '$250build_tuple.14'}), (252, {'index': '$250build_tuple.14', 'target': '$quad_mz_values244.11', 'res': '$252binary_subscr.15'}), (254, {'res': '$quad_slices254.16'}), (256, {'func': '$232load_global.5', 'args': ['$242binary_subscr.10', '$252binary_subscr.15', '$quad_slices254.16'], 'res': '$256call_function.17'}), (258, {'pred': '$256call_function.17'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={260: ('$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3'), 266: ('$phi228.0', '$phi228.1', '$phi228.2', '$phi228.3')})\n", - "2024-10-16 10:11:07,715 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=260 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((260, {'res': '$const260.4'}), (262, {'value': '$const260.4'}), (264, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={290: ('$phi260.0', '$phi260.1', '$phi260.2', '$phi260.3')})\n", - "2024-10-16 10:11:07,716 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=266 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((266, {'res': '$266load_global.4'}), (268, {'res': '$precursor_indices268.5'}), (270, {'res': '$quad_index270.6'}), (272, {'index': '$quad_index270.6', 'target': '$precursor_indices268.5', 'res': '$272binary_subscr.7'}), (274, {'res': '$precursor_slices274.8'}), (276, {'func': '$266load_global.4', 'args': ['$272binary_subscr.7', '$precursor_slices274.8'], 'res': '$276call_function.9'}), (278, {'pred': '$276call_function.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={280: ('$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3'), 286: ('$phi266.0', '$phi266.1', '$phi266.2', '$phi266.3')})\n", - "2024-10-16 10:11:07,716 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=280 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((280, {'res': '$const280.4'}), (282, {'value': '$const280.4'}), (284, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={290: ('$phi280.0', '$phi280.1', '$phi280.2', '$phi280.3')})\n", - "2024-10-16 10:11:07,717 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=286 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((286, {'res': '$const286.4'}), (288, {'value': '$const286.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={290: ('$phi286.0', '$phi286.1', '$phi286.2', '$phi286.3')})\n", - "2024-10-16 10:11:07,718 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=290 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((290, {'res': '$is_valid_quad_index290.4'}), (292, {'pred': '$is_valid_quad_index290.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={294: ('$phi290.0', '$phi290.1', '$phi290.2', '$phi290.3'), 296: ('$phi290.0', '$phi290.1', '$phi290.2', '$phi290.3')})\n", - "2024-10-16 10:11:07,719 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=294 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((294, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={166: ('$phi294.0', '$phi294.1', '$phi294.2', '$phi294.3')})\n", - "2024-10-16 10:11:07,720 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=296 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((296, {'res': '$sparse_start296.4'}), (298, {'value': '$sparse_start296.4'}), (300, {'res': '$tof_slices300.5'}), (302, {'value': '$tof_slices300.5', 'res': '$302get_iter.6'})), outgoing_phis={'$phi304.4': '$302get_iter.6'}, blockstack=(), active_try_block=None, outgoing_edgepushed={304: ('$phi296.0', '$phi296.1', '$phi296.2', '$phi296.3', '$302get_iter.6')})\n", - "2024-10-16 10:11:07,720 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=304 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((304, {'iterator': '$phi304.4', 'pair': '$304for_iter.5', 'indval': '$304for_iter.6', 'pred': '$304for_iter.7'}),), outgoing_phis={'$phi306.5': '$304for_iter.6'}, blockstack=(), active_try_block=None, outgoing_edgepushed={464: ('$phi304.0', '$phi304.1', '$phi304.2', '$phi304.3'), 306: ('$phi304.0', '$phi304.1', '$phi304.2', '$phi304.3', '$phi304.4', '$304for_iter.6')})\n", - "2024-10-16 10:11:07,721 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=306 nstack_initial=6):\n", - "AdaptBlockInfo(insts=((306, {'iterable': '$phi306.5', 'stores': ['$306unpack_sequence.6', '$306unpack_sequence.7', '$306unpack_sequence.8'], 'tupleobj': '$306unpack_sequence.9'}), (308, {'value': '$306unpack_sequence.6'}), (310, {'value': '$306unpack_sequence.7'}), (312, {'value': '$306unpack_sequence.8'}), (314, {'res': '$idx314.10'}), (316, {'res': '$316load_global.11'}), (318, {'item': '$316load_global.11', 'res': '$318load_method.12'}), (320, {'res': '$tof_indices320.13'}), (322, {'res': '$idx322.14'}), (324, {'res': '$sparse_end324.15'}), (326, {'start': '$idx322.14', 'stop': '$sparse_end324.15', 'step': None, 'res': '$326build_slice.17', 'slicevar': '$326build_slice.16'}), (328, {'index': '$326build_slice.17', 'target': '$tof_indices320.13', 'res': '$328binary_subscr.18'}), (330, {'res': '$tof_start330.19'}), (332, {'func': '$318load_method.12', 'args': ['$328binary_subscr.18', '$tof_start330.19'], 'res': '$332call_method.20'}), (334, {'lhs': '$idx314.10', 'rhs': '$332call_method.20', 'res': '$334inplace_add.21'}), (336, {'value': '$334inplace_add.21'}), (338, {'res': '$tof_indices338.22'}), (340, {'res': '$idx340.23'}), (342, {'index': '$idx340.23', 'target': '$tof_indices338.22', 'res': '$342binary_subscr.24'}), (344, {'value': '$342binary_subscr.24'}), (346, {'res': '$tof_value346.25'}), (348, {'res': '$tof_stop348.26'}), (350, {'lhs': '$tof_value346.25', 'rhs': '$tof_stop348.26', 'res': '$350compare_op.27'}), (352, {'pred': '$350compare_op.27'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={354: ('$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4'), 462: ('$phi306.0', '$phi306.1', '$phi306.2', '$phi306.3', '$phi306.4')})\n", - "2024-10-16 10:11:07,722 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=354 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((354, {'res': '$idx354.5'}), (356, {'res': '$sparse_end356.6'}), (358, {'lhs': '$idx354.5', 'rhs': '$sparse_end356.6', 'res': '$358compare_op.7'}), (360, {'pred': '$358compare_op.7'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={362: ('$phi354.0', '$phi354.1', '$phi354.2', '$phi354.3', '$phi354.4'), 462: ('$phi354.0', '$phi354.1', '$phi354.2', '$phi354.3', '$phi354.4')})\n", - "2024-10-16 10:11:07,723 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=362 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((362, {'res': '$tof_value362.5'}), (364, {'res': '$364load_global.6'}), (366, {'res': '$tof_start366.7'}), (368, {'res': '$tof_stop368.8'}), (370, {'res': '$tof_step370.9'}), (372, {'func': '$364load_global.6', 'args': ['$tof_start366.7', '$tof_stop368.8', '$tof_step370.9'], 'res': '$372call_function.10'}), (374, {'lhs': '$tof_value362.5', 'rhs': '$372call_function.10', 'res': '$374contains_op.11'}), (376, {'pred': '$374contains_op.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={378: ('$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4'), 430: ('$phi362.0', '$phi362.1', '$phi362.2', '$phi362.3', '$phi362.4')})\n", - "2024-10-16 10:11:07,724 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=378 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((378, {'res': '$intensities378.5'}), (380, {'res': '$idx380.6'}), (382, {'index': '$idx380.6', 'target': '$intensities378.5', 'res': '$382binary_subscr.7'}), (384, {'value': '$382binary_subscr.7'}), (386, {'res': '$intensity_slices386.8'}), (388, {'value': '$intensity_slices386.8', 'res': '$388get_iter.9'})), outgoing_phis={'$phi390.5': '$388get_iter.9'}, blockstack=(), active_try_block=None, outgoing_edgepushed={390: ('$phi378.0', '$phi378.1', '$phi378.2', '$phi378.3', '$phi378.4', '$388get_iter.9')})\n", - "2024-10-16 10:11:07,725 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=390 nstack_initial=6):\n", - "AdaptBlockInfo(insts=((390, {'iterator': '$phi390.5', 'pair': '$390for_iter.6', 'indval': '$390for_iter.7', 'pred': '$390for_iter.8'}),), outgoing_phis={'$phi392.6': '$390for_iter.7'}, blockstack=(), active_try_block=None, outgoing_edgepushed={430: ('$phi390.0', '$phi390.1', '$phi390.2', '$phi390.3', '$phi390.4'), 392: ('$phi390.0', '$phi390.1', '$phi390.2', '$phi390.3', '$phi390.4', '$phi390.5', '$390for_iter.7')})\n", - "2024-10-16 10:11:07,726 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=392 nstack_initial=7):\n", - "AdaptBlockInfo(insts=((392, {'iterable': '$phi392.6', 'stores': ['$392unpack_sequence.7', '$392unpack_sequence.8'], 'tupleobj': '$392unpack_sequence.9'}), (394, {'value': '$392unpack_sequence.7'}), (396, {'value': '$392unpack_sequence.8'}), (398, {'res': '$low_intensity398.10'}), (400, {'res': '$intensity400.11'}), (402, {'lhs': '$low_intensity398.10', 'rhs': '$intensity400.11', 'res': '$402compare_op.12'}), (404, {'pred': '$402compare_op.12'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={406: ('$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5'), 428: ('$phi392.0', '$phi392.1', '$phi392.2', '$phi392.3', '$phi392.4', '$phi392.5')})\n", - "2024-10-16 10:11:07,727 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=406 nstack_initial=6):\n", - "AdaptBlockInfo(insts=((406, {'res': '$intensity406.6'}), (408, {'res': '$high_intensity408.7'}), (410, {'lhs': '$intensity406.6', 'rhs': '$high_intensity408.7', 'res': '$410compare_op.8'}), (412, {'pred': '$410compare_op.8'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={414: ('$phi406.0', '$phi406.1', '$phi406.2', '$phi406.3', '$phi406.4', '$phi406.5'), 428: ('$phi406.0', '$phi406.1', '$phi406.2', '$phi406.3', '$phi406.4', '$phi406.5')})\n", - "2024-10-16 10:11:07,727 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=414 nstack_initial=6):\n", - "AdaptBlockInfo(insts=((414, {'res': '$result414.6'}), (416, {'item': '$result414.6', 'res': '$416load_method.7'}), (418, {'res': '$idx418.8'}), (420, {'func': '$416load_method.7', 'args': ['$idx418.8'], 'res': '$420call_method.9'}), (426, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={430: ('$phi414.0', '$phi414.1', '$phi414.2', '$phi414.3', '$phi414.4')})\n", - "2024-10-16 10:11:07,728 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=428 nstack_initial=6):\n", - "AdaptBlockInfo(insts=((428, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={390: ('$phi428.0', '$phi428.1', '$phi428.2', '$phi428.3', '$phi428.4', '$phi428.5')})\n", - "2024-10-16 10:11:07,729 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=430 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((430, {'res': '$idx430.5'}), (432, {'res': '$const432.6'}), (434, {'lhs': '$idx430.5', 'rhs': '$const432.6', 'res': '$434inplace_add.7'}), (436, {'value': '$434inplace_add.7'}), (438, {'res': '$tof_indices438.8'}), (440, {'res': '$idx440.9'}), (442, {'index': '$idx440.9', 'target': '$tof_indices438.8', 'res': '$442binary_subscr.10'}), (444, {'value': '$442binary_subscr.10'}), (446, {'res': '$tof_value446.11'}), (448, {'res': '$tof_stop448.12'}), (450, {'lhs': '$tof_value446.11', 'rhs': '$tof_stop448.12', 'res': '$450compare_op.13'}), (452, {'pred': '$450compare_op.13'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={454: ('$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4'), 462: ('$phi430.0', '$phi430.1', '$phi430.2', '$phi430.3', '$phi430.4')})\n", - "2024-10-16 10:11:07,730 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=454 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((454, {'res': '$idx454.5'}), (456, {'res': '$sparse_end456.6'}), (458, {'lhs': '$idx454.5', 'rhs': '$sparse_end456.6', 'res': '$458compare_op.7'}), (460, {'pred': '$458compare_op.7'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={462: ('$phi454.0', '$phi454.1', '$phi454.2', '$phi454.3', '$phi454.4'), 362: ('$phi454.0', '$phi454.1', '$phi454.2', '$phi454.3', '$phi454.4')})\n", - "2024-10-16 10:11:07,731 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=462 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((462, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={304: ('$phi462.0', '$phi462.1', '$phi462.2', '$phi462.3', '$phi462.4')})\n", - "2024-10-16 10:11:07,731 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=464 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((464, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={166: ('$phi464.0', '$phi464.1', '$phi464.2', '$phi464.3')})\n", - "2024-10-16 10:11:07,732 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=466 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((466, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={122: ('$phi466.0', '$phi466.1', '$phi466.2')})\n", - "2024-10-16 10:11:07,733 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=468 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((468, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={110: ('$phi468.0', '$phi468.1')})\n", - "2024-10-16 10:11:07,734 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=470 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((470, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={66: ('$phi470.0',)})\n", - "2024-10-16 10:11:07,735 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=472 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((472, {'res': '$472load_global.0'}), (474, {'item': '$472load_global.0', 'res': '$474load_method.1'}), (476, {'res': '$result476.2'}), (478, {'func': '$474load_method.1', 'args': ['$result476.2'], 'res': '$478call_method.3'}), (480, {'retval': '$478call_method.3', 'castval': '$480return_value.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:07,753 - numba.core.interpreter - DEBUG - label 0:\n", - " frame_slices = arg(0, name=frame_slices) ['frame_slices']\n", - " scan_slices = arg(1, name=scan_slices) ['scan_slices']\n", - " precursor_slices = arg(2, name=precursor_slices) ['precursor_slices']\n", - " tof_slices = arg(3, name=tof_slices) ['tof_slices']\n", - " quad_slices = arg(4, name=quad_slices) ['quad_slices']\n", - " intensity_slices = arg(5, name=intensity_slices) ['intensity_slices']\n", - " frame_max_index = arg(6, name=frame_max_index) ['frame_max_index']\n", - " scan_max_index = arg(7, name=scan_max_index) ['scan_max_index']\n", - " push_indptr = arg(8, name=push_indptr) ['push_indptr']\n", - " precursor_indices = arg(9, name=precursor_indices) ['precursor_indices']\n", - " quad_mz_values = arg(10, name=quad_mz_values) ['quad_mz_values']\n", - " quad_indptr = arg(11, name=quad_indptr) ['quad_indptr']\n", - " tof_indices = arg(12, name=tof_indices) ['tof_indices']\n", - " intensities = arg(13, name=intensities) ['intensities']\n", - " result = build_list(items=[]) ['result']\n", - " quad_index = const(int, -1) ['quad_index']\n", - " new_quad_index = const(int, -1) ['new_quad_index']\n", - " quad_end = const(int, -1) ['quad_end']\n", - " is_valid_quad_index = const(bool, True) ['is_valid_quad_index']\n", - " $const24.6 = const(NoneType, None) ['$const24.6']\n", - " $const26.7 = const(int, -1) ['$const26.7']\n", - " $28build_slice.8 = global(slice: ) ['$28build_slice.8']\n", - " $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None) ['$28build_slice.8', '$28build_slice.9', '$const24.6', '$const26.7']\n", - " $30binary_subscr.10 = getitem(value=push_indptr, index=$28build_slice.9, fn=) ['$28build_slice.9', '$30binary_subscr.10', 'push_indptr']\n", - " $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape) ['$30binary_subscr.10', '$32load_method.11']\n", - " starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None) ['$32load_method.11', 'frame_max_index', 'scan_max_index', 'starts']\n", - " $const44.16 = const(int, 1) ['$const44.16']\n", - " $const46.17 = const(NoneType, None) ['$const46.17']\n", - " $48build_slice.18 = global(slice: ) ['$48build_slice.18']\n", - " $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None) ['$48build_slice.18', '$48build_slice.19', '$const44.16', '$const46.17']\n", - " $50binary_subscr.20 = getitem(value=push_indptr, index=$48build_slice.19, fn=) ['$48build_slice.19', '$50binary_subscr.20', 'push_indptr']\n", - " $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape) ['$50binary_subscr.20', '$52load_method.21']\n", - " ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None) ['$52load_method.21', 'ends', 'frame_max_index', 'scan_max_index']\n", - " $64get_iter.26 = getiter(value=frame_slices) ['$64get_iter.26', 'frame_slices']\n", - " $phi66.0 = $64get_iter.26 ['$64get_iter.26', '$phi66.0']\n", - " jump 66 []\n", - "label 66:\n", - " $66for_iter.1 = iternext(value=$phi66.0) ['$66for_iter.1', '$phi66.0']\n", - " $66for_iter.2 = pair_first(value=$66for_iter.1) ['$66for_iter.1', '$66for_iter.2']\n", - " $66for_iter.3 = pair_second(value=$66for_iter.1) ['$66for_iter.1', '$66for_iter.3']\n", - " $phi68.1 = $66for_iter.2 ['$66for_iter.2', '$phi68.1']\n", - " branch $66for_iter.3, 68, 472 ['$66for_iter.3']\n", - "label 68:\n", - " $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3) ['$68unpack_sequence.5', '$phi68.1']\n", - " $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=) ['$68unpack_sequence.2', '$68unpack_sequence.5']\n", - " $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=) ['$68unpack_sequence.3', '$68unpack_sequence.5']\n", - " $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=) ['$68unpack_sequence.4', '$68unpack_sequence.5']\n", - " frame_start = $68unpack_sequence.2 ['$68unpack_sequence.2', 'frame_start']\n", - " frame_stop = $68unpack_sequence.3 ['$68unpack_sequence.3', 'frame_stop']\n", - " frame_step = $68unpack_sequence.4 ['$68unpack_sequence.4', 'frame_step']\n", - " $76load_global.6 = global(zip: ) ['$76load_global.6']\n", - " $80load_global.8 = global(slice: ) ['$80load_global.8']\n", - " $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None) ['$80load_global.8', '$88call_function.12', 'frame_start', 'frame_step', 'frame_stop']\n", - " $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=) ['$88call_function.12', '$90binary_subscr.13', 'starts']\n", - " $94load_global.15 = global(slice: ) ['$94load_global.15']\n", - " $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None) ['$102call_function.19', '$94load_global.15', 'frame_start', 'frame_step', 'frame_stop']\n", - " $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=) ['$102call_function.19', '$104binary_subscr.20', 'ends']\n", - " $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None) ['$104binary_subscr.20', '$106call_function.21', '$76load_global.6', '$90binary_subscr.13']\n", - " $108get_iter.22 = getiter(value=$106call_function.21) ['$106call_function.21', '$108get_iter.22']\n", - " $phi110.1 = $108get_iter.22 ['$108get_iter.22', '$phi110.1']\n", - " jump 110 []\n", - "label 110:\n", - " $110for_iter.2 = iternext(value=$phi110.1) ['$110for_iter.2', '$phi110.1']\n", - " $110for_iter.3 = pair_first(value=$110for_iter.2) ['$110for_iter.2', '$110for_iter.3']\n", - " $110for_iter.4 = pair_second(value=$110for_iter.2) ['$110for_iter.2', '$110for_iter.4']\n", - " $phi112.2 = $110for_iter.3 ['$110for_iter.3', '$phi112.2']\n", - " branch $110for_iter.4, 112, 470 ['$110for_iter.4']\n", - "label 112:\n", - " $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2) ['$112unpack_sequence.5', '$phi112.2']\n", - " $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=) ['$112unpack_sequence.3', '$112unpack_sequence.5']\n", - " $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=) ['$112unpack_sequence.4', '$112unpack_sequence.5']\n", - " frame_start_slice = $112unpack_sequence.3 ['$112unpack_sequence.3', 'frame_start_slice']\n", - " frame_end_slice = $112unpack_sequence.4 ['$112unpack_sequence.4', 'frame_end_slice']\n", - " $120get_iter.7 = getiter(value=scan_slices) ['$120get_iter.7', 'scan_slices']\n", - " $phi122.2 = $120get_iter.7 ['$120get_iter.7', '$phi122.2']\n", - " jump 122 []\n", - "label 122:\n", - " $122for_iter.3 = iternext(value=$phi122.2) ['$122for_iter.3', '$phi122.2']\n", - " $122for_iter.4 = pair_first(value=$122for_iter.3) ['$122for_iter.3', '$122for_iter.4']\n", - " $122for_iter.5 = pair_second(value=$122for_iter.3) ['$122for_iter.3', '$122for_iter.5']\n", - " $phi124.3 = $122for_iter.4 ['$122for_iter.4', '$phi124.3']\n", - " branch $122for_iter.5, 124, 468 ['$122for_iter.5']\n", - "label 124:\n", - " $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3) ['$124unpack_sequence.7', '$phi124.3']\n", - " $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=) ['$124unpack_sequence.4', '$124unpack_sequence.7']\n", - " $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=) ['$124unpack_sequence.5', '$124unpack_sequence.7']\n", - " $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=) ['$124unpack_sequence.6', '$124unpack_sequence.7']\n", - " scan_start = $124unpack_sequence.4 ['$124unpack_sequence.4', 'scan_start']\n", - " scan_stop = $124unpack_sequence.5 ['$124unpack_sequence.5', 'scan_stop']\n", - " scan_step = $124unpack_sequence.6 ['$124unpack_sequence.6', 'scan_step']\n", - " $132load_global.8 = global(zip: ) ['$132load_global.8']\n", - " $136load_global.10 = global(slice: ) ['$136load_global.10']\n", - " $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None) ['$136load_global.10', '$144call_function.14', 'scan_start', 'scan_step', 'scan_stop']\n", - " $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=) ['$144call_function.14', '$146binary_subscr.15', 'frame_start_slice']\n", - " $150load_global.17 = global(slice: ) ['$150load_global.17']\n", - " $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None) ['$150load_global.17', '$158call_function.21', 'scan_start', 'scan_step', 'scan_stop']\n", - " $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=) ['$158call_function.21', '$160binary_subscr.22', 'frame_end_slice']\n", - " $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None) ['$132load_global.8', '$146binary_subscr.15', '$160binary_subscr.22', '$162call_function.23']\n", - " $164get_iter.24 = getiter(value=$162call_function.23) ['$162call_function.23', '$164get_iter.24']\n", - " $phi166.3 = $164get_iter.24 ['$164get_iter.24', '$phi166.3']\n", - " jump 166 []\n", - "label 166:\n", - " $166for_iter.4 = iternext(value=$phi166.3) ['$166for_iter.4', '$phi166.3']\n", - " $166for_iter.5 = pair_first(value=$166for_iter.4) ['$166for_iter.4', '$166for_iter.5']\n", - " $166for_iter.6 = pair_second(value=$166for_iter.4) ['$166for_iter.4', '$166for_iter.6']\n", - " $phi168.4 = $166for_iter.5 ['$166for_iter.5', '$phi168.4']\n", - " branch $166for_iter.6, 168, 466 ['$166for_iter.6']\n", - "label 168:\n", - " $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2) ['$168unpack_sequence.7', '$phi168.4']\n", - " $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=) ['$168unpack_sequence.5', '$168unpack_sequence.7']\n", - " $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=) ['$168unpack_sequence.6', '$168unpack_sequence.7']\n", - " sparse_start = $168unpack_sequence.5 ['$168unpack_sequence.5', 'sparse_start']\n", - " sparse_end = $168unpack_sequence.6 ['$168unpack_sequence.6', 'sparse_end']\n", - " $178compare_op.10 = sparse_start == sparse_end ['$178compare_op.10', 'sparse_end', 'sparse_start']\n", - " bool180 = global(bool: ) ['bool180']\n", - " $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None) ['$178compare_op.10', '$180pred', 'bool180']\n", - " branch $180pred, 182, 184 ['$180pred']\n", - "label 182:\n", - " jump 166 []\n", - "label 184:\n", - " $188compare_op.6 = quad_end < sparse_end ['$188compare_op.6', 'quad_end', 'sparse_end']\n", - " bool190 = global(bool: ) ['bool190']\n", - " $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None) ['$188compare_op.6', '$190pred', 'bool190']\n", - " branch $190pred, 192, 220 ['$190pred']\n", - "label 192:\n", - " $const194.5 = const(int, 1) ['$const194.5']\n", - " $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined) ['$196inplace_add.6', '$const194.5', 'new_quad_index']\n", - " new_quad_index = $196inplace_add.6 ['$196inplace_add.6', 'new_quad_index']\n", - " $const204.9 = const(int, 1) ['$const204.9']\n", - " $206binary_add.10 = new_quad_index + $const204.9 ['$206binary_add.10', '$const204.9', 'new_quad_index']\n", - " quad_end = getitem(value=quad_indptr, index=$206binary_add.10, fn=) ['$206binary_add.10', 'quad_end', 'quad_indptr']\n", - " $216compare_op.14 = quad_end < sparse_end ['$216compare_op.14', 'quad_end', 'sparse_end']\n", - " bool218 = global(bool: ) ['bool218']\n", - " $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None) ['$216compare_op.14', '$218pred', 'bool218']\n", - " branch $218pred, 192, 220 ['$218pred']\n", - "label 220:\n", - " $224compare_op.6 = quad_index != new_quad_index ['$224compare_op.6', 'new_quad_index', 'quad_index']\n", - " bool226 = global(bool: ) ['bool226']\n", - " $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None) ['$224compare_op.6', '$226pred', 'bool226']\n", - " branch $226pred, 228, 290 ['$226pred']\n", - "label 228:\n", - " quad_index = new_quad_index ['new_quad_index', 'quad_index']\n", - " $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher()) ['$232load_global.5']\n", - " $const238.8 = const(int, 0) ['$const238.8']\n", - " $240build_tuple.9 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const238.8, bruker.py:3058)]) ['$240build_tuple.9', '$const238.8', 'quad_index']\n", - " $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=) ['$240build_tuple.9', '$242binary_subscr.10', 'quad_mz_values']\n", - " $const248.13 = const(int, 1) ['$const248.13']\n", - " $250build_tuple.14 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const248.13, bruker.py:3059)]) ['$250build_tuple.14', '$const248.13', 'quad_index']\n", - " $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=) ['$250build_tuple.14', '$252binary_subscr.15', 'quad_mz_values']\n", - " $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None) ['$232load_global.5', '$242binary_subscr.10', '$252binary_subscr.15', '$256call_function.17', 'quad_slices']\n", - " bool258 = global(bool: ) ['bool258']\n", - " $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None) ['$256call_function.17', '$258pred', 'bool258']\n", - " branch $258pred, 266, 260 ['$258pred']\n", - "label 260:\n", - " is_valid_quad_index = const(bool, False) ['is_valid_quad_index']\n", - " jump 290 []\n", - "label 266:\n", - " $266load_global.4 = global(valid_precursor_index: CPUDispatcher()) ['$266load_global.4']\n", - " $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index, fn=) ['$272binary_subscr.7', 'precursor_indices', 'quad_index']\n", - " $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None) ['$266load_global.4', '$272binary_subscr.7', '$276call_function.9', 'precursor_slices']\n", - " bool278 = global(bool: ) ['bool278']\n", - " $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None) ['$276call_function.9', '$278pred', 'bool278']\n", - " branch $278pred, 286, 280 ['$278pred']\n", - "label 280:\n", - " is_valid_quad_index = const(bool, False) ['is_valid_quad_index']\n", - " jump 290 []\n", - "label 286:\n", - " is_valid_quad_index = const(bool, True) ['is_valid_quad_index']\n", - " jump 290 []\n", - "label 290:\n", - " bool292 = global(bool: ) ['bool292']\n", - " $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None) ['$292pred', 'bool292', 'is_valid_quad_index']\n", - " branch $292pred, 296, 294 ['$292pred']\n", - "label 294:\n", - " jump 166 []\n", - "label 296:\n", - " idx = sparse_start ['idx', 'sparse_start']\n", - " $302get_iter.6 = getiter(value=tof_slices) ['$302get_iter.6', 'tof_slices']\n", - " $phi304.4 = $302get_iter.6 ['$302get_iter.6', '$phi304.4']\n", - " jump 304 []\n", - "label 304:\n", - " $304for_iter.5 = iternext(value=$phi304.4) ['$304for_iter.5', '$phi304.4']\n", - " $304for_iter.6 = pair_first(value=$304for_iter.5) ['$304for_iter.5', '$304for_iter.6']\n", - " $304for_iter.7 = pair_second(value=$304for_iter.5) ['$304for_iter.5', '$304for_iter.7']\n", - " $phi306.5 = $304for_iter.6 ['$304for_iter.6', '$phi306.5']\n", - " branch $304for_iter.7, 306, 464 ['$304for_iter.7']\n", - "label 306:\n", - " $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3) ['$306unpack_sequence.9', '$phi306.5']\n", - " $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=) ['$306unpack_sequence.6', '$306unpack_sequence.9']\n", - " $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=) ['$306unpack_sequence.7', '$306unpack_sequence.9']\n", - " $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=) ['$306unpack_sequence.8', '$306unpack_sequence.9']\n", - " tof_start = $306unpack_sequence.6 ['$306unpack_sequence.6', 'tof_start']\n", - " tof_stop = $306unpack_sequence.7 ['$306unpack_sequence.7', 'tof_stop']\n", - " tof_step = $306unpack_sequence.8 ['$306unpack_sequence.8', 'tof_step']\n", - " $316load_global.11 = global(np: ) ['$316load_global.11']\n", - " $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted) ['$316load_global.11', '$318load_method.12']\n", - " $326build_slice.16 = global(slice: ) ['$326build_slice.16']\n", - " $326build_slice.17 = call $326build_slice.16(idx, sparse_end, func=$326build_slice.16, args=(Var(idx, bruker.py:3072), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None) ['$326build_slice.16', '$326build_slice.17', 'idx', 'sparse_end']\n", - " $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=) ['$326build_slice.17', '$328binary_subscr.18', 'tof_indices']\n", - " $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None) ['$318load_method.12', '$328binary_subscr.18', '$332call_method.20', 'tof_start']\n", - " $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined) ['$332call_method.20', '$334inplace_add.21', 'idx']\n", - " idx = $334inplace_add.21 ['$334inplace_add.21', 'idx']\n", - " tof_value = getitem(value=tof_indices, index=idx, fn=) ['idx', 'tof_indices', 'tof_value']\n", - " $350compare_op.27 = tof_value < tof_stop ['$350compare_op.27', 'tof_stop', 'tof_value']\n", - " bool352 = global(bool: ) ['bool352']\n", - " $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None) ['$350compare_op.27', '$352pred', 'bool352']\n", - " branch $352pred, 354, 462 ['$352pred']\n", - "label 354:\n", - " $358compare_op.7 = idx < sparse_end ['$358compare_op.7', 'idx', 'sparse_end']\n", - " bool360 = global(bool: ) ['bool360']\n", - " $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None) ['$358compare_op.7', '$360pred', 'bool360']\n", - " branch $360pred, 362, 462 ['$360pred']\n", - "label 362:\n", - " $364load_global.6 = global(range: ) ['$364load_global.6']\n", - " $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None) ['$364load_global.6', '$372call_function.10', 'tof_start', 'tof_step', 'tof_stop']\n", - " $374contains_op.11 = tof_value in $372call_function.10 ['$372call_function.10', '$374contains_op.11', 'tof_value']\n", - " bool376 = global(bool: ) ['bool376']\n", - " $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None) ['$374contains_op.11', '$376pred', 'bool376']\n", - " branch $376pred, 378, 430 ['$376pred']\n", - "label 378:\n", - " intensity = getitem(value=intensities, index=idx, fn=) ['idx', 'intensities', 'intensity']\n", - " $388get_iter.9 = getiter(value=intensity_slices) ['$388get_iter.9', 'intensity_slices']\n", - " $phi390.5 = $388get_iter.9 ['$388get_iter.9', '$phi390.5']\n", - " jump 390 []\n", - "label 390:\n", - " $390for_iter.6 = iternext(value=$phi390.5) ['$390for_iter.6', '$phi390.5']\n", - " $390for_iter.7 = pair_first(value=$390for_iter.6) ['$390for_iter.6', '$390for_iter.7']\n", - " $390for_iter.8 = pair_second(value=$390for_iter.6) ['$390for_iter.6', '$390for_iter.8']\n", - " $phi392.6 = $390for_iter.7 ['$390for_iter.7', '$phi392.6']\n", - " branch $390for_iter.8, 392, 430 ['$390for_iter.8']\n", - "label 392:\n", - " $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2) ['$392unpack_sequence.9', '$phi392.6']\n", - " $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=) ['$392unpack_sequence.7', '$392unpack_sequence.9']\n", - " $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=) ['$392unpack_sequence.8', '$392unpack_sequence.9']\n", - " low_intensity = $392unpack_sequence.7 ['$392unpack_sequence.7', 'low_intensity']\n", - " high_intensity = $392unpack_sequence.8 ['$392unpack_sequence.8', 'high_intensity']\n", - " $402compare_op.12 = low_intensity <= intensity ['$402compare_op.12', 'intensity', 'low_intensity']\n", - " bool404 = global(bool: ) ['bool404']\n", - " $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None) ['$402compare_op.12', '$404pred', 'bool404']\n", - " branch $404pred, 406, 428 ['$404pred']\n", - "label 406:\n", - " $410compare_op.8 = intensity <= high_intensity ['$410compare_op.8', 'high_intensity', 'intensity']\n", - " bool412 = global(bool: ) ['bool412']\n", - " $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None) ['$410compare_op.8', '$412pred', 'bool412']\n", - " branch $412pred, 414, 428 ['$412pred']\n", - "label 414:\n", - " $416load_method.7 = getattr(value=result, attr=append) ['$416load_method.7', 'result']\n", - " $420call_method.9 = call $416load_method.7(idx, func=$416load_method.7, args=[Var(idx, bruker.py:3072)], kws=(), vararg=None, varkwarg=None, target=None) ['$416load_method.7', '$420call_method.9', 'idx']\n", - " jump 430 []\n", - "label 428:\n", - " jump 390 []\n", - "label 430:\n", - " $const432.6 = const(int, 1) ['$const432.6']\n", - " $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined) ['$434inplace_add.7', '$const432.6', 'idx']\n", - " idx = $434inplace_add.7 ['$434inplace_add.7', 'idx']\n", - " tof_value = getitem(value=tof_indices, index=idx, fn=) ['idx', 'tof_indices', 'tof_value']\n", - " $450compare_op.13 = tof_value < tof_stop ['$450compare_op.13', 'tof_stop', 'tof_value']\n", - " bool452 = global(bool: ) ['bool452']\n", - " $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None) ['$450compare_op.13', '$452pred', 'bool452']\n", - " branch $452pred, 454, 462 ['$452pred']\n", - "label 454:\n", - " $458compare_op.7 = idx < sparse_end ['$458compare_op.7', 'idx', 'sparse_end']\n", - " bool460 = global(bool: ) ['bool460']\n", - " $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None) ['$458compare_op.7', '$460pred', 'bool460']\n", - " branch $460pred, 362, 462 ['$460pred']\n", - "label 462:\n", - " jump 304 []\n", - "label 464:\n", - " jump 166 []\n", - "label 466:\n", - " jump 122 []\n", - "label 468:\n", - " jump 110 []\n", - "label 470:\n", - " jump 66 []\n", - "label 472:\n", - " $472load_global.0 = global(np: ) ['$472load_global.0']\n", - " $474load_method.1 = getattr(value=$472load_global.0, attr=array) ['$472load_global.0', '$474load_method.1']\n", - " $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None) ['$474load_method.1', '$478call_method.3', 'result']\n", - " $480return_value.4 = cast(value=$478call_method.3) ['$478call_method.3', '$480return_value.4']\n", - " return $480return_value.4 ['$480return_value.4']\n", - "\n", - "2024-10-16 10:11:07,858 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:07,859 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,859 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:07,860 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:07,861 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:07,861 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:07,862 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:07,863 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:07,864 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:07,864 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:07,865 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:07,866 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:07,866 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:07,867 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:07,868 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:07,869 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:07,869 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:07,870 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:07,871 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:07,871 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:07,872 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:07,873 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:07,873 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:07,874 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:07,875 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,875 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:07,876 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:07,877 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,878 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:07,878 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:07,879 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:07,880 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,881 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:07,882 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:07,883 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,883 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:07,884 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:07,885 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:07,886 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 66\n", - "2024-10-16 10:11:07,887 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,888 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:07,888 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:07,889 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:07,890 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:07,891 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:07,892 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 68\n", - "2024-10-16 10:11:07,893 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,893 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:07,894 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:07,895 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:07,896 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:07,897 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:07,898 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:07,898 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:07,899 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:07,900 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:07,901 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,902 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:07,903 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:07,903 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,904 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:07,905 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,906 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:07,907 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:07,908 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:07,909 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 110\n", - "2024-10-16 10:11:07,910 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,910 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:07,911 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:07,912 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:07,913 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:07,914 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:07,914 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 112\n", - "2024-10-16 10:11:07,915 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,916 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:07,917 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:07,918 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:07,919 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:07,920 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:07,920 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:07,921 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:07,922 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:07,923 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 122\n", - "2024-10-16 10:11:07,924 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,925 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:07,925 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:07,926 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:07,927 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:07,928 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:07,929 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 124\n", - "2024-10-16 10:11:07,930 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,931 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:07,931 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:07,932 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:07,933 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:07,934 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:07,935 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:07,936 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:07,936 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:07,937 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:07,938 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,939 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:07,940 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:07,941 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,942 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:07,943 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,944 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:07,944 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:07,945 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:07,946 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 166\n", - "2024-10-16 10:11:07,947 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,948 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:07,949 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:07,970 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:07,971 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:07,971 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:07,972 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 168\n", - "2024-10-16 10:11:07,973 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,973 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:07,974 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:07,975 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:07,976 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:07,976 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:07,977 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:07,978 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:07,978 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,981 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:07,982 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 182\n", - "2024-10-16 10:11:07,983 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,983 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:07,984 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 184\n", - "2024-10-16 10:11:07,985 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,985 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:07,987 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:07,988 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,989 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:07,989 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 192\n", - "2024-10-16 10:11:07,990 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:07,991 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:07,992 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:07,993 - numba.core.ssa - DEBUG - on stmt: new_quad_index = $196inplace_add.6\n", - "2024-10-16 10:11:07,994 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:07,994 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index + $const204.9\n", - "2024-10-16 10:11:07,995 - numba.core.ssa - DEBUG - on stmt: quad_end = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:07,996 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:07,997 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:07,997 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:07,998 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:07,999 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 220\n", - "2024-10-16 10:11:07,999 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,000 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index != new_quad_index\n", - "2024-10-16 10:11:08,001 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:08,002 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,002 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:08,003 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 228\n", - "2024-10-16 10:11:08,004 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,004 - numba.core.ssa - DEBUG - on stmt: quad_index = new_quad_index\n", - "2024-10-16 10:11:08,005 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:08,006 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:08,007 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:08,007 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:08,008 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:08,009 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:08,010 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:08,011 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,011 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:08,012 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,013 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:08,013 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 260\n", - "2024-10-16 10:11:08,014 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,015 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:08,015 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,016 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 266\n", - "2024-10-16 10:11:08,017 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,018 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:08,018 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index, fn=)\n", - "2024-10-16 10:11:08,019 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,020 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:08,020 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,021 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:08,022 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 280\n", - "2024-10-16 10:11:08,022 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,023 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:08,024 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,024 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 286\n", - "2024-10-16 10:11:08,025 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,026 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:08,026 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,027 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 290\n", - "2024-10-16 10:11:08,028 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,028 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:08,029 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,030 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:08,033 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 294\n", - "2024-10-16 10:11:08,034 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,034 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,035 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 296\n", - "2024-10-16 10:11:08,036 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,036 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:08,037 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:08,038 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:08,038 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:08,039 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 304\n", - "2024-10-16 10:11:08,039 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,040 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:08,041 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:08,041 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:08,042 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:08,043 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:08,043 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 306\n", - "2024-10-16 10:11:08,044 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,045 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:08,045 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,046 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,047 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,047 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:08,048 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:08,049 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:08,049 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:08,050 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:08,051 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:08,052 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx, sparse_end, func=$326build_slice.16, args=(Var(idx, bruker.py:3072), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,052 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:08,053 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,054 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,054 - numba.core.ssa - DEBUG - on stmt: idx = $334inplace_add.21\n", - "2024-10-16 10:11:08,055 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:08,056 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:08,056 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:08,057 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,058 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:08,058 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 354\n", - "2024-10-16 10:11:08,059 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,060 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:08,060 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:08,061 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,062 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:08,062 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 362\n", - "2024-10-16 10:11:08,063 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,064 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:08,064 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,065 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:08,066 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:08,066 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,067 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:08,068 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 378\n", - "2024-10-16 10:11:08,069 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,069 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx, fn=)\n", - "2024-10-16 10:11:08,070 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:08,070 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:08,071 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:08,072 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 390\n", - "2024-10-16 10:11:08,072 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,073 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:08,074 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:08,074 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:08,075 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:08,076 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:08,076 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 392\n", - "2024-10-16 10:11:08,077 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,078 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:08,078 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,079 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,080 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:08,080 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:08,081 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:08,081 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:08,082 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,083 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:08,083 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 406\n", - "2024-10-16 10:11:08,084 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,085 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:08,085 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:08,102 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,103 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:08,104 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 414\n", - "2024-10-16 10:11:08,104 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,105 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:08,105 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx, func=$416load_method.7, args=[Var(idx, bruker.py:3072)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,107 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:08,107 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 428\n", - "2024-10-16 10:11:08,108 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,109 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:08,109 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 430\n", - "2024-10-16 10:11:08,110 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,110 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:08,111 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,111 - numba.core.ssa - DEBUG - on stmt: idx = $434inplace_add.7\n", - "2024-10-16 10:11:08,112 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:08,112 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:08,114 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:08,115 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,116 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:08,116 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 454\n", - "2024-10-16 10:11:08,117 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,117 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:08,119 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:08,119 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,120 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:08,120 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 462\n", - "2024-10-16 10:11:08,121 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,121 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:08,122 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 464\n", - "2024-10-16 10:11:08,122 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,123 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,123 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 466\n", - "2024-10-16 10:11:08,124 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,124 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:08,125 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 468\n", - "2024-10-16 10:11:08,126 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,126 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:08,127 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 470\n", - "2024-10-16 10:11:08,129 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,130 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:08,130 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 472\n", - "2024-10-16 10:11:08,131 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,131 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:08,132 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:08,132 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,133 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:08,134 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:08,134 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 473\n", - "2024-10-16 10:11:08,135 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,135 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:08,141 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102call_function.19': [],\n", - " '$104binary_subscr.20': [],\n", - " '$106call_function.21': [],\n", - " '$108get_iter.22': [],\n", - " '$110for_iter.2': [],\n", - " '$110for_iter.3': [],\n", - " '$110for_iter.4': [],\n", - " '$112unpack_sequence.3': [],\n", - " '$112unpack_sequence.4': [],\n", - " '$112unpack_sequence.5': [],\n", - " '$120get_iter.7': [],\n", - " '$122for_iter.3': [],\n", - " '$122for_iter.4': [],\n", - " '$122for_iter.5': [],\n", - " '$124unpack_sequence.4': [],\n", - " '$124unpack_sequence.5': [],\n", - " '$124unpack_sequence.6': [],\n", - " '$124unpack_sequence.7': [],\n", - " '$132load_global.8': [],\n", - " '$136load_global.10': [],\n", - " '$144call_function.14': [],\n", - " '$146binary_subscr.15': [],\n", - " '$150load_global.17': [],\n", - " '$158call_function.21': [],\n", - " '$160binary_subscr.22': [],\n", - " '$162call_function.23': [],\n", - " '$164get_iter.24': [],\n", - " '$166for_iter.4': [],\n", - " '$166for_iter.5': [],\n", - " '$166for_iter.6': [],\n", - " '$168unpack_sequence.5': [],\n", - " '$168unpack_sequence.6': [],\n", - " '$168unpack_sequence.7': [],\n", - " '$178compare_op.10': [],\n", - " '$180pred': [],\n", - " '$188compare_op.6': [],\n", - " '$190pred': [],\n", - " '$196inplace_add.6': [],\n", - " '$206binary_add.10': [],\n", - " '$216compare_op.14': [],\n", - " '$218pred': [],\n", - " '$224compare_op.6': [],\n", - " '$226pred': [],\n", - " '$232load_global.5': [],\n", - " '$240build_tuple.9': [],\n", - " '$242binary_subscr.10': [],\n", - " '$250build_tuple.14': [],\n", - " '$252binary_subscr.15': [],\n", - " '$256call_function.17': [],\n", - " '$258pred': [],\n", - " '$266load_global.4': [],\n", - " '$272binary_subscr.7': [],\n", - " '$276call_function.9': [],\n", - " '$278pred': [],\n", - " '$28build_slice.8': [],\n", - " '$28build_slice.9': [],\n", - " '$292pred': [],\n", - " '$302get_iter.6': [],\n", - " '$304for_iter.5': [],\n", - " '$304for_iter.6': [],\n", - " '$304for_iter.7': [],\n", - " '$306unpack_sequence.6': [],\n", - " '$306unpack_sequence.7': [],\n", - " '$306unpack_sequence.8': [],\n", - " '$306unpack_sequence.9': [],\n", - " '$30binary_subscr.10': [],\n", - " '$316load_global.11': [],\n", - " '$318load_method.12': [],\n", - " '$326build_slice.16': [],\n", - " '$326build_slice.17': [],\n", - " '$328binary_subscr.18': [],\n", - " '$32load_method.11': [],\n", - " '$332call_method.20': [],\n", - " '$334inplace_add.21': [],\n", - " '$350compare_op.27': [],\n", - " '$352pred': [],\n", - " '$358compare_op.7': [],\n", - " '$360pred': [],\n", - " '$364load_global.6': [],\n", - " '$372call_function.10': [],\n", - " '$374contains_op.11': [],\n", - " '$376pred': [],\n", - " '$388get_iter.9': [],\n", - " '$390for_iter.6': [],\n", - " '$390for_iter.7': [],\n", - " '$390for_iter.8': [],\n", - " '$392unpack_sequence.7': [],\n", - " '$392unpack_sequence.8': [],\n", - " '$392unpack_sequence.9': [],\n", - " '$402compare_op.12': [],\n", - " '$404pred': [],\n", - " '$410compare_op.8': [],\n", - " '$412pred': [],\n", - " '$416load_method.7': [],\n", - " '$420call_method.9': [],\n", - " '$434inplace_add.7': [],\n", - " '$450compare_op.13': [],\n", - " '$452pred': [],\n", - " '$458compare_op.7': [],\n", - " '$460pred': [],\n", - " '$472load_global.0': [],\n", - " '$474load_method.1': [],\n", - " '$478call_method.3': [],\n", - " '$480return_value.4': [],\n", - " '$48build_slice.18': [],\n", - " '$48build_slice.19': [],\n", - " '$50binary_subscr.20': [],\n", - " '$52load_method.21': [],\n", - " '$64get_iter.26': [],\n", - " '$66for_iter.1': [],\n", - " '$66for_iter.2': [],\n", - " '$66for_iter.3': [],\n", - " '$68unpack_sequence.2': [],\n", - " '$68unpack_sequence.3': [],\n", - " '$68unpack_sequence.4': [],\n", - " '$68unpack_sequence.5': [],\n", - " '$76load_global.6': [],\n", - " '$80load_global.8': [],\n", - " '$88call_function.12': [],\n", - " '$90binary_subscr.13': [],\n", - " '$94load_global.15': [],\n", - " '$const194.5': [],\n", - " '$const204.9': [],\n", - " '$const238.8': [],\n", - " '$const24.6': [],\n", - " '$const248.13': [],\n", - " '$const26.7': [],\n", - " '$const432.6': [],\n", - " '$const44.16': [],\n", - " '$const46.17': [],\n", - " '$phi110.1': [],\n", - " '$phi112.2': [],\n", - " '$phi122.2': [],\n", - " '$phi124.3': [],\n", - " '$phi166.3': [],\n", - " '$phi168.4': [],\n", - " '$phi304.4': [],\n", - " '$phi306.5': [],\n", - " '$phi390.5': [],\n", - " '$phi392.6': [],\n", - " '$phi66.0': [],\n", - " '$phi68.1': [],\n", - " 'bool180': [],\n", - " 'bool190': [],\n", - " 'bool218': [],\n", - " 'bool226': [],\n", - " 'bool258': [],\n", - " 'bool278': [],\n", - " 'bool292': [],\n", - " 'bool352': [],\n", - " 'bool360': [],\n", - " 'bool376': [],\n", - " 'bool404': [],\n", - " 'bool412': [],\n", - " 'bool452': [],\n", - " 'bool460': [],\n", - " 'ends': [],\n", - " 'frame_end_slice': [],\n", - " 'frame_max_index': [],\n", - " 'frame_slices': [],\n", - " 'frame_start': [],\n", - " 'frame_start_slice': [],\n", - " 'frame_step': [],\n", - " 'frame_stop': [],\n", - " 'high_intensity': [],\n", - " 'idx': [,\n", - " ,\n", - " ],\n", - " 'intensities': [],\n", - " 'intensity': [],\n", - " 'intensity_slices': [],\n", - " 'is_valid_quad_index': [,\n", - " ,\n", - " ,\n", - " ],\n", - " 'low_intensity': [],\n", - " 'new_quad_index': [,\n", - " ],\n", - " 'precursor_indices': [],\n", - " 'precursor_slices': [],\n", - " 'push_indptr': [],\n", - " 'quad_end': [,\n", - " ],\n", - " 'quad_index': [,\n", - " ],\n", - " 'quad_indptr': [],\n", - " 'quad_mz_values': [],\n", - " 'quad_slices': [],\n", - " 'result': [],\n", - " 'scan_max_index': [],\n", - " 'scan_slices': [],\n", - " 'scan_start': [],\n", - " 'scan_step': [],\n", - " 'scan_stop': [],\n", - " 'sparse_end': [],\n", - " 'sparse_start': [],\n", - " 'starts': [],\n", - " 'tof_indices': [],\n", - " 'tof_slices': [],\n", - " 'tof_start': [],\n", - " 'tof_step': [],\n", - " 'tof_stop': [],\n", - " 'tof_value': [,\n", - " ]})\n", - "2024-10-16 10:11:08,142 - numba.core.ssa - DEBUG - SSA violators {'idx',\n", - " 'is_valid_quad_index',\n", - " 'new_quad_index',\n", - " 'quad_end',\n", - " 'quad_index',\n", - " 'tof_value'}\n", - "2024-10-16 10:11:08,143 - numba.core.ssa - DEBUG - Fix SSA violator on var new_quad_index\n", - "2024-10-16 10:11:08,144 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:08,144 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,145 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:08,145 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:08,149 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:08,149 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:08,150 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:08,150 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:08,151 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:08,151 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:08,152 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:08,153 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:08,154 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:08,154 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:08,155 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:08,155 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:08,156 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:08,157 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,157 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,158 - numba.core.ssa - DEBUG - first assign: new_quad_index\n", - "2024-10-16 10:11:08,159 - numba.core.ssa - DEBUG - replaced with: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,160 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:08,160 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:08,161 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:08,161 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:08,162 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:08,163 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,163 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:08,164 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:08,164 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,165 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:08,165 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:08,166 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:08,167 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,169 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:08,169 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:08,170 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,171 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:08,172 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:08,172 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:08,173 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:08,173 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,174 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:08,174 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:08,175 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:08,175 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:08,176 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:08,176 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:08,177 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,178 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:08,178 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,179 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,179 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,180 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:08,180 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:08,181 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:08,181 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:08,182 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:08,185 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,186 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:08,186 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:08,187 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,187 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:08,188 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,189 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:08,189 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:08,190 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:08,191 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:08,191 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,192 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:08,192 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:08,193 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:08,193 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:08,194 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:08,194 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:08,195 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,195 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:08,196 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,199 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,200 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:08,200 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:08,201 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:08,202 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:08,202 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:08,203 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:08,203 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,204 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:08,205 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:08,205 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:08,206 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:08,206 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:08,207 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:08,207 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,208 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:08,208 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,209 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,209 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,210 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:08,213 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:08,213 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:08,214 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:08,214 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:08,215 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,216 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:08,216 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:08,217 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,218 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:08,219 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,219 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:08,220 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:08,220 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:08,221 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:08,222 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,223 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:08,223 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:08,224 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:08,224 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:08,225 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:08,225 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:08,226 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,226 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:08,227 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,227 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,228 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:08,228 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:08,229 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:08,229 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:08,230 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,231 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:08,231 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:08,232 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,232 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,235 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:08,236 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,237 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:08,237 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:08,238 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,239 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:08,239 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:08,240 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,241 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:08,242 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,242 - numba.core.ssa - DEBUG - on stmt: new_quad_index = $196inplace_add.6\n", - "2024-10-16 10:11:08,243 - numba.core.ssa - DEBUG - replaced with: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:08,243 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:08,244 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index + $const204.9\n", - "2024-10-16 10:11:08,245 - numba.core.ssa - DEBUG - on stmt: quad_end = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:08,245 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:08,246 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:08,247 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,247 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:08,248 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:08,248 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,249 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index != new_quad_index\n", - "2024-10-16 10:11:08,250 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:08,251 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,251 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:08,252 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:08,253 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,254 - numba.core.ssa - DEBUG - on stmt: quad_index = new_quad_index\n", - "2024-10-16 10:11:08,254 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:08,255 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:08,255 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:08,256 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:08,256 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:08,257 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:08,258 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:08,259 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,259 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:08,260 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,261 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:08,261 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:08,262 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,263 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:08,264 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,264 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:08,265 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,265 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:08,266 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index, fn=)\n", - "2024-10-16 10:11:08,267 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,267 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:08,268 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,268 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:08,269 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:08,269 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,270 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:08,270 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,271 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:08,271 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,272 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:08,272 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,273 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:08,273 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,274 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:08,274 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,275 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:08,275 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:08,276 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,279 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,280 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:08,280 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,281 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:08,282 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:08,282 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:08,283 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:08,283 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:08,284 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,285 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:08,286 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:08,286 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:08,287 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:08,287 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:08,288 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:08,289 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,289 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:08,290 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,291 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,291 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,292 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:08,292 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:08,293 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:08,293 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:08,294 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:08,295 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:08,296 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx, sparse_end, func=$326build_slice.16, args=(Var(idx, bruker.py:3072), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,296 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:08,297 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,298 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,298 - numba.core.ssa - DEBUG - on stmt: idx = $334inplace_add.21\n", - "2024-10-16 10:11:08,299 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:08,300 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:08,300 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:08,301 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,301 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:08,302 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:08,303 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,304 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:08,304 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:08,305 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,305 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:08,306 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:08,308 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,308 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:08,309 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,310 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:08,310 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:08,311 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,312 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:08,312 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:08,313 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,314 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx, fn=)\n", - "2024-10-16 10:11:08,314 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:08,315 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:08,316 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:08,316 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:08,317 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,318 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:08,318 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:08,319 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:08,320 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:08,320 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:08,321 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:08,322 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,322 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:08,323 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,323 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,324 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:08,324 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:08,326 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:08,326 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:08,327 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,327 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:08,328 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:08,329 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,329 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:08,330 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:08,330 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,332 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:08,332 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:08,333 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,334 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:08,334 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx, func=$416load_method.7, args=[Var(idx, bruker.py:3072)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,335 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:08,335 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:08,336 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,337 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:08,337 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:08,338 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,338 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:08,339 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,340 - numba.core.ssa - DEBUG - on stmt: idx = $434inplace_add.7\n", - "2024-10-16 10:11:08,340 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:08,341 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:08,341 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:08,342 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,342 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:08,343 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:08,343 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,344 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:08,344 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:08,345 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,345 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:08,346 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:08,346 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,347 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:08,347 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:08,349 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,350 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,350 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:08,351 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,351 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:08,352 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:08,353 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,353 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:08,354 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:08,354 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,355 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:08,355 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:08,356 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,357 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:08,358 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:08,358 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,358 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:08,359 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:08,360 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:08,360 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,360 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:08,361 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 192: []})\n", - "2024-10-16 10:11:08,362 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:08,362 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,363 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:08,363 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:08,364 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:08,364 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:08,366 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:08,367 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:08,367 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:08,368 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:08,368 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:08,369 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:08,370 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:08,370 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:08,371 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:08,372 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:08,372 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:08,373 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,373 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,374 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:08,374 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:08,375 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:08,375 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:08,377 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:08,377 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,378 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:08,379 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:08,379 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,380 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:08,380 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:08,381 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:08,381 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,382 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:08,382 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:08,384 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,384 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:08,385 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:08,385 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:08,386 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:08,386 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,387 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:08,388 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:08,389 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:08,389 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:08,390 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:08,390 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:08,391 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,391 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:08,392 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,393 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,394 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,394 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:08,395 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:08,395 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:08,396 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:08,396 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:08,396 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,397 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:08,399 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:08,399 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,400 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:08,400 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,401 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:08,401 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:08,403 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:08,404 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:08,404 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,405 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:08,406 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:08,407 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:08,408 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:08,409 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:08,410 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:08,410 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,411 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:08,411 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,412 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,413 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:08,414 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:08,422 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:08,423 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:08,424 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:08,425 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:08,425 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,426 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:08,427 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:08,427 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:08,428 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:08,429 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:08,430 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:08,431 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,432 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:08,433 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,433 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,434 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,435 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:08,436 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:08,436 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:08,437 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:08,438 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:08,439 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,440 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:08,441 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:08,441 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,442 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:08,443 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,444 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:08,445 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:08,446 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:08,447 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:08,447 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,448 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:08,449 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:08,450 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:08,450 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:08,451 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:08,452 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:08,453 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,453 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:08,454 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,455 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,456 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:08,456 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:08,457 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:08,458 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:08,458 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,459 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:08,460 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:08,461 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,461 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,462 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:08,463 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,464 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:08,464 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:08,465 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,466 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:08,467 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:08,468 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,468 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:08,469 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,470 - numba.core.ssa - DEBUG - find_def var='new_quad_index' stmt=$196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,470 - numba.core.ssa - DEBUG - find_def_from_top label 192\n", - "2024-10-16 10:11:08,471 - numba.core.ssa - DEBUG - insert phi node new_quad_index.2 = phi(incoming_values=[], incoming_blocks=[]) at 192\n", - "2024-10-16 10:11:08,472 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-10-16 10:11:08,472 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-10-16 10:11:08,473 - numba.core.ssa - DEBUG - idom 168 from label 184\n", - "2024-10-16 10:11:08,473 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:08,474 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:08,474 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:08,475 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:08,475 - numba.core.ssa - DEBUG - find_def_from_top label 166\n", - "2024-10-16 10:11:08,476 - numba.core.ssa - DEBUG - insert phi node new_quad_index.3 = phi(incoming_values=[], incoming_blocks=[]) at 166\n", - "2024-10-16 10:11:08,476 - numba.core.ssa - DEBUG - find_def_from_bottom label 473\n", - "2024-10-16 10:11:08,476 - numba.core.ssa - DEBUG - find_def_from_top label 473\n", - "2024-10-16 10:11:08,477 - numba.core.ssa - DEBUG - insert phi node new_quad_index.4 = phi(incoming_values=[], incoming_blocks=[]) at 473\n", - "2024-10-16 10:11:08,477 - numba.core.ssa - DEBUG - find_def_from_bottom label 294\n", - "2024-10-16 10:11:08,479 - numba.core.ssa - DEBUG - find_def_from_top label 294\n", - "2024-10-16 10:11:08,480 - numba.core.ssa - DEBUG - idom 290 from label 294\n", - "2024-10-16 10:11:08,480 - numba.core.ssa - DEBUG - find_def_from_bottom label 290\n", - "2024-10-16 10:11:08,481 - numba.core.ssa - DEBUG - find_def_from_top label 290\n", - "2024-10-16 10:11:08,481 - numba.core.ssa - DEBUG - idom 220 from label 290\n", - "2024-10-16 10:11:08,481 - numba.core.ssa - DEBUG - find_def_from_bottom label 220\n", - "2024-10-16 10:11:08,482 - numba.core.ssa - DEBUG - find_def_from_top label 220\n", - "2024-10-16 10:11:08,482 - numba.core.ssa - DEBUG - insert phi node new_quad_index.5 = phi(incoming_values=[], incoming_blocks=[]) at 220\n", - "2024-10-16 10:11:08,483 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-10-16 10:11:08,483 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-10-16 10:11:08,484 - numba.core.ssa - DEBUG - idom 168 from label 184\n", - "2024-10-16 10:11:08,484 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:08,485 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:08,485 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:08,486 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:08,486 - numba.core.ssa - DEBUG - incoming_def new_quad_index.3 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:08,487 - numba.core.ssa - DEBUG - find_def_from_bottom label 192\n", - "2024-10-16 10:11:08,487 - numba.core.ssa - DEBUG - incoming_def new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:08,487 - numba.core.ssa - DEBUG - incoming_def new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:08,488 - numba.core.ssa - DEBUG - find_def_from_bottom label 182\n", - "2024-10-16 10:11:08,488 - numba.core.ssa - DEBUG - find_def_from_top label 182\n", - "2024-10-16 10:11:08,489 - numba.core.ssa - DEBUG - idom 168 from label 182\n", - "2024-10-16 10:11:08,489 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:08,490 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:08,490 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:08,491 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:08,491 - numba.core.ssa - DEBUG - incoming_def new_quad_index.3 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:08,492 - numba.core.ssa - DEBUG - find_def_from_bottom label 464\n", - "2024-10-16 10:11:08,492 - numba.core.ssa - DEBUG - find_def_from_top label 464\n", - "2024-10-16 10:11:08,493 - numba.core.ssa - DEBUG - idom 304 from label 464\n", - "2024-10-16 10:11:08,493 - numba.core.ssa - DEBUG - find_def_from_bottom label 304\n", - "2024-10-16 10:11:08,493 - numba.core.ssa - DEBUG - find_def_from_top label 304\n", - "2024-10-16 10:11:08,494 - numba.core.ssa - DEBUG - idom 296 from label 304\n", - "2024-10-16 10:11:08,494 - numba.core.ssa - DEBUG - find_def_from_bottom label 296\n", - "2024-10-16 10:11:08,495 - numba.core.ssa - DEBUG - find_def_from_top label 296\n", - "2024-10-16 10:11:08,495 - numba.core.ssa - DEBUG - idom 290 from label 296\n", - "2024-10-16 10:11:08,496 - numba.core.ssa - DEBUG - find_def_from_bottom label 290\n", - "2024-10-16 10:11:08,496 - numba.core.ssa - DEBUG - find_def_from_top label 290\n", - "2024-10-16 10:11:08,497 - numba.core.ssa - DEBUG - idom 220 from label 290\n", - "2024-10-16 10:11:08,497 - numba.core.ssa - DEBUG - find_def_from_bottom label 220\n", - "2024-10-16 10:11:08,497 - numba.core.ssa - DEBUG - incoming_def new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:08,498 - numba.core.ssa - DEBUG - incoming_def new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:08,498 - numba.core.ssa - DEBUG - find_def_from_bottom label 124\n", - "2024-10-16 10:11:08,499 - numba.core.ssa - DEBUG - find_def_from_top label 124\n", - "2024-10-16 10:11:08,499 - numba.core.ssa - DEBUG - idom 122 from label 124\n", - "2024-10-16 10:11:08,500 - numba.core.ssa - DEBUG - find_def_from_bottom label 122\n", - "2024-10-16 10:11:08,505 - numba.core.ssa - DEBUG - find_def_from_top label 122\n", - "2024-10-16 10:11:08,505 - numba.core.ssa - DEBUG - insert phi node new_quad_index.6 = phi(incoming_values=[], incoming_blocks=[]) at 122\n", - "2024-10-16 10:11:08,506 - numba.core.ssa - DEBUG - find_def_from_bottom label 112\n", - "2024-10-16 10:11:08,506 - numba.core.ssa - DEBUG - find_def_from_top label 112\n", - "2024-10-16 10:11:08,507 - numba.core.ssa - DEBUG - idom 110 from label 112\n", - "2024-10-16 10:11:08,507 - numba.core.ssa - DEBUG - find_def_from_bottom label 110\n", - "2024-10-16 10:11:08,508 - numba.core.ssa - DEBUG - find_def_from_top label 110\n", - "2024-10-16 10:11:08,509 - numba.core.ssa - DEBUG - insert phi node new_quad_index.7 = phi(incoming_values=[], incoming_blocks=[]) at 110\n", - "2024-10-16 10:11:08,510 - numba.core.ssa - DEBUG - find_def_from_bottom label 468\n", - "2024-10-16 10:11:08,510 - numba.core.ssa - DEBUG - find_def_from_top label 468\n", - "2024-10-16 10:11:08,511 - numba.core.ssa - DEBUG - idom 122 from label 468\n", - "2024-10-16 10:11:08,511 - numba.core.ssa - DEBUG - find_def_from_bottom label 122\n", - "2024-10-16 10:11:08,512 - numba.core.ssa - DEBUG - incoming_def new_quad_index.6 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:08,512 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:08,513 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-10-16 10:11:08,514 - numba.core.ssa - DEBUG - idom 66 from label 68\n", - "2024-10-16 10:11:08,514 - numba.core.ssa - DEBUG - find_def_from_bottom label 66\n", - "2024-10-16 10:11:08,515 - numba.core.ssa - DEBUG - find_def_from_top label 66\n", - "2024-10-16 10:11:08,515 - numba.core.ssa - DEBUG - insert phi node new_quad_index.8 = phi(incoming_values=[], incoming_blocks=[]) at 66\n", - "2024-10-16 10:11:08,516 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:08,517 - numba.core.ssa - DEBUG - incoming_def new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,517 - numba.core.ssa - DEBUG - find_def_from_bottom label 470\n", - "2024-10-16 10:11:08,518 - numba.core.ssa - DEBUG - find_def_from_top label 470\n", - "2024-10-16 10:11:08,518 - numba.core.ssa - DEBUG - idom 110 from label 470\n", - "2024-10-16 10:11:08,519 - numba.core.ssa - DEBUG - find_def_from_bottom label 110\n", - "2024-10-16 10:11:08,519 - numba.core.ssa - DEBUG - incoming_def new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[468])\n", - "2024-10-16 10:11:08,520 - numba.core.ssa - DEBUG - incoming_def new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:08,520 - numba.core.ssa - DEBUG - incoming_def new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:08,521 - numba.core.ssa - DEBUG - find_def_from_bottom label 466\n", - "2024-10-16 10:11:08,521 - numba.core.ssa - DEBUG - find_def_from_top label 466\n", - "2024-10-16 10:11:08,522 - numba.core.ssa - DEBUG - idom 166 from label 466\n", - "2024-10-16 10:11:08,522 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:08,523 - numba.core.ssa - DEBUG - incoming_def new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053)], incoming_blocks=[473])\n", - "2024-10-16 10:11:08,523 - numba.core.ssa - DEBUG - incoming_def new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:08,524 - numba.core.ssa - DEBUG - incoming_def new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:08,524 - numba.core.ssa - DEBUG - find_def_from_bottom label 192\n", - "2024-10-16 10:11:08,525 - numba.core.ssa - DEBUG - incoming_def new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:08,525 - numba.core.ssa - DEBUG - replaced with: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,529 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:08,529 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:08,530 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index + $const204.9\n", - "2024-10-16 10:11:08,530 - numba.core.ssa - DEBUG - find_def var='new_quad_index' stmt=$206binary_add.10 = new_quad_index + $const204.9\n", - "2024-10-16 10:11:08,531 - numba.core.ssa - DEBUG - replaced with: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:08,531 - numba.core.ssa - DEBUG - on stmt: quad_end = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:08,532 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:08,533 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:08,534 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,534 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:08,535 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:08,535 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,536 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index != new_quad_index\n", - "2024-10-16 10:11:08,536 - numba.core.ssa - DEBUG - find_def var='new_quad_index' stmt=$224compare_op.6 = quad_index != new_quad_index\n", - "2024-10-16 10:11:08,536 - numba.core.ssa - DEBUG - replaced with: $224compare_op.6 = quad_index != new_quad_index.5\n", - "2024-10-16 10:11:08,537 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:08,537 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,538 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:08,538 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:08,539 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,539 - numba.core.ssa - DEBUG - on stmt: quad_index = new_quad_index\n", - "2024-10-16 10:11:08,540 - numba.core.ssa - DEBUG - find_def var='new_quad_index' stmt=quad_index = new_quad_index\n", - "2024-10-16 10:11:08,540 - numba.core.ssa - DEBUG - find_def_from_top label 228\n", - "2024-10-16 10:11:08,541 - numba.core.ssa - DEBUG - idom 220 from label 228\n", - "2024-10-16 10:11:08,541 - numba.core.ssa - DEBUG - find_def_from_bottom label 220\n", - "2024-10-16 10:11:08,542 - numba.core.ssa - DEBUG - replaced with: quad_index = new_quad_index.5\n", - "2024-10-16 10:11:08,542 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:08,543 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:08,543 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:08,544 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:08,544 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:08,545 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:08,546 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:08,546 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,547 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:08,547 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,548 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:08,551 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:08,552 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,552 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:08,553 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,553 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:08,554 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,554 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:08,555 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index, fn=)\n", - "2024-10-16 10:11:08,555 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,556 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:08,557 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,558 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:08,558 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:08,559 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,559 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:08,560 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,560 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:08,562 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,562 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:08,562 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,563 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:08,564 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,564 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:08,565 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,566 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:08,566 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:08,567 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,567 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,568 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:08,568 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,569 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:08,569 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:08,570 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:08,570 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:08,571 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:08,571 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,572 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:08,574 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:08,574 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:08,575 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:08,575 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:08,576 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:08,576 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,577 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:08,577 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,578 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,578 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,580 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:08,580 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:08,581 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:08,581 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:08,582 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:08,583 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:08,583 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx, sparse_end, func=$326build_slice.16, args=(Var(idx, bruker.py:3072), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,584 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:08,585 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,585 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,586 - numba.core.ssa - DEBUG - on stmt: idx = $334inplace_add.21\n", - "2024-10-16 10:11:08,587 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:08,587 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:08,588 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:08,588 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,589 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:08,589 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:08,590 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,591 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:08,592 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:08,592 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,593 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:08,593 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:08,594 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,594 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:08,595 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,596 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:08,597 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:08,597 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,598 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:08,598 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:08,599 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,599 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx, fn=)\n", - "2024-10-16 10:11:08,601 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:08,601 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:08,602 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:08,602 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:08,603 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,603 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:08,604 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:08,605 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:08,606 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:08,606 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:08,607 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:08,607 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,608 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:08,608 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,609 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,610 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:08,610 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:08,611 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:08,611 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:08,612 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,612 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:08,613 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:08,613 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,614 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:08,617 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:08,618 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,618 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:08,619 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:08,619 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,620 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:08,620 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx, func=$416load_method.7, args=[Var(idx, bruker.py:3072)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,621 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:08,621 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:08,622 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,622 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:08,623 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:08,623 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,624 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:08,624 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,625 - numba.core.ssa - DEBUG - on stmt: idx = $434inplace_add.7\n", - "2024-10-16 10:11:08,625 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:08,626 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:08,626 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:08,627 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,627 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:08,628 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:08,628 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,629 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:08,629 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:08,630 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,631 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:08,635 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:08,635 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,636 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:08,636 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:08,637 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,637 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,638 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:08,638 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,639 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:08,639 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:08,640 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,640 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:08,641 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:08,641 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,642 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:08,642 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:08,643 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,643 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:08,644 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:08,644 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,645 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:08,645 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:08,646 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:08,646 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,647 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:08,650 - numba.core.ssa - DEBUG - Fix SSA violator on var quad_index\n", - "2024-10-16 10:11:08,651 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:08,651 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,652 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:08,652 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:08,652 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:08,653 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:08,653 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:08,654 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:08,654 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:08,655 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:08,655 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:08,657 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:08,658 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:08,658 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:08,658 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:08,659 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:08,659 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:08,660 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,660 - numba.core.ssa - DEBUG - first assign: quad_index\n", - "2024-10-16 10:11:08,662 - numba.core.ssa - DEBUG - replaced with: quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,663 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,664 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:08,664 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:08,665 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:08,666 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:08,667 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:08,668 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,668 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:08,669 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:08,670 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,671 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:08,672 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:08,673 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:08,673 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,674 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:08,674 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:08,675 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,675 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:08,677 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:08,678 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:08,679 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:08,679 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,680 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:08,681 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:08,682 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:08,683 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:08,683 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:08,684 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:08,685 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:08,686 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,687 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:08,687 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,688 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,689 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,690 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:08,691 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:08,692 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:08,692 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:08,693 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:08,694 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,695 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:08,696 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:08,697 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,698 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:08,698 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,699 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:08,700 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:08,701 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:08,701 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:08,702 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,703 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:08,704 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:08,704 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:08,705 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:08,706 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:08,707 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:08,707 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:08,708 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,709 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:08,710 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,710 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,711 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:08,711 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:08,712 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:08,712 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:08,714 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:08,715 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:08,715 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,716 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:08,717 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:08,718 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:08,718 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:08,719 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:08,720 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:08,721 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:08,721 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,722 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:08,723 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,723 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,724 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,725 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:08,725 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:08,726 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:08,727 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:08,727 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:08,728 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,728 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:08,729 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:08,729 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,731 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:08,731 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,732 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:08,732 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:08,733 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:08,734 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:08,735 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,735 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:08,736 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:08,736 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:08,737 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:08,737 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:08,738 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:08,738 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:08,739 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,739 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:08,740 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,740 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,740 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:08,741 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:08,741 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:08,742 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:08,743 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,743 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:08,743 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:08,744 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,744 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,745 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:08,745 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,746 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:08,746 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:08,746 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,747 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:08,747 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:08,748 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,748 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:08,749 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:08,749 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,750 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:08,750 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:08,751 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:08,755 - numba.core.ssa - DEBUG - on stmt: quad_end = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:08,756 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:08,756 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:08,757 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,757 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:08,757 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:08,758 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,758 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:08,759 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index != new_quad_index.5\n", - "2024-10-16 10:11:08,759 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:08,759 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,760 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:08,760 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:08,762 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,763 - numba.core.ssa - DEBUG - on stmt: quad_index = new_quad_index.5\n", - "2024-10-16 10:11:08,763 - numba.core.ssa - DEBUG - replaced with: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:08,763 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:08,764 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:08,764 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:08,765 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:08,765 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:08,766 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:08,766 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:08,767 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,767 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:08,768 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,768 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:08,769 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:08,769 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,769 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:08,770 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,770 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:08,771 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,771 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:08,771 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index, fn=)\n", - "2024-10-16 10:11:08,772 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,772 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:08,773 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,773 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:08,774 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:08,774 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,774 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:08,775 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,775 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:08,776 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,776 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:08,777 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:08,777 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:08,777 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,778 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:08,778 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,779 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:08,779 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:08,779 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,780 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,780 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:08,781 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,781 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:08,781 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:08,782 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:08,782 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:08,783 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:08,783 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,783 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:08,784 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:08,784 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:08,785 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:08,785 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:08,785 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:08,786 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,786 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:08,787 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,787 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,788 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,788 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:08,788 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:08,789 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:08,789 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:08,790 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:08,790 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:08,790 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx, sparse_end, func=$326build_slice.16, args=(Var(idx, bruker.py:3072), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,791 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:08,791 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,792 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,792 - numba.core.ssa - DEBUG - on stmt: idx = $334inplace_add.21\n", - "2024-10-16 10:11:08,793 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:08,793 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:08,793 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:08,794 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,794 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:08,795 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:08,795 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,795 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:08,796 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:08,796 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,797 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:08,797 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:08,798 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,798 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:08,798 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,799 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:08,799 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:08,800 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,800 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:08,801 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:08,801 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,801 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx, fn=)\n", - "2024-10-16 10:11:08,802 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:08,802 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:08,803 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:08,803 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:08,803 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,804 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:08,804 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:08,805 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:08,805 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:08,805 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:08,806 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:08,806 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,807 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:08,807 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,808 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,808 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:08,808 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:08,809 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:08,809 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:08,810 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,810 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:08,810 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:08,811 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,811 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:08,812 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:08,812 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,813 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:08,813 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:08,813 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,814 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:08,814 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx, func=$416load_method.7, args=[Var(idx, bruker.py:3072)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,815 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:08,815 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:08,815 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,816 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:08,816 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:08,817 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,817 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:08,817 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,818 - numba.core.ssa - DEBUG - on stmt: idx = $434inplace_add.7\n", - "2024-10-16 10:11:08,818 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:08,819 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:08,819 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:08,820 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,820 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:08,820 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:08,821 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,821 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:08,822 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:08,822 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,823 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:08,823 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:08,824 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,824 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:08,824 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:08,825 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,825 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,826 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:08,826 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,826 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:08,827 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:08,827 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,828 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:08,828 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:08,828 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,829 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:08,829 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:08,830 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,830 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:08,830 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:08,831 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,831 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:08,832 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:08,832 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:08,833 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,833 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:08,833 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:08,834 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 228: []})\n", - "2024-10-16 10:11:08,834 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:08,835 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,835 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:08,836 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:08,836 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:08,837 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:08,837 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:08,837 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:08,838 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:08,856 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:08,857 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:08,857 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:08,857 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:08,859 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:08,859 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:08,860 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:08,860 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:08,861 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,861 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,861 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:08,862 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:08,863 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:08,863 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:08,864 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:08,864 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,865 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:08,865 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:08,865 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,866 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:08,866 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:08,867 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:08,867 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,868 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:08,868 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:08,868 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,869 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:08,869 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:08,870 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:08,870 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:08,871 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,871 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:08,871 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:08,872 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:08,872 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:08,873 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:08,873 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:08,874 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:08,874 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,874 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:08,875 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,875 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,876 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,877 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:08,877 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:08,878 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:08,878 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:08,878 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:08,879 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,879 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:08,880 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:08,880 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,881 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:08,881 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,881 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:08,882 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:08,882 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:08,886 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:08,887 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,887 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:08,888 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:08,889 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:08,889 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:08,889 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:08,890 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:08,890 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:08,891 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,892 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:08,892 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,892 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,893 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:08,893 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:08,894 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:08,894 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:08,895 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:08,895 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:08,895 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,896 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:08,896 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:08,897 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:08,897 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:08,897 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:08,898 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:08,898 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:08,899 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,899 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:08,900 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,900 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,900 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:08,901 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:08,901 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:08,902 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:08,902 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:08,903 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:08,903 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,903 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:08,904 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:08,904 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,905 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:08,905 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,906 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:08,910 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:08,910 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:08,910 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:08,911 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,911 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:08,912 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:08,912 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:08,913 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:08,913 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:08,913 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:08,914 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:08,914 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,915 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:08,915 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:08,915 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:08,916 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:08,918 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:08,918 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:08,919 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:08,919 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,920 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:08,921 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:08,921 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,921 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:08,922 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:08,922 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,923 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:08,923 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:08,924 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,924 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:08,925 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:08,926 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,927 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:08,927 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:08,928 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:08,929 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:08,929 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:08,930 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:08,931 - numba.core.ssa - DEBUG - on stmt: quad_end = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:08,931 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:08,932 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:08,932 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:08,933 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:08,933 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:08,934 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:08,934 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:08,935 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index != new_quad_index.5\n", - "2024-10-16 10:11:08,935 - numba.core.ssa - DEBUG - find_def var='quad_index' stmt=$224compare_op.6 = quad_index != new_quad_index.5\n", - "2024-10-16 10:11:08,936 - numba.core.ssa - DEBUG - find_def_from_top label 220\n", - "2024-10-16 10:11:08,936 - numba.core.ssa - DEBUG - idom 184 from label 220\n", - "2024-10-16 10:11:08,937 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-10-16 10:11:08,939 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-10-16 10:11:08,939 - numba.core.ssa - DEBUG - idom 168 from label 184\n", - "2024-10-16 10:11:08,940 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:08,940 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:08,940 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:08,941 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:08,941 - numba.core.ssa - DEBUG - find_def_from_top label 166\n", - "2024-10-16 10:11:08,942 - numba.core.ssa - DEBUG - insert phi node quad_index.2 = phi(incoming_values=[], incoming_blocks=[]) at 166\n", - "2024-10-16 10:11:08,942 - numba.core.ssa - DEBUG - find_def_from_bottom label 473\n", - "2024-10-16 10:11:08,943 - numba.core.ssa - DEBUG - find_def_from_top label 473\n", - "2024-10-16 10:11:08,943 - numba.core.ssa - DEBUG - insert phi node quad_index.3 = phi(incoming_values=[], incoming_blocks=[]) at 473\n", - "2024-10-16 10:11:08,944 - numba.core.ssa - DEBUG - find_def_from_bottom label 294\n", - "2024-10-16 10:11:08,944 - numba.core.ssa - DEBUG - find_def_from_top label 294\n", - "2024-10-16 10:11:08,946 - numba.core.ssa - DEBUG - idom 290 from label 294\n", - "2024-10-16 10:11:08,947 - numba.core.ssa - DEBUG - find_def_from_bottom label 290\n", - "2024-10-16 10:11:08,947 - numba.core.ssa - DEBUG - find_def_from_top label 290\n", - "2024-10-16 10:11:08,948 - numba.core.ssa - DEBUG - insert phi node quad_index.4 = phi(incoming_values=[], incoming_blocks=[]) at 290\n", - "2024-10-16 10:11:08,948 - numba.core.ssa - DEBUG - find_def_from_bottom label 280\n", - "2024-10-16 10:11:08,949 - numba.core.ssa - DEBUG - find_def_from_top label 280\n", - "2024-10-16 10:11:08,949 - numba.core.ssa - DEBUG - idom 266 from label 280\n", - "2024-10-16 10:11:08,950 - numba.core.ssa - DEBUG - find_def_from_bottom label 266\n", - "2024-10-16 10:11:08,950 - numba.core.ssa - DEBUG - find_def_from_top label 266\n", - "2024-10-16 10:11:08,951 - numba.core.ssa - DEBUG - idom 228 from label 266\n", - "2024-10-16 10:11:08,952 - numba.core.ssa - DEBUG - find_def_from_bottom label 228\n", - "2024-10-16 10:11:08,953 - numba.core.ssa - DEBUG - incoming_def quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:08,953 - numba.core.ssa - DEBUG - find_def_from_bottom label 220\n", - "2024-10-16 10:11:08,954 - numba.core.ssa - DEBUG - find_def_from_top label 220\n", - "2024-10-16 10:11:08,954 - numba.core.ssa - DEBUG - idom 184 from label 220\n", - "2024-10-16 10:11:08,955 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-10-16 10:11:08,955 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-10-16 10:11:08,956 - numba.core.ssa - DEBUG - idom 168 from label 184\n", - "2024-10-16 10:11:08,956 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:08,957 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:08,958 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:08,959 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:08,959 - numba.core.ssa - DEBUG - incoming_def quad_index.2 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:08,959 - numba.core.ssa - DEBUG - find_def_from_bottom label 260\n", - "2024-10-16 10:11:08,962 - numba.core.ssa - DEBUG - find_def_from_top label 260\n", - "2024-10-16 10:11:08,962 - numba.core.ssa - DEBUG - idom 228 from label 260\n", - "2024-10-16 10:11:08,962 - numba.core.ssa - DEBUG - find_def_from_bottom label 228\n", - "2024-10-16 10:11:08,963 - numba.core.ssa - DEBUG - incoming_def quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:08,963 - numba.core.ssa - DEBUG - find_def_from_bottom label 286\n", - "2024-10-16 10:11:08,964 - numba.core.ssa - DEBUG - find_def_from_top label 286\n", - "2024-10-16 10:11:08,964 - numba.core.ssa - DEBUG - idom 266 from label 286\n", - "2024-10-16 10:11:08,966 - numba.core.ssa - DEBUG - find_def_from_bottom label 266\n", - "2024-10-16 10:11:08,966 - numba.core.ssa - DEBUG - find_def_from_top label 266\n", - "2024-10-16 10:11:08,967 - numba.core.ssa - DEBUG - idom 228 from label 266\n", - "2024-10-16 10:11:08,967 - numba.core.ssa - DEBUG - find_def_from_bottom label 228\n", - "2024-10-16 10:11:08,968 - numba.core.ssa - DEBUG - incoming_def quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:08,968 - numba.core.ssa - DEBUG - incoming_def quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:08,968 - numba.core.ssa - DEBUG - find_def_from_bottom label 182\n", - "2024-10-16 10:11:08,969 - numba.core.ssa - DEBUG - find_def_from_top label 182\n", - "2024-10-16 10:11:08,969 - numba.core.ssa - DEBUG - idom 168 from label 182\n", - "2024-10-16 10:11:08,970 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:08,970 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:08,971 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:08,971 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:08,972 - numba.core.ssa - DEBUG - incoming_def quad_index.2 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:08,972 - numba.core.ssa - DEBUG - find_def_from_bottom label 464\n", - "2024-10-16 10:11:08,972 - numba.core.ssa - DEBUG - find_def_from_top label 464\n", - "2024-10-16 10:11:08,973 - numba.core.ssa - DEBUG - idom 304 from label 464\n", - "2024-10-16 10:11:08,973 - numba.core.ssa - DEBUG - find_def_from_bottom label 304\n", - "2024-10-16 10:11:08,974 - numba.core.ssa - DEBUG - find_def_from_top label 304\n", - "2024-10-16 10:11:08,974 - numba.core.ssa - DEBUG - idom 296 from label 304\n", - "2024-10-16 10:11:08,975 - numba.core.ssa - DEBUG - find_def_from_bottom label 296\n", - "2024-10-16 10:11:08,975 - numba.core.ssa - DEBUG - find_def_from_top label 296\n", - "2024-10-16 10:11:08,975 - numba.core.ssa - DEBUG - idom 290 from label 296\n", - "2024-10-16 10:11:08,976 - numba.core.ssa - DEBUG - find_def_from_bottom label 290\n", - "2024-10-16 10:11:08,976 - numba.core.ssa - DEBUG - incoming_def quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:08,977 - numba.core.ssa - DEBUG - incoming_def quad_index.3 = phi(incoming_values=[Var(quad_index.4, bruker.py:3055), Var(quad_index.2, bruker.py:3055), Var(quad_index.4, bruker.py:3055)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:08,977 - numba.core.ssa - DEBUG - find_def_from_bottom label 124\n", - "2024-10-16 10:11:08,978 - numba.core.ssa - DEBUG - find_def_from_top label 124\n", - "2024-10-16 10:11:08,982 - numba.core.ssa - DEBUG - idom 122 from label 124\n", - "2024-10-16 10:11:08,982 - numba.core.ssa - DEBUG - find_def_from_bottom label 122\n", - "2024-10-16 10:11:08,983 - numba.core.ssa - DEBUG - find_def_from_top label 122\n", - "2024-10-16 10:11:08,983 - numba.core.ssa - DEBUG - insert phi node quad_index.5 = phi(incoming_values=[], incoming_blocks=[]) at 122\n", - "2024-10-16 10:11:08,984 - numba.core.ssa - DEBUG - find_def_from_bottom label 112\n", - "2024-10-16 10:11:08,984 - numba.core.ssa - DEBUG - find_def_from_top label 112\n", - "2024-10-16 10:11:08,985 - numba.core.ssa - DEBUG - idom 110 from label 112\n", - "2024-10-16 10:11:08,985 - numba.core.ssa - DEBUG - find_def_from_bottom label 110\n", - "2024-10-16 10:11:08,985 - numba.core.ssa - DEBUG - find_def_from_top label 110\n", - "2024-10-16 10:11:08,986 - numba.core.ssa - DEBUG - insert phi node quad_index.6 = phi(incoming_values=[], incoming_blocks=[]) at 110\n", - "2024-10-16 10:11:08,986 - numba.core.ssa - DEBUG - find_def_from_bottom label 468\n", - "2024-10-16 10:11:08,987 - numba.core.ssa - DEBUG - find_def_from_top label 468\n", - "2024-10-16 10:11:08,987 - numba.core.ssa - DEBUG - idom 122 from label 468\n", - "2024-10-16 10:11:08,988 - numba.core.ssa - DEBUG - find_def_from_bottom label 122\n", - "2024-10-16 10:11:08,988 - numba.core.ssa - DEBUG - incoming_def quad_index.5 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:08,989 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:08,991 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-10-16 10:11:08,992 - numba.core.ssa - DEBUG - idom 66 from label 68\n", - "2024-10-16 10:11:08,992 - numba.core.ssa - DEBUG - find_def_from_bottom label 66\n", - "2024-10-16 10:11:08,993 - numba.core.ssa - DEBUG - find_def_from_top label 66\n", - "2024-10-16 10:11:08,993 - numba.core.ssa - DEBUG - insert phi node quad_index.7 = phi(incoming_values=[], incoming_blocks=[]) at 66\n", - "2024-10-16 10:11:08,994 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:08,994 - numba.core.ssa - DEBUG - incoming_def quad_index = const(int, -1)\n", - "2024-10-16 10:11:08,995 - numba.core.ssa - DEBUG - find_def_from_bottom label 470\n", - "2024-10-16 10:11:08,996 - numba.core.ssa - DEBUG - find_def_from_top label 470\n", - "2024-10-16 10:11:08,996 - numba.core.ssa - DEBUG - idom 110 from label 470\n", - "2024-10-16 10:11:08,997 - numba.core.ssa - DEBUG - find_def_from_bottom label 110\n", - "2024-10-16 10:11:08,997 - numba.core.ssa - DEBUG - incoming_def quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055)], incoming_blocks=[468])\n", - "2024-10-16 10:11:08,998 - numba.core.ssa - DEBUG - incoming_def quad_index.7 = phi(incoming_values=[Var(quad_index, bruker.py:3028), Var(quad_index.6, bruker.py:3055)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:08,998 - numba.core.ssa - DEBUG - incoming_def quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055), Var(quad_index.7, bruker.py:3055)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:08,999 - numba.core.ssa - DEBUG - find_def_from_bottom label 466\n", - "2024-10-16 10:11:08,999 - numba.core.ssa - DEBUG - find_def_from_top label 466\n", - "2024-10-16 10:11:09,000 - numba.core.ssa - DEBUG - idom 166 from label 466\n", - "2024-10-16 10:11:09,000 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:09,000 - numba.core.ssa - DEBUG - incoming_def quad_index.2 = phi(incoming_values=[Var(quad_index.3, bruker.py:3055)], incoming_blocks=[473])\n", - "2024-10-16 10:11:09,001 - numba.core.ssa - DEBUG - incoming_def quad_index.5 = phi(incoming_values=[Var(quad_index.6, bruker.py:3055), Var(quad_index.2, bruker.py:3055)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,003 - numba.core.ssa - DEBUG - replaced with: $224compare_op.6 = quad_index.2 != new_quad_index.5\n", - "2024-10-16 10:11:09,004 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:09,004 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,005 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:09,006 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:09,006 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,007 - numba.core.ssa - DEBUG - on stmt: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:09,007 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:09,008 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:09,009 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:09,010 - numba.core.ssa - DEBUG - find_def var='quad_index' stmt=$240build_tuple.9 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:09,010 - numba.core.ssa - DEBUG - replaced with: $240build_tuple.9 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:09,011 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:09,011 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:09,012 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:09,012 - numba.core.ssa - DEBUG - find_def var='quad_index' stmt=$250build_tuple.14 = build_tuple(items=[Var(quad_index, bruker.py:3028), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:09,014 - numba.core.ssa - DEBUG - replaced with: $250build_tuple.14 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:09,014 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:09,015 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,015 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:09,016 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,016 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:09,017 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:09,018 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,019 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,019 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,019 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:09,021 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,021 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:09,022 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index, fn=)\n", - "2024-10-16 10:11:09,022 - numba.core.ssa - DEBUG - find_def var='quad_index' stmt=$272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index, fn=)\n", - "2024-10-16 10:11:09,023 - numba.core.ssa - DEBUG - find_def_from_top label 266\n", - "2024-10-16 10:11:09,023 - numba.core.ssa - DEBUG - idom 228 from label 266\n", - "2024-10-16 10:11:09,024 - numba.core.ssa - DEBUG - find_def_from_bottom label 228\n", - "2024-10-16 10:11:09,024 - numba.core.ssa - DEBUG - replaced with: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index.1, fn=)\n", - "2024-10-16 10:11:09,025 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,025 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:09,026 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,026 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:09,027 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:09,029 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,029 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,030 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,030 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:09,031 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,031 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:09,031 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,032 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:09,032 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,033 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:09,035 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,035 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:09,036 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:09,036 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,037 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,037 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:09,037 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,039 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:09,039 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:09,040 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:09,040 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:09,041 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:09,041 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,042 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:09,042 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,043 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,043 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:09,044 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:09,044 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:09,045 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,045 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:09,046 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,046 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,047 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,047 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:09,048 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:09,050 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:09,050 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:09,051 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:09,051 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:09,052 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx, sparse_end, func=$326build_slice.16, args=(Var(idx, bruker.py:3072), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,052 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:09,054 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,054 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,055 - numba.core.ssa - DEBUG - on stmt: idx = $334inplace_add.21\n", - "2024-10-16 10:11:09,055 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:09,056 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:09,057 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:09,057 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,057 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:09,058 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:09,058 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,059 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:09,059 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:09,060 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,060 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:09,062 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:09,063 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,063 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:09,064 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,064 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:09,065 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:09,065 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,066 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:09,066 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:09,066 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,067 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx, fn=)\n", - "2024-10-16 10:11:09,067 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:09,068 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:09,070 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:09,071 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:09,071 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,071 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:09,072 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:09,072 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:09,073 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:09,073 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:09,074 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:09,074 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,075 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:09,075 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,075 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,076 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:09,076 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:09,077 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:09,077 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:09,078 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,078 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:09,079 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:09,079 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,080 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:09,083 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:09,084 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,084 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:09,085 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:09,086 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,086 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:09,087 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx, func=$416load_method.7, args=[Var(idx, bruker.py:3072)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,087 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:09,088 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:09,088 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,089 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:09,089 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:09,090 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,090 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:09,092 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,092 - numba.core.ssa - DEBUG - on stmt: idx = $434inplace_add.7\n", - "2024-10-16 10:11:09,093 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:09,093 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:09,094 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:09,095 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,096 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:09,096 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:09,097 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,097 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:09,098 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:09,099 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,099 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:09,100 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:09,101 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,101 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:09,102 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:09,102 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,103 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,104 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:09,104 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,105 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:09,106 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:09,106 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,107 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:09,107 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:09,108 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,109 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:09,109 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:09,110 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,110 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:09,111 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:09,111 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,112 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:09,112 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:09,113 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:09,113 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,113 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:09,114 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:09,114 - numba.core.ssa - DEBUG - Fix SSA violator on var idx\n", - "2024-10-16 10:11:09,115 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:09,115 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,116 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:09,116 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:09,117 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:09,117 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:09,118 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:09,118 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:09,119 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:09,119 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:09,120 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:09,120 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:09,120 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:09,121 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:09,125 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:09,125 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:09,126 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:09,126 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:09,127 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:09,128 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:09,128 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:09,129 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:09,129 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:09,130 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:09,130 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,131 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:09,131 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:09,132 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,132 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:09,133 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:09,133 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:09,135 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,136 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:09,136 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:09,137 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,137 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:09,138 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:09,138 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:09,139 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:09,140 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,140 - numba.core.ssa - DEBUG - on stmt: quad_index.7 = phi(incoming_values=[Var(quad_index, bruker.py:3028), Var(quad_index.6, bruker.py:3055)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:09,141 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:09,142 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:09,142 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:09,143 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:09,144 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:09,144 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:09,145 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:09,146 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,146 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:09,147 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,147 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,148 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,149 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:09,149 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:09,150 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:09,151 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:09,151 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:09,152 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,152 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:09,153 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:09,154 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,155 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:09,155 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,156 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:09,156 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:09,157 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:09,158 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:09,158 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,159 - numba.core.ssa - DEBUG - on stmt: quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055), Var(quad_index.7, bruker.py:3055)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:09,159 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:09,160 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:09,160 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:09,161 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:09,162 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:09,162 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:09,163 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:09,163 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,164 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:09,164 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,165 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,165 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:09,166 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:09,166 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:09,167 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:09,167 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:09,168 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:09,168 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,169 - numba.core.ssa - DEBUG - on stmt: quad_index.5 = phi(incoming_values=[Var(quad_index.6, bruker.py:3055), Var(quad_index.2, bruker.py:3055)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,169 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,169 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:09,170 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:09,170 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:09,171 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:09,171 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:09,174 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:09,175 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,175 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:09,176 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,176 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,177 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,177 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:09,179 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:09,179 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:09,179 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:09,180 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:09,180 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,181 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:09,181 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:09,182 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,183 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:09,183 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,185 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:09,185 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:09,186 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:09,186 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:09,187 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,187 - numba.core.ssa - DEBUG - on stmt: quad_index.2 = phi(incoming_values=[Var(quad_index.3, bruker.py:3055), Var(quad_index.5, bruker.py:3055)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:09,188 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:09,188 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:09,189 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:09,190 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:09,191 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:09,191 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:09,191 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:09,192 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,192 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:09,193 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,194 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,194 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:09,194 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:09,196 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:09,196 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:09,197 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,197 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:09,198 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:09,198 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,199 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,199 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:09,200 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,200 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,202 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:09,202 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,203 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:09,203 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:09,204 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,204 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,205 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:09,206 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,207 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:09,207 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:09,208 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:09,208 - numba.core.ssa - DEBUG - on stmt: quad_end = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:09,209 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,209 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:09,210 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,211 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:09,211 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:09,212 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,212 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,213 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index.2 != new_quad_index.5\n", - "2024-10-16 10:11:09,213 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:09,214 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,214 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:09,215 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:09,217 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,217 - numba.core.ssa - DEBUG - on stmt: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:09,217 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:09,218 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:09,219 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:09,220 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:09,220 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:09,220 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:09,221 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:09,222 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,223 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:09,223 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,224 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:09,224 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:09,225 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,225 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,226 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,226 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:09,227 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,228 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:09,229 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index.1, fn=)\n", - "2024-10-16 10:11:09,229 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,230 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:09,230 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,231 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:09,231 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:09,232 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,233 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,233 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,234 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:09,234 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,235 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:09,235 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,236 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:09,236 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,237 - numba.core.ssa - DEBUG - on stmt: quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:09,237 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:09,238 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,238 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:09,240 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:09,241 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,241 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,242 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:09,242 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,242 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:09,243 - numba.core.ssa - DEBUG - first assign: idx\n", - "2024-10-16 10:11:09,243 - numba.core.ssa - DEBUG - replaced with: idx = sparse_start\n", - "2024-10-16 10:11:09,244 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:09,244 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:09,245 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:09,245 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:09,246 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,246 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:09,247 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,247 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,248 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:09,248 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:09,249 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:09,249 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,250 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:09,250 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,251 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,251 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,252 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:09,252 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:09,253 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:09,253 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:09,256 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:09,257 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:09,257 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx, sparse_end, func=$326build_slice.16, args=(Var(idx, bruker.py:3072), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,258 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:09,258 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,259 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,259 - numba.core.ssa - DEBUG - on stmt: idx = $334inplace_add.21\n", - "2024-10-16 10:11:09,261 - numba.core.ssa - DEBUG - replaced with: idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:09,261 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:09,262 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:09,262 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:09,263 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,264 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:09,264 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:09,265 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,265 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:09,266 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:09,266 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,267 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:09,268 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:09,269 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,269 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:09,270 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,271 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:09,271 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:09,271 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,272 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:09,272 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:09,274 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,274 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx, fn=)\n", - "2024-10-16 10:11:09,275 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:09,275 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:09,276 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:09,276 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:09,276 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,277 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:09,277 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:09,278 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:09,278 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:09,279 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:09,279 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:09,280 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,280 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:09,281 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,281 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,282 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:09,282 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:09,283 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:09,283 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:09,284 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,284 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:09,285 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:09,285 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,288 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:09,289 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:09,289 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,290 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:09,290 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:09,291 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,291 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:09,293 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx, func=$416load_method.7, args=[Var(idx, bruker.py:3072)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,293 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:09,294 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:09,294 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,295 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:09,296 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:09,296 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,297 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:09,297 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,298 - numba.core.ssa - DEBUG - on stmt: idx = $434inplace_add.7\n", - "2024-10-16 10:11:09,298 - numba.core.ssa - DEBUG - replaced with: idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:09,299 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:09,299 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:09,300 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:09,300 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,302 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:09,302 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:09,303 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,303 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:09,304 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:09,304 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,305 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:09,305 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:09,306 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,306 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:09,308 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:09,308 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,309 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,309 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:09,310 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,311 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:09,311 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:09,312 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,313 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:09,313 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:09,314 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,314 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:09,315 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:09,316 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,316 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:09,317 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:09,317 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,318 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:09,318 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:09,320 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:09,320 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,321 - numba.core.ssa - DEBUG - on stmt: quad_index.3 = phi(incoming_values=[Var(quad_index.4, bruker.py:3055), Var(quad_index.2, bruker.py:3055), Var(quad_index.4, bruker.py:3055)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:09,321 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:09,322 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:09,323 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {296: [],\n", - " 306: [],\n", - " 430: []})\n", - "2024-10-16 10:11:09,324 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:09,324 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,325 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:09,325 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:09,326 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:09,326 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:09,327 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:09,327 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:09,328 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:09,328 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:09,328 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:09,329 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:09,329 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:09,330 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:09,332 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:09,332 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:09,333 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:09,333 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:09,334 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:09,334 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:09,335 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:09,336 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:09,337 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:09,337 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:09,337 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,339 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:09,339 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:09,340 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,340 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:09,341 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:09,342 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:09,342 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,343 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:09,343 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:09,344 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,344 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:09,345 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:09,345 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:09,346 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:09,346 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,347 - numba.core.ssa - DEBUG - on stmt: quad_index.7 = phi(incoming_values=[Var(quad_index, bruker.py:3028), Var(quad_index.6, bruker.py:3055)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:09,347 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:09,348 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:09,348 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:09,349 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:09,349 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:09,350 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:09,350 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:09,351 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,351 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:09,352 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,352 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,353 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,353 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:09,354 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:09,354 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:09,355 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:09,358 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:09,359 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,359 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:09,360 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:09,360 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,361 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:09,361 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,362 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:09,363 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:09,363 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:09,364 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:09,364 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,365 - numba.core.ssa - DEBUG - on stmt: quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055), Var(quad_index.7, bruker.py:3055)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:09,365 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:09,366 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:09,367 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:09,368 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:09,368 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:09,369 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:09,369 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:09,370 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,370 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:09,372 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,372 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,373 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:09,373 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:09,374 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:09,374 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:09,375 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:09,375 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:09,376 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,376 - numba.core.ssa - DEBUG - on stmt: quad_index.5 = phi(incoming_values=[Var(quad_index.6, bruker.py:3055), Var(quad_index.2, bruker.py:3055)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,377 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,377 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:09,378 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:09,379 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:09,380 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:09,380 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:09,381 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:09,382 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,382 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:09,383 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,384 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,384 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,385 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:09,386 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:09,386 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:09,387 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:09,387 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:09,388 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,388 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:09,389 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:09,389 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,390 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:09,390 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,391 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:09,391 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:09,392 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:09,392 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:09,393 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,393 - numba.core.ssa - DEBUG - on stmt: quad_index.2 = phi(incoming_values=[Var(quad_index.3, bruker.py:3055), Var(quad_index.5, bruker.py:3055)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:09,394 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:09,394 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:09,395 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:09,395 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:09,398 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:09,398 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:09,399 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:09,399 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,400 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:09,400 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,401 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,401 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:09,402 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:09,402 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:09,404 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:09,404 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,405 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:09,405 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:09,406 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,407 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,408 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:09,408 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,409 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,409 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:09,410 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,411 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:09,411 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:09,412 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,412 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,412 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:09,414 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,414 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:09,415 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:09,415 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:09,416 - numba.core.ssa - DEBUG - on stmt: quad_end = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:09,416 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,417 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:09,417 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,418 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:09,418 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:09,420 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,421 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,421 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index.2 != new_quad_index.5\n", - "2024-10-16 10:11:09,421 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:09,422 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,422 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:09,423 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:09,423 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,424 - numba.core.ssa - DEBUG - on stmt: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:09,424 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:09,426 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:09,427 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:09,427 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:09,428 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:09,428 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:09,429 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:09,429 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,430 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:09,430 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,431 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:09,431 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:09,432 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,432 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,433 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,433 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:09,434 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,434 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:09,435 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index.1, fn=)\n", - "2024-10-16 10:11:09,435 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,436 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:09,436 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,437 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:09,437 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:09,438 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,438 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,439 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,439 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:09,440 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,443 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:09,443 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,444 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:09,444 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,445 - numba.core.ssa - DEBUG - on stmt: quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:09,446 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:09,447 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,447 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:09,448 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:09,449 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,449 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,450 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:09,451 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,451 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:09,452 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:09,452 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:09,453 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:09,454 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:09,454 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,455 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:09,455 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,456 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,457 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:09,457 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:09,458 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:09,459 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,459 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:09,460 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,461 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,461 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,462 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:09,462 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:09,463 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:09,464 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:09,464 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:09,465 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:09,466 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx, sparse_end, func=$326build_slice.16, args=(Var(idx, bruker.py:3072), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,467 - numba.core.ssa - DEBUG - find_def var='idx' stmt=$326build_slice.17 = call $326build_slice.16(idx, sparse_end, func=$326build_slice.16, args=(Var(idx, bruker.py:3072), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,467 - numba.core.ssa - DEBUG - find_def_from_top label 306\n", - "2024-10-16 10:11:09,468 - numba.core.ssa - DEBUG - idom 304 from label 306\n", - "2024-10-16 10:11:09,469 - numba.core.ssa - DEBUG - find_def_from_bottom label 304\n", - "2024-10-16 10:11:09,469 - numba.core.ssa - DEBUG - find_def_from_top label 304\n", - "2024-10-16 10:11:09,469 - numba.core.ssa - DEBUG - insert phi node idx.3 = phi(incoming_values=[], incoming_blocks=[]) at 304\n", - "2024-10-16 10:11:09,470 - numba.core.ssa - DEBUG - find_def_from_bottom label 296\n", - "2024-10-16 10:11:09,470 - numba.core.ssa - DEBUG - incoming_def idx = sparse_start\n", - "2024-10-16 10:11:09,471 - numba.core.ssa - DEBUG - find_def_from_bottom label 462\n", - "2024-10-16 10:11:09,471 - numba.core.ssa - DEBUG - find_def_from_top label 462\n", - "2024-10-16 10:11:09,472 - numba.core.ssa - DEBUG - insert phi node idx.4 = phi(incoming_values=[], incoming_blocks=[]) at 462\n", - "2024-10-16 10:11:09,472 - numba.core.ssa - DEBUG - find_def_from_bottom label 306\n", - "2024-10-16 10:11:09,474 - numba.core.ssa - DEBUG - incoming_def idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:09,475 - numba.core.ssa - DEBUG - find_def_from_bottom label 430\n", - "2024-10-16 10:11:09,475 - numba.core.ssa - DEBUG - incoming_def idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:09,475 - numba.core.ssa - DEBUG - find_def_from_bottom label 454\n", - "2024-10-16 10:11:09,476 - numba.core.ssa - DEBUG - find_def_from_top label 454\n", - "2024-10-16 10:11:09,476 - numba.core.ssa - DEBUG - idom 430 from label 454\n", - "2024-10-16 10:11:09,477 - numba.core.ssa - DEBUG - find_def_from_bottom label 430\n", - "2024-10-16 10:11:09,477 - numba.core.ssa - DEBUG - incoming_def idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:09,478 - numba.core.ssa - DEBUG - find_def_from_bottom label 354\n", - "2024-10-16 10:11:09,478 - numba.core.ssa - DEBUG - find_def_from_top label 354\n", - "2024-10-16 10:11:09,479 - numba.core.ssa - DEBUG - idom 306 from label 354\n", - "2024-10-16 10:11:09,479 - numba.core.ssa - DEBUG - find_def_from_bottom label 306\n", - "2024-10-16 10:11:09,480 - numba.core.ssa - DEBUG - incoming_def idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:09,482 - numba.core.ssa - DEBUG - incoming_def idx.4 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094), Var(idx.2, bruker.py:3094), Var(idx.1, bruker.py:3074)], incoming_blocks=[306, 430, 454, 354])\n", - "2024-10-16 10:11:09,482 - numba.core.ssa - DEBUG - replaced with: $326build_slice.17 = call $326build_slice.16(idx.3, sparse_end, func=$326build_slice.16, args=(Var(idx.3, bruker.py:3073), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,483 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:09,483 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,484 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,484 - numba.core.ssa - DEBUG - find_def var='idx' stmt=$334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,485 - numba.core.ssa - DEBUG - find_def_from_top label 306\n", - "2024-10-16 10:11:09,485 - numba.core.ssa - DEBUG - idom 304 from label 306\n", - "2024-10-16 10:11:09,486 - numba.core.ssa - DEBUG - find_def_from_bottom label 304\n", - "2024-10-16 10:11:09,487 - numba.core.ssa - DEBUG - replaced with: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx.3, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,488 - numba.core.ssa - DEBUG - on stmt: idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:09,488 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:09,489 - numba.core.ssa - DEBUG - find_def var='idx' stmt=tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:09,490 - numba.core.ssa - DEBUG - replaced with: tof_value = getitem(value=tof_indices, index=idx.1, fn=)\n", - "2024-10-16 10:11:09,490 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:09,491 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:09,492 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,492 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:09,493 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:09,494 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,494 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:09,495 - numba.core.ssa - DEBUG - find_def var='idx' stmt=$358compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:09,495 - numba.core.ssa - DEBUG - find_def_from_top label 354\n", - "2024-10-16 10:11:09,496 - numba.core.ssa - DEBUG - idom 306 from label 354\n", - "2024-10-16 10:11:09,496 - numba.core.ssa - DEBUG - find_def_from_bottom label 306\n", - "2024-10-16 10:11:09,496 - numba.core.ssa - DEBUG - replaced with: $358compare_op.7 = idx.1 < sparse_end\n", - "2024-10-16 10:11:09,497 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:09,498 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,498 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:09,498 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:09,499 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,499 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:09,502 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,502 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:09,503 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:09,503 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,504 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:09,504 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:09,504 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,506 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx, fn=)\n", - "2024-10-16 10:11:09,506 - numba.core.ssa - DEBUG - find_def var='idx' stmt=intensity = getitem(value=intensities, index=idx, fn=)\n", - "2024-10-16 10:11:09,507 - numba.core.ssa - DEBUG - find_def_from_top label 378\n", - "2024-10-16 10:11:09,507 - numba.core.ssa - DEBUG - idom 362 from label 378\n", - "2024-10-16 10:11:09,508 - numba.core.ssa - DEBUG - find_def_from_bottom label 362\n", - "2024-10-16 10:11:09,508 - numba.core.ssa - DEBUG - find_def_from_top label 362\n", - "2024-10-16 10:11:09,509 - numba.core.ssa - DEBUG - insert phi node idx.5 = phi(incoming_values=[], incoming_blocks=[]) at 362\n", - "2024-10-16 10:11:09,509 - numba.core.ssa - DEBUG - find_def_from_bottom label 354\n", - "2024-10-16 10:11:09,510 - numba.core.ssa - DEBUG - find_def_from_top label 354\n", - "2024-10-16 10:11:09,510 - numba.core.ssa - DEBUG - idom 306 from label 354\n", - "2024-10-16 10:11:09,512 - numba.core.ssa - DEBUG - find_def_from_bottom label 306\n", - "2024-10-16 10:11:09,512 - numba.core.ssa - DEBUG - incoming_def idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:09,513 - numba.core.ssa - DEBUG - find_def_from_bottom label 454\n", - "2024-10-16 10:11:09,513 - numba.core.ssa - DEBUG - find_def_from_top label 454\n", - "2024-10-16 10:11:09,514 - numba.core.ssa - DEBUG - idom 430 from label 454\n", - "2024-10-16 10:11:09,514 - numba.core.ssa - DEBUG - find_def_from_bottom label 430\n", - "2024-10-16 10:11:09,515 - numba.core.ssa - DEBUG - incoming_def idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:09,515 - numba.core.ssa - DEBUG - replaced with: intensity = getitem(value=intensities, index=idx.5, fn=)\n", - "2024-10-16 10:11:09,516 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:09,516 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:09,517 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:09,517 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:09,518 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,520 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:09,520 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:09,521 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:09,521 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:09,522 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:09,523 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:09,523 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,523 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:09,524 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,525 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,526 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:09,526 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:09,527 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:09,527 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:09,528 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,528 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:09,528 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:09,529 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,529 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:09,531 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:09,532 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,532 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:09,533 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:09,533 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,534 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:09,534 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx, func=$416load_method.7, args=[Var(idx, bruker.py:3072)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,535 - numba.core.ssa - DEBUG - find_def var='idx' stmt=$420call_method.9 = call $416load_method.7(idx, func=$416load_method.7, args=[Var(idx, bruker.py:3072)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,536 - numba.core.ssa - DEBUG - find_def_from_top label 414\n", - "2024-10-16 10:11:09,536 - numba.core.ssa - DEBUG - idom 406 from label 414\n", - "2024-10-16 10:11:09,537 - numba.core.ssa - DEBUG - find_def_from_bottom label 406\n", - "2024-10-16 10:11:09,537 - numba.core.ssa - DEBUG - find_def_from_top label 406\n", - "2024-10-16 10:11:09,538 - numba.core.ssa - DEBUG - idom 392 from label 406\n", - "2024-10-16 10:11:09,538 - numba.core.ssa - DEBUG - find_def_from_bottom label 392\n", - "2024-10-16 10:11:09,539 - numba.core.ssa - DEBUG - find_def_from_top label 392\n", - "2024-10-16 10:11:09,539 - numba.core.ssa - DEBUG - idom 390 from label 392\n", - "2024-10-16 10:11:09,540 - numba.core.ssa - DEBUG - find_def_from_bottom label 390\n", - "2024-10-16 10:11:09,540 - numba.core.ssa - DEBUG - find_def_from_top label 390\n", - "2024-10-16 10:11:09,541 - numba.core.ssa - DEBUG - idom 378 from label 390\n", - "2024-10-16 10:11:09,541 - numba.core.ssa - DEBUG - find_def_from_bottom label 378\n", - "2024-10-16 10:11:09,542 - numba.core.ssa - DEBUG - find_def_from_top label 378\n", - "2024-10-16 10:11:09,542 - numba.core.ssa - DEBUG - idom 362 from label 378\n", - "2024-10-16 10:11:09,542 - numba.core.ssa - DEBUG - find_def_from_bottom label 362\n", - "2024-10-16 10:11:09,543 - numba.core.ssa - DEBUG - replaced with: $420call_method.9 = call $416load_method.7(idx.5, func=$416load_method.7, args=[Var(idx.5, bruker.py:3085)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,544 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:09,544 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:09,544 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,545 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:09,545 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:09,546 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,546 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:09,547 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,547 - numba.core.ssa - DEBUG - find_def var='idx' stmt=$434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,548 - numba.core.ssa - DEBUG - find_def_from_top label 430\n", - "2024-10-16 10:11:09,548 - numba.core.ssa - DEBUG - idom 362 from label 430\n", - "2024-10-16 10:11:09,549 - numba.core.ssa - DEBUG - find_def_from_bottom label 362\n", - "2024-10-16 10:11:09,549 - numba.core.ssa - DEBUG - replaced with: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx.5, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,553 - numba.core.ssa - DEBUG - on stmt: idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:09,554 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:09,554 - numba.core.ssa - DEBUG - find_def var='idx' stmt=tof_value = getitem(value=tof_indices, index=idx, fn=)\n", - "2024-10-16 10:11:09,555 - numba.core.ssa - DEBUG - replaced with: tof_value = getitem(value=tof_indices, index=idx.2, fn=)\n", - "2024-10-16 10:11:09,555 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:09,556 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:09,556 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,557 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:09,558 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:09,559 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,559 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:09,560 - numba.core.ssa - DEBUG - find_def var='idx' stmt=$458compare_op.7 = idx < sparse_end\n", - "2024-10-16 10:11:09,561 - numba.core.ssa - DEBUG - find_def_from_top label 454\n", - "2024-10-16 10:11:09,561 - numba.core.ssa - DEBUG - idom 430 from label 454\n", - "2024-10-16 10:11:09,562 - numba.core.ssa - DEBUG - find_def_from_bottom label 430\n", - "2024-10-16 10:11:09,563 - numba.core.ssa - DEBUG - replaced with: $458compare_op.7 = idx.2 < sparse_end\n", - "2024-10-16 10:11:09,563 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:09,564 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,565 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:09,565 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:09,566 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,566 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:09,567 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:09,568 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,568 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,569 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:09,570 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,570 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:09,571 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:09,571 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,572 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:09,572 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:09,572 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,573 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:09,573 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:09,574 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,574 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:09,575 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:09,575 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,576 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:09,576 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:09,577 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:09,577 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,580 - numba.core.ssa - DEBUG - on stmt: quad_index.3 = phi(incoming_values=[Var(quad_index.4, bruker.py:3055), Var(quad_index.2, bruker.py:3055), Var(quad_index.4, bruker.py:3055)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:09,580 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:09,581 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:09,581 - numba.core.ssa - DEBUG - Fix SSA violator on var quad_end\n", - "2024-10-16 10:11:09,582 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:09,582 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,583 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:09,584 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:09,584 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:09,585 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:09,585 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:09,586 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:09,586 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:09,587 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:09,588 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:09,589 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:09,589 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:09,590 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:09,590 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:09,591 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:09,591 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:09,592 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:09,592 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:09,593 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:09,593 - numba.core.ssa - DEBUG - first assign: quad_end\n", - "2024-10-16 10:11:09,594 - numba.core.ssa - DEBUG - replaced with: quad_end = const(int, -1)\n", - "2024-10-16 10:11:09,594 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:09,596 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:09,596 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:09,597 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:09,597 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,598 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:09,598 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:09,599 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,600 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:09,601 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:09,601 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:09,602 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,602 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:09,603 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:09,603 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,604 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:09,604 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:09,605 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:09,605 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:09,605 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,606 - numba.core.ssa - DEBUG - on stmt: quad_index.7 = phi(incoming_values=[Var(quad_index, bruker.py:3028), Var(quad_index.6, bruker.py:3055)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:09,608 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:09,609 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:09,609 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:09,610 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:09,610 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:09,611 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:09,611 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:09,612 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,613 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:09,613 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,614 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,615 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,615 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:09,616 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:09,616 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:09,617 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:09,617 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:09,618 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,618 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:09,620 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:09,620 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,621 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:09,621 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,622 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:09,622 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:09,623 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:09,624 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:09,624 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,625 - numba.core.ssa - DEBUG - on stmt: quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055), Var(quad_index.7, bruker.py:3055)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:09,625 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:09,626 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:09,626 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:09,627 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:09,628 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:09,629 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:09,629 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:09,630 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,630 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:09,631 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,631 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,632 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:09,633 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:09,634 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:09,634 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:09,634 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:09,635 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:09,636 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,637 - numba.core.ssa - DEBUG - on stmt: quad_index.5 = phi(incoming_values=[Var(quad_index.6, bruker.py:3055), Var(quad_index.2, bruker.py:3055)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,637 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,638 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:09,638 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:09,638 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:09,639 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:09,640 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:09,641 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:09,641 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,642 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:09,642 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,643 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,643 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,644 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:09,644 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:09,645 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:09,646 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:09,647 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:09,647 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,648 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:09,648 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:09,649 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,649 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:09,651 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,651 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:09,652 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:09,652 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:09,653 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:09,653 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,654 - numba.core.ssa - DEBUG - on stmt: quad_index.2 = phi(incoming_values=[Var(quad_index.3, bruker.py:3055), Var(quad_index.5, bruker.py:3055)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:09,655 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:09,656 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:09,656 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:09,657 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:09,657 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:09,657 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:09,658 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:09,659 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,660 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:09,660 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,661 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,661 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:09,662 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:09,662 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:09,663 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:09,664 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,664 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:09,665 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:09,665 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,666 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,666 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:09,667 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,667 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,668 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:09,668 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,669 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:09,669 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:09,671 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,672 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,672 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:09,673 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,673 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:09,674 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:09,674 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:09,675 - numba.core.ssa - DEBUG - on stmt: quad_end = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:09,675 - numba.core.ssa - DEBUG - replaced with: quad_end.1 = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:09,676 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,676 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:09,677 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,677 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:09,678 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:09,678 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,679 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,679 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index.2 != new_quad_index.5\n", - "2024-10-16 10:11:09,680 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:09,680 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,681 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:09,681 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:09,682 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,682 - numba.core.ssa - DEBUG - on stmt: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:09,683 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:09,683 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:09,686 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:09,687 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:09,687 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:09,688 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:09,688 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:09,689 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,689 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:09,691 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,691 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:09,692 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:09,692 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,693 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,693 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,694 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:09,695 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,695 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:09,696 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index.1, fn=)\n", - "2024-10-16 10:11:09,696 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,697 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:09,697 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,698 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:09,698 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:09,699 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,699 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,700 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,700 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:09,702 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,702 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:09,703 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,704 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:09,704 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,705 - numba.core.ssa - DEBUG - on stmt: quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:09,706 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:09,706 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,707 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:09,707 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:09,708 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,708 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,709 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:09,709 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,710 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:09,710 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:09,711 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:09,711 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:09,712 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:09,712 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,713 - numba.core.ssa - DEBUG - on stmt: idx.3 = phi(incoming_values=[Var(idx, bruker.py:3072), Var(idx.4, bruker.py:3073)], incoming_blocks=[296, 462])\n", - "2024-10-16 10:11:09,713 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:09,714 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,714 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,715 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:09,715 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:09,715 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:09,716 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,716 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:09,717 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,720 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,721 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,721 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:09,722 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:09,722 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:09,722 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:09,723 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:09,724 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:09,725 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx.3, sparse_end, func=$326build_slice.16, args=(Var(idx.3, bruker.py:3073), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,725 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:09,726 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,726 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx.3, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,727 - numba.core.ssa - DEBUG - on stmt: idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:09,727 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.1, fn=)\n", - "2024-10-16 10:11:09,729 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:09,729 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:09,730 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,730 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:09,731 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:09,731 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,732 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx.1 < sparse_end\n", - "2024-10-16 10:11:09,732 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:09,733 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,733 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:09,735 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:09,735 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,736 - numba.core.ssa - DEBUG - on stmt: idx.5 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094)], incoming_blocks=[354, 454])\n", - "2024-10-16 10:11:09,736 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:09,737 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,737 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:09,738 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:09,738 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,739 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:09,739 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:09,741 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,741 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx.5, fn=)\n", - "2024-10-16 10:11:09,742 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:09,742 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:09,743 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:09,743 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:09,744 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,744 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:09,745 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:09,745 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:09,746 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:09,746 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:09,747 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:09,749 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,749 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:09,750 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,750 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,751 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:09,751 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:09,752 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:09,752 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:09,753 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,753 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:09,754 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:09,754 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,755 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:09,756 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:09,757 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,757 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:09,758 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:09,758 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,759 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:09,759 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx.5, func=$416load_method.7, args=[Var(idx.5, bruker.py:3085)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,761 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:09,761 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:09,762 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,762 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:09,763 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:09,764 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,764 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:09,765 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx.5, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,765 - numba.core.ssa - DEBUG - on stmt: idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:09,766 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.2, fn=)\n", - "2024-10-16 10:11:09,767 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:09,767 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:09,768 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,769 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:09,769 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:09,770 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,770 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx.2 < sparse_end\n", - "2024-10-16 10:11:09,771 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:09,771 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,772 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:09,772 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:09,773 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,773 - numba.core.ssa - DEBUG - on stmt: idx.4 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094), Var(idx.2, bruker.py:3094), Var(idx.1, bruker.py:3074)], incoming_blocks=[306, 430, 454, 354])\n", - "2024-10-16 10:11:09,774 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:09,775 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:09,776 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,776 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,777 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:09,777 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,778 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:09,778 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:09,779 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,779 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:09,780 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:09,781 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,782 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:09,782 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:09,783 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,783 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:09,784 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:09,784 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,785 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:09,785 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:09,786 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:09,786 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,786 - numba.core.ssa - DEBUG - on stmt: quad_index.3 = phi(incoming_values=[Var(quad_index.4, bruker.py:3055), Var(quad_index.2, bruker.py:3055), Var(quad_index.4, bruker.py:3055)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:09,787 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:09,787 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:09,788 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 192: []})\n", - "2024-10-16 10:11:09,789 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:09,789 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,790 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:09,790 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:09,790 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:09,791 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:09,791 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:09,792 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:09,792 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:09,793 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:09,793 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:09,794 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:09,794 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:09,795 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:09,795 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:09,796 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:09,796 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:09,797 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:09,797 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:09,798 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:09,798 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:09,799 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:09,799 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:09,800 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:09,800 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,801 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:09,801 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:09,802 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,802 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:09,803 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:09,803 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:09,809 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,809 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:09,810 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:09,810 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,811 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:09,811 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:09,812 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:09,812 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:09,813 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,813 - numba.core.ssa - DEBUG - on stmt: quad_index.7 = phi(incoming_values=[Var(quad_index, bruker.py:3028), Var(quad_index.6, bruker.py:3055)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:09,815 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:09,815 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:09,816 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:09,816 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:09,817 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:09,817 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:09,818 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:09,818 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,819 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:09,819 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,820 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,820 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,820 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:09,821 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:09,821 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:09,822 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:09,824 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:09,825 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,825 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:09,826 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:09,826 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,827 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:09,827 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,828 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:09,828 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:09,829 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:09,831 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:09,831 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,832 - numba.core.ssa - DEBUG - on stmt: quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055), Var(quad_index.7, bruker.py:3055)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:09,832 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:09,833 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:09,833 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:09,834 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:09,834 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:09,834 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:09,835 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:09,837 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,837 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:09,838 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,838 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,839 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:09,839 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:09,839 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:09,841 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:09,841 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:09,842 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:09,842 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,843 - numba.core.ssa - DEBUG - on stmt: quad_index.5 = phi(incoming_values=[Var(quad_index.6, bruker.py:3055), Var(quad_index.2, bruker.py:3055)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,843 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,844 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:09,844 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:09,845 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:09,845 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:09,847 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:09,847 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:09,848 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,848 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:09,849 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,849 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,850 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,850 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:09,851 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:09,851 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:09,853 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:09,853 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:09,854 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,854 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:09,855 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:09,855 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,856 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:09,856 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,857 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:09,857 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:09,859 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:09,860 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:09,860 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,860 - numba.core.ssa - DEBUG - on stmt: quad_index.2 = phi(incoming_values=[Var(quad_index.3, bruker.py:3055), Var(quad_index.5, bruker.py:3055)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:09,861 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:09,862 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:09,862 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:09,863 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:09,864 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:09,864 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:09,865 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:09,865 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,866 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:09,866 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,867 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,867 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:09,868 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:09,869 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:09,870 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:09,870 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,871 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:09,871 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:09,872 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,872 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,874 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:09,874 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,875 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,875 - numba.core.ssa - DEBUG - find_def var='quad_end' stmt=$188compare_op.6 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,876 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-10-16 10:11:09,876 - numba.core.ssa - DEBUG - idom 168 from label 184\n", - "2024-10-16 10:11:09,877 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:09,877 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:09,877 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:09,878 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:09,878 - numba.core.ssa - DEBUG - find_def_from_top label 166\n", - "2024-10-16 10:11:09,879 - numba.core.ssa - DEBUG - insert phi node quad_end.2 = phi(incoming_values=[], incoming_blocks=[]) at 166\n", - "2024-10-16 10:11:09,879 - numba.core.ssa - DEBUG - find_def_from_bottom label 473\n", - "2024-10-16 10:11:09,879 - numba.core.ssa - DEBUG - find_def_from_top label 473\n", - "2024-10-16 10:11:09,880 - numba.core.ssa - DEBUG - insert phi node quad_end.3 = phi(incoming_values=[], incoming_blocks=[]) at 473\n", - "2024-10-16 10:11:09,880 - numba.core.ssa - DEBUG - find_def_from_bottom label 294\n", - "2024-10-16 10:11:09,880 - numba.core.ssa - DEBUG - find_def_from_top label 294\n", - "2024-10-16 10:11:09,881 - numba.core.ssa - DEBUG - idom 290 from label 294\n", - "2024-10-16 10:11:09,881 - numba.core.ssa - DEBUG - find_def_from_bottom label 290\n", - "2024-10-16 10:11:09,882 - numba.core.ssa - DEBUG - find_def_from_top label 290\n", - "2024-10-16 10:11:09,882 - numba.core.ssa - DEBUG - idom 220 from label 290\n", - "2024-10-16 10:11:09,883 - numba.core.ssa - DEBUG - find_def_from_bottom label 220\n", - "2024-10-16 10:11:09,883 - numba.core.ssa - DEBUG - find_def_from_top label 220\n", - "2024-10-16 10:11:09,883 - numba.core.ssa - DEBUG - insert phi node quad_end.4 = phi(incoming_values=[], incoming_blocks=[]) at 220\n", - "2024-10-16 10:11:09,884 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-10-16 10:11:09,884 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-10-16 10:11:09,885 - numba.core.ssa - DEBUG - idom 168 from label 184\n", - "2024-10-16 10:11:09,885 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:09,885 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:09,886 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:09,886 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:09,886 - numba.core.ssa - DEBUG - incoming_def quad_end.2 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:09,887 - numba.core.ssa - DEBUG - find_def_from_bottom label 192\n", - "2024-10-16 10:11:09,887 - numba.core.ssa - DEBUG - incoming_def quad_end.1 = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:09,888 - numba.core.ssa - DEBUG - incoming_def quad_end.4 = phi(incoming_values=[Var(quad_end.2, bruker.py:3052), Var(quad_end.1, bruker.py:3054)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,888 - numba.core.ssa - DEBUG - find_def_from_bottom label 182\n", - "2024-10-16 10:11:09,888 - numba.core.ssa - DEBUG - find_def_from_top label 182\n", - "2024-10-16 10:11:09,889 - numba.core.ssa - DEBUG - idom 168 from label 182\n", - "2024-10-16 10:11:09,889 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:09,890 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:09,890 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:09,890 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:09,891 - numba.core.ssa - DEBUG - incoming_def quad_end.2 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:09,891 - numba.core.ssa - DEBUG - find_def_from_bottom label 464\n", - "2024-10-16 10:11:09,892 - numba.core.ssa - DEBUG - find_def_from_top label 464\n", - "2024-10-16 10:11:09,892 - numba.core.ssa - DEBUG - idom 304 from label 464\n", - "2024-10-16 10:11:09,892 - numba.core.ssa - DEBUG - find_def_from_bottom label 304\n", - "2024-10-16 10:11:09,898 - numba.core.ssa - DEBUG - find_def_from_top label 304\n", - "2024-10-16 10:11:09,898 - numba.core.ssa - DEBUG - idom 296 from label 304\n", - "2024-10-16 10:11:09,898 - numba.core.ssa - DEBUG - find_def_from_bottom label 296\n", - "2024-10-16 10:11:09,899 - numba.core.ssa - DEBUG - find_def_from_top label 296\n", - "2024-10-16 10:11:09,899 - numba.core.ssa - DEBUG - idom 290 from label 296\n", - "2024-10-16 10:11:09,899 - numba.core.ssa - DEBUG - find_def_from_bottom label 290\n", - "2024-10-16 10:11:09,900 - numba.core.ssa - DEBUG - find_def_from_top label 290\n", - "2024-10-16 10:11:09,900 - numba.core.ssa - DEBUG - idom 220 from label 290\n", - "2024-10-16 10:11:09,901 - numba.core.ssa - DEBUG - find_def_from_bottom label 220\n", - "2024-10-16 10:11:09,901 - numba.core.ssa - DEBUG - incoming_def quad_end.4 = phi(incoming_values=[Var(quad_end.2, bruker.py:3052), Var(quad_end.1, bruker.py:3054)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,901 - numba.core.ssa - DEBUG - incoming_def quad_end.3 = phi(incoming_values=[Var(quad_end.4, bruker.py:3052), Var(quad_end.2, bruker.py:3052), Var(quad_end.4, bruker.py:3052)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:09,902 - numba.core.ssa - DEBUG - find_def_from_bottom label 124\n", - "2024-10-16 10:11:09,902 - numba.core.ssa - DEBUG - find_def_from_top label 124\n", - "2024-10-16 10:11:09,903 - numba.core.ssa - DEBUG - idom 122 from label 124\n", - "2024-10-16 10:11:09,903 - numba.core.ssa - DEBUG - find_def_from_bottom label 122\n", - "2024-10-16 10:11:09,903 - numba.core.ssa - DEBUG - find_def_from_top label 122\n", - "2024-10-16 10:11:09,904 - numba.core.ssa - DEBUG - insert phi node quad_end.5 = phi(incoming_values=[], incoming_blocks=[]) at 122\n", - "2024-10-16 10:11:09,904 - numba.core.ssa - DEBUG - find_def_from_bottom label 112\n", - "2024-10-16 10:11:09,904 - numba.core.ssa - DEBUG - find_def_from_top label 112\n", - "2024-10-16 10:11:09,905 - numba.core.ssa - DEBUG - idom 110 from label 112\n", - "2024-10-16 10:11:09,905 - numba.core.ssa - DEBUG - find_def_from_bottom label 110\n", - "2024-10-16 10:11:09,906 - numba.core.ssa - DEBUG - find_def_from_top label 110\n", - "2024-10-16 10:11:09,906 - numba.core.ssa - DEBUG - insert phi node quad_end.6 = phi(incoming_values=[], incoming_blocks=[]) at 110\n", - "2024-10-16 10:11:09,906 - numba.core.ssa - DEBUG - find_def_from_bottom label 468\n", - "2024-10-16 10:11:09,907 - numba.core.ssa - DEBUG - find_def_from_top label 468\n", - "2024-10-16 10:11:09,907 - numba.core.ssa - DEBUG - idom 122 from label 468\n", - "2024-10-16 10:11:09,908 - numba.core.ssa - DEBUG - find_def_from_bottom label 122\n", - "2024-10-16 10:11:09,908 - numba.core.ssa - DEBUG - incoming_def quad_end.5 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:09,908 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:09,909 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-10-16 10:11:09,909 - numba.core.ssa - DEBUG - idom 66 from label 68\n", - "2024-10-16 10:11:09,909 - numba.core.ssa - DEBUG - find_def_from_bottom label 66\n", - "2024-10-16 10:11:09,910 - numba.core.ssa - DEBUG - find_def_from_top label 66\n", - "2024-10-16 10:11:09,910 - numba.core.ssa - DEBUG - insert phi node quad_end.7 = phi(incoming_values=[], incoming_blocks=[]) at 66\n", - "2024-10-16 10:11:09,911 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:09,911 - numba.core.ssa - DEBUG - incoming_def quad_end = const(int, -1)\n", - "2024-10-16 10:11:09,911 - numba.core.ssa - DEBUG - find_def_from_bottom label 470\n", - "2024-10-16 10:11:09,912 - numba.core.ssa - DEBUG - find_def_from_top label 470\n", - "2024-10-16 10:11:09,912 - numba.core.ssa - DEBUG - idom 110 from label 470\n", - "2024-10-16 10:11:09,913 - numba.core.ssa - DEBUG - find_def_from_bottom label 110\n", - "2024-10-16 10:11:09,913 - numba.core.ssa - DEBUG - incoming_def quad_end.6 = phi(incoming_values=[Var(quad_end.5, bruker.py:3052)], incoming_blocks=[468])\n", - "2024-10-16 10:11:09,913 - numba.core.ssa - DEBUG - incoming_def quad_end.7 = phi(incoming_values=[Var(quad_end, bruker.py:3030), Var(quad_end.6, bruker.py:3052)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:09,914 - numba.core.ssa - DEBUG - incoming_def quad_end.6 = phi(incoming_values=[Var(quad_end.5, bruker.py:3052), Var(quad_end.7, bruker.py:3052)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:09,914 - numba.core.ssa - DEBUG - find_def_from_bottom label 466\n", - "2024-10-16 10:11:09,915 - numba.core.ssa - DEBUG - find_def_from_top label 466\n", - "2024-10-16 10:11:09,915 - numba.core.ssa - DEBUG - idom 166 from label 466\n", - "2024-10-16 10:11:09,915 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:09,921 - numba.core.ssa - DEBUG - incoming_def quad_end.2 = phi(incoming_values=[Var(quad_end.3, bruker.py:3052)], incoming_blocks=[473])\n", - "2024-10-16 10:11:09,921 - numba.core.ssa - DEBUG - incoming_def quad_end.5 = phi(incoming_values=[Var(quad_end.6, bruker.py:3052), Var(quad_end.2, bruker.py:3052)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:09,922 - numba.core.ssa - DEBUG - replaced with: $188compare_op.6 = quad_end.2 < sparse_end\n", - "2024-10-16 10:11:09,923 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:09,923 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,923 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:09,925 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:09,925 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,926 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,926 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:09,927 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,927 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:09,928 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:09,929 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:09,929 - numba.core.ssa - DEBUG - on stmt: quad_end.1 = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:09,930 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,930 - numba.core.ssa - DEBUG - find_def var='quad_end' stmt=$216compare_op.14 = quad_end < sparse_end\n", - "2024-10-16 10:11:09,931 - numba.core.ssa - DEBUG - replaced with: $216compare_op.14 = quad_end.1 < sparse_end\n", - "2024-10-16 10:11:09,932 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:09,932 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,933 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:09,933 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:09,934 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,934 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:09,935 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index.2 != new_quad_index.5\n", - "2024-10-16 10:11:09,935 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:09,936 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,936 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:09,937 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:09,939 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,939 - numba.core.ssa - DEBUG - on stmt: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:09,940 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:09,940 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:09,941 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:09,942 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:09,943 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:09,943 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:09,944 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:09,944 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,945 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:09,946 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,946 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:09,947 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:09,948 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,948 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,949 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,949 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:09,950 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,951 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:09,951 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index.1, fn=)\n", - "2024-10-16 10:11:09,952 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,953 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:09,953 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,954 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:09,955 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:09,955 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,956 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:09,956 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,957 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:09,957 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,958 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:09,958 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:09,960 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:09,960 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,961 - numba.core.ssa - DEBUG - on stmt: quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:09,961 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:09,962 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,963 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:09,963 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:09,964 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,964 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:09,965 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:09,965 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,966 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:09,966 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:09,967 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:09,967 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:09,968 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:09,968 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,969 - numba.core.ssa - DEBUG - on stmt: idx.3 = phi(incoming_values=[Var(idx, bruker.py:3072), Var(idx.4, bruker.py:3073)], incoming_blocks=[296, 462])\n", - "2024-10-16 10:11:09,969 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:09,970 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,970 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:09,971 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:09,971 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:09,974 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:09,974 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,974 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:09,975 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:09,975 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:09,976 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:09,977 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:09,978 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:09,978 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:09,979 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:09,979 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:09,980 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:09,980 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx.3, sparse_end, func=$326build_slice.16, args=(Var(idx.3, bruker.py:3073), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,981 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:09,981 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,982 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx.3, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:09,982 - numba.core.ssa - DEBUG - on stmt: idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:09,983 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.1, fn=)\n", - "2024-10-16 10:11:09,983 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:09,984 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:09,984 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,985 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:09,985 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:09,988 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,988 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx.1 < sparse_end\n", - "2024-10-16 10:11:09,989 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:09,989 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,990 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:09,991 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:09,991 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,991 - numba.core.ssa - DEBUG - on stmt: idx.5 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094)], incoming_blocks=[354, 454])\n", - "2024-10-16 10:11:09,992 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:09,993 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,994 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:09,994 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:09,995 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:09,995 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:09,996 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:09,996 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:09,997 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx.5, fn=)\n", - "2024-10-16 10:11:09,997 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:09,997 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:09,999 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,000 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:10,000 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,001 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:10,001 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,002 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,002 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:10,003 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:10,003 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:10,004 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,004 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:10,005 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,005 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,006 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:10,006 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:10,007 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:10,007 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:10,008 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,008 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:10,011 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:10,011 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,012 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:10,012 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:10,013 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,013 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:10,014 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:10,014 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,015 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:10,015 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx.5, func=$416load_method.7, args=[Var(idx.5, bruker.py:3085)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,017 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:10,017 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:10,018 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,018 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,019 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:10,019 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,020 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:10,021 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx.5, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,021 - numba.core.ssa - DEBUG - on stmt: idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:10,022 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.2, fn=)\n", - "2024-10-16 10:11:10,022 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,023 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:10,023 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,024 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:10,025 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:10,026 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,026 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx.2 < sparse_end\n", - "2024-10-16 10:11:10,027 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:10,027 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,028 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:10,028 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:10,029 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,029 - numba.core.ssa - DEBUG - on stmt: idx.4 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094), Var(idx.2, bruker.py:3094), Var(idx.1, bruker.py:3074)], incoming_blocks=[306, 430, 454, 354])\n", - "2024-10-16 10:11:10,030 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:10,031 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:10,032 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,032 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,033 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:10,034 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,035 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:10,035 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:10,036 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,036 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:10,037 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:10,037 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,038 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:10,038 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:10,039 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,039 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:10,040 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:10,040 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,041 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:10,041 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:10,042 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:10,042 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,044 - numba.core.ssa - DEBUG - on stmt: quad_index.3 = phi(incoming_values=[Var(quad_index.4, bruker.py:3055), Var(quad_index.2, bruker.py:3055), Var(quad_index.4, bruker.py:3055)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,045 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,045 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:10,046 - numba.core.ssa - DEBUG - Fix SSA violator on var is_valid_quad_index\n", - "2024-10-16 10:11:10,047 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:10,047 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,048 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:10,048 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:10,049 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:10,049 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:10,050 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:10,050 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:10,052 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:10,052 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:10,053 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:10,053 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:10,054 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:10,054 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:10,055 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:10,055 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:10,056 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:10,056 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:10,057 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:10,057 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:10,058 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:10,058 - numba.core.ssa - DEBUG - first assign: is_valid_quad_index\n", - "2024-10-16 10:11:10,059 - numba.core.ssa - DEBUG - replaced with: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:10,059 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:10,060 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:10,060 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:10,061 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,063 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:10,064 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:10,064 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,065 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:10,066 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:10,066 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:10,067 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,067 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:10,068 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:10,069 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,069 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:10,070 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:10,070 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:10,071 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:10,071 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,072 - numba.core.ssa - DEBUG - on stmt: quad_end.7 = phi(incoming_values=[Var(quad_end, bruker.py:3030), Var(quad_end.6, bruker.py:3052)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,072 - numba.core.ssa - DEBUG - on stmt: quad_index.7 = phi(incoming_values=[Var(quad_index, bruker.py:3028), Var(quad_index.6, bruker.py:3055)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,073 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,073 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:10,074 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:10,074 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:10,075 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:10,075 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:10,076 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:10,076 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,077 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:10,077 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,077 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,078 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,078 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:10,079 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:10,079 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:10,080 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:10,080 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:10,084 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,084 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:10,085 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:10,085 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,086 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:10,086 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,087 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:10,088 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:10,089 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:10,089 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:10,090 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,090 - numba.core.ssa - DEBUG - on stmt: quad_end.6 = phi(incoming_values=[Var(quad_end.5, bruker.py:3052), Var(quad_end.7, bruker.py:3052)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,091 - numba.core.ssa - DEBUG - on stmt: quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055), Var(quad_index.7, bruker.py:3055)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,091 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,092 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:10,093 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:10,093 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:10,094 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:10,094 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:10,095 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:10,095 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,096 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:10,096 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,097 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,097 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:10,098 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:10,098 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:10,100 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:10,101 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:10,101 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:10,101 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,102 - numba.core.ssa - DEBUG - on stmt: quad_end.5 = phi(incoming_values=[Var(quad_end.6, bruker.py:3052), Var(quad_end.2, bruker.py:3052)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,102 - numba.core.ssa - DEBUG - on stmt: quad_index.5 = phi(incoming_values=[Var(quad_index.6, bruker.py:3055), Var(quad_index.2, bruker.py:3055)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,103 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,103 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:10,104 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:10,104 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:10,106 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:10,107 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:10,107 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:10,107 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,108 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:10,108 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,109 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,109 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,110 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:10,110 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:10,111 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:10,111 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:10,111 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:10,114 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,114 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:10,115 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:10,115 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,116 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:10,117 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,117 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:10,118 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:10,118 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:10,119 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:10,119 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,120 - numba.core.ssa - DEBUG - on stmt: quad_end.2 = phi(incoming_values=[Var(quad_end.3, bruker.py:3052), Var(quad_end.5, bruker.py:3052)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,121 - numba.core.ssa - DEBUG - on stmt: quad_index.2 = phi(incoming_values=[Var(quad_index.3, bruker.py:3055), Var(quad_index.5, bruker.py:3055)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,122 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,122 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:10,123 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:10,124 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:10,124 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:10,124 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:10,125 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:10,126 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,127 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:10,127 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,128 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,128 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:10,129 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:10,129 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:10,130 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:10,130 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,131 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:10,132 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:10,133 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,133 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,133 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:10,134 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,134 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end.2 < sparse_end\n", - "2024-10-16 10:11:10,135 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:10,135 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,136 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:10,136 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:10,137 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,137 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,138 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:10,140 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,140 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:10,141 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:10,142 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:10,142 - numba.core.ssa - DEBUG - on stmt: quad_end.1 = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:10,143 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end.1 < sparse_end\n", - "2024-10-16 10:11:10,143 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:10,144 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,144 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:10,145 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:10,145 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,146 - numba.core.ssa - DEBUG - on stmt: quad_end.4 = phi(incoming_values=[Var(quad_end.2, bruker.py:3052), Var(quad_end.1, bruker.py:3054)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,147 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,148 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index.2 != new_quad_index.5\n", - "2024-10-16 10:11:10,148 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:10,149 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,149 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:10,150 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:10,150 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,151 - numba.core.ssa - DEBUG - on stmt: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:10,152 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:10,152 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:10,153 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:10,153 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:10,154 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:10,154 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:10,155 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:10,155 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,156 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:10,158 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,158 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:10,159 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:10,159 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,160 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:10,160 - numba.core.ssa - DEBUG - replaced with: is_valid_quad_index.1 = const(bool, False)\n", - "2024-10-16 10:11:10,160 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,161 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:10,161 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,162 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:10,162 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index.1, fn=)\n", - "2024-10-16 10:11:10,163 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,163 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:10,165 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,166 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:10,166 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:10,167 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,167 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, False)\n", - "2024-10-16 10:11:10,168 - numba.core.ssa - DEBUG - replaced with: is_valid_quad_index.2 = const(bool, False)\n", - "2024-10-16 10:11:10,168 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,170 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:10,170 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,171 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:10,171 - numba.core.ssa - DEBUG - replaced with: is_valid_quad_index.3 = const(bool, True)\n", - "2024-10-16 10:11:10,172 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,172 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:10,173 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,174 - numba.core.ssa - DEBUG - on stmt: quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:10,174 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:10,175 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,176 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:10,176 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:10,177 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,177 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,178 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:10,178 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,179 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:10,179 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:10,180 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:10,180 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:10,181 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:10,181 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,182 - numba.core.ssa - DEBUG - on stmt: idx.3 = phi(incoming_values=[Var(idx, bruker.py:3072), Var(idx.4, bruker.py:3073)], incoming_blocks=[296, 462])\n", - "2024-10-16 10:11:10,182 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:10,184 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:10,185 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:10,185 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:10,185 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:10,186 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:10,186 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,187 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:10,187 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,188 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,188 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,189 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:10,189 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:10,190 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:10,192 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:10,192 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:10,193 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:10,193 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx.3, sparse_end, func=$326build_slice.16, args=(Var(idx.3, bruker.py:3073), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,194 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:10,194 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,195 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx.3, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,196 - numba.core.ssa - DEBUG - on stmt: idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:10,197 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.1, fn=)\n", - "2024-10-16 10:11:10,197 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,197 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:10,199 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,200 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:10,200 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:10,201 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,201 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx.1 < sparse_end\n", - "2024-10-16 10:11:10,202 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:10,203 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,203 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:10,204 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:10,205 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,205 - numba.core.ssa - DEBUG - on stmt: idx.5 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094)], incoming_blocks=[354, 454])\n", - "2024-10-16 10:11:10,206 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:10,206 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,207 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:10,207 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:10,208 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,209 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:10,209 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:10,210 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,210 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx.5, fn=)\n", - "2024-10-16 10:11:10,211 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:10,211 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:10,212 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,212 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:10,213 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,213 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:10,214 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,214 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,215 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:10,215 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:10,216 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:10,218 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,218 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:10,219 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,220 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,221 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:10,221 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:10,222 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:10,222 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:10,223 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,224 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:10,224 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:10,225 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,226 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:10,226 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:10,227 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,227 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:10,228 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:10,229 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,229 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:10,230 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx.5, func=$416load_method.7, args=[Var(idx.5, bruker.py:3085)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,231 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:10,231 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:10,232 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,232 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,233 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:10,233 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,234 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:10,234 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx.5, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,235 - numba.core.ssa - DEBUG - on stmt: idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:10,236 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.2, fn=)\n", - "2024-10-16 10:11:10,236 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,237 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:10,237 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,238 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:10,238 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:10,240 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,240 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx.2 < sparse_end\n", - "2024-10-16 10:11:10,241 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:10,241 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,242 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:10,242 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:10,243 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,243 - numba.core.ssa - DEBUG - on stmt: idx.4 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094), Var(idx.2, bruker.py:3094), Var(idx.1, bruker.py:3074)], incoming_blocks=[306, 430, 454, 354])\n", - "2024-10-16 10:11:10,244 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:10,244 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:10,245 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,245 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,246 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:10,246 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,247 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:10,247 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:10,247 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,248 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:10,248 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:10,249 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,249 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:10,250 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:10,250 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,251 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:10,251 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:10,252 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,252 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:10,253 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:10,253 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:10,254 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,254 - numba.core.ssa - DEBUG - on stmt: quad_end.3 = phi(incoming_values=[Var(quad_end.4, bruker.py:3052), Var(quad_end.2, bruker.py:3052), Var(quad_end.4, bruker.py:3052)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,258 - numba.core.ssa - DEBUG - on stmt: quad_index.3 = phi(incoming_values=[Var(quad_index.4, bruker.py:3055), Var(quad_index.2, bruker.py:3055), Var(quad_index.4, bruker.py:3055)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,259 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,259 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:10,260 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 260: [],\n", - " 280: [],\n", - " 286: []})\n", - "2024-10-16 10:11:10,261 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:10,261 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,262 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:10,262 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:10,263 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:10,263 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:10,264 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:10,265 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:10,266 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:10,266 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:10,267 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:10,267 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:10,268 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:10,268 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:10,269 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:10,269 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:10,270 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:10,270 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:10,271 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:10,271 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:10,271 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:10,272 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:10,272 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:10,273 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:10,273 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,274 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:10,274 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:10,277 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,278 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:10,278 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:10,278 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:10,279 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,279 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:10,280 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:10,280 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,281 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:10,281 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:10,282 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:10,282 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:10,283 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,283 - numba.core.ssa - DEBUG - on stmt: quad_end.7 = phi(incoming_values=[Var(quad_end, bruker.py:3030), Var(quad_end.6, bruker.py:3052)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,284 - numba.core.ssa - DEBUG - on stmt: quad_index.7 = phi(incoming_values=[Var(quad_index, bruker.py:3028), Var(quad_index.6, bruker.py:3055)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,284 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,287 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:10,287 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:10,288 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:10,288 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:10,289 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:10,290 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:10,290 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,291 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:10,292 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,292 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,293 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,293 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:10,294 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:10,294 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:10,295 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:10,296 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:10,297 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,297 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:10,298 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:10,298 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,299 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:10,299 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,300 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:10,301 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:10,302 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:10,302 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:10,303 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,304 - numba.core.ssa - DEBUG - on stmt: quad_end.6 = phi(incoming_values=[Var(quad_end.5, bruker.py:3052), Var(quad_end.7, bruker.py:3052)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,304 - numba.core.ssa - DEBUG - on stmt: quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055), Var(quad_index.7, bruker.py:3055)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,305 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,305 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:10,306 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:10,307 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:10,308 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:10,308 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:10,309 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:10,309 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,310 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:10,311 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,311 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,312 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:10,313 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:10,313 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:10,314 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:10,314 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:10,315 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:10,316 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,316 - numba.core.ssa - DEBUG - on stmt: quad_end.5 = phi(incoming_values=[Var(quad_end.6, bruker.py:3052), Var(quad_end.2, bruker.py:3052)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,317 - numba.core.ssa - DEBUG - on stmt: quad_index.5 = phi(incoming_values=[Var(quad_index.6, bruker.py:3055), Var(quad_index.2, bruker.py:3055)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,318 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,318 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:10,319 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:10,319 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:10,320 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:10,321 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:10,321 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:10,322 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,322 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:10,323 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,323 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,325 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,325 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:10,326 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:10,326 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:10,327 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:10,327 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:10,328 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,329 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:10,329 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:10,330 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,330 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:10,331 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,331 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:10,332 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:10,332 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:10,333 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:10,333 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,334 - numba.core.ssa - DEBUG - on stmt: quad_end.2 = phi(incoming_values=[Var(quad_end.3, bruker.py:3052), Var(quad_end.5, bruker.py:3052)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,334 - numba.core.ssa - DEBUG - on stmt: quad_index.2 = phi(incoming_values=[Var(quad_index.3, bruker.py:3055), Var(quad_index.5, bruker.py:3055)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,335 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,335 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:10,336 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:10,336 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:10,341 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:10,341 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:10,342 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:10,342 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,343 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:10,343 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,344 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,345 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:10,346 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:10,346 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:10,347 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:10,347 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,348 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:10,348 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:10,349 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,349 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,350 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:10,350 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,351 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end.2 < sparse_end\n", - "2024-10-16 10:11:10,351 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:10,352 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,352 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:10,353 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:10,355 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,355 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,356 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:10,356 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,357 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:10,357 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:10,358 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:10,359 - numba.core.ssa - DEBUG - on stmt: quad_end.1 = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:10,360 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end.1 < sparse_end\n", - "2024-10-16 10:11:10,360 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:10,360 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,362 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:10,362 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:10,363 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,363 - numba.core.ssa - DEBUG - on stmt: quad_end.4 = phi(incoming_values=[Var(quad_end.2, bruker.py:3052), Var(quad_end.1, bruker.py:3054)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,364 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,364 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index.2 != new_quad_index.5\n", - "2024-10-16 10:11:10,365 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:10,365 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,366 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:10,366 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:10,367 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,367 - numba.core.ssa - DEBUG - on stmt: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:10,368 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:10,368 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:10,369 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:10,369 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:10,371 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:10,372 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:10,372 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:10,373 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,373 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:10,374 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,374 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:10,376 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:10,376 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,377 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.1 = const(bool, False)\n", - "2024-10-16 10:11:10,377 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,378 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:10,378 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,379 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:10,379 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index.1, fn=)\n", - "2024-10-16 10:11:10,380 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,380 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:10,382 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,382 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:10,383 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:10,383 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,384 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.2 = const(bool, False)\n", - "2024-10-16 10:11:10,385 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,385 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:10,386 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,387 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.3 = const(bool, True)\n", - "2024-10-16 10:11:10,387 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,388 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:10,388 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,389 - numba.core.ssa - DEBUG - on stmt: quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:10,390 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:10,390 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,391 - numba.core.ssa - DEBUG - find_def var='is_valid_quad_index' stmt=$292pred = call bool292(is_valid_quad_index, func=bool292, args=(Var(is_valid_quad_index, bruker.py:3031),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,392 - numba.core.ssa - DEBUG - find_def_from_top label 290\n", - "2024-10-16 10:11:10,392 - numba.core.ssa - DEBUG - insert phi node is_valid_quad_index.4 = phi(incoming_values=[], incoming_blocks=[]) at 290\n", - "2024-10-16 10:11:10,393 - numba.core.ssa - DEBUG - find_def_from_bottom label 280\n", - "2024-10-16 10:11:10,394 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.2 = const(bool, False)\n", - "2024-10-16 10:11:10,394 - numba.core.ssa - DEBUG - find_def_from_bottom label 220\n", - "2024-10-16 10:11:10,395 - numba.core.ssa - DEBUG - find_def_from_top label 220\n", - "2024-10-16 10:11:10,395 - numba.core.ssa - DEBUG - idom 184 from label 220\n", - "2024-10-16 10:11:10,396 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-10-16 10:11:10,396 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-10-16 10:11:10,397 - numba.core.ssa - DEBUG - idom 168 from label 184\n", - "2024-10-16 10:11:10,397 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:10,398 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:10,399 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:10,399 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:10,400 - numba.core.ssa - DEBUG - find_def_from_top label 166\n", - "2024-10-16 10:11:10,400 - numba.core.ssa - DEBUG - insert phi node is_valid_quad_index.5 = phi(incoming_values=[], incoming_blocks=[]) at 166\n", - "2024-10-16 10:11:10,401 - numba.core.ssa - DEBUG - find_def_from_bottom label 473\n", - "2024-10-16 10:11:10,401 - numba.core.ssa - DEBUG - find_def_from_top label 473\n", - "2024-10-16 10:11:10,402 - numba.core.ssa - DEBUG - insert phi node is_valid_quad_index.6 = phi(incoming_values=[], incoming_blocks=[]) at 473\n", - "2024-10-16 10:11:10,402 - numba.core.ssa - DEBUG - find_def_from_bottom label 294\n", - "2024-10-16 10:11:10,403 - numba.core.ssa - DEBUG - find_def_from_top label 294\n", - "2024-10-16 10:11:10,403 - numba.core.ssa - DEBUG - idom 290 from label 294\n", - "2024-10-16 10:11:10,404 - numba.core.ssa - DEBUG - find_def_from_bottom label 290\n", - "2024-10-16 10:11:10,404 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.4 = phi(incoming_values=[Var(is_valid_quad_index.2, bruker.py:3067)], incoming_blocks=[280])\n", - "2024-10-16 10:11:10,405 - numba.core.ssa - DEBUG - find_def_from_bottom label 182\n", - "2024-10-16 10:11:10,405 - numba.core.ssa - DEBUG - find_def_from_top label 182\n", - "2024-10-16 10:11:10,406 - numba.core.ssa - DEBUG - idom 168 from label 182\n", - "2024-10-16 10:11:10,406 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-10-16 10:11:10,408 - numba.core.ssa - DEBUG - find_def_from_top label 168\n", - "2024-10-16 10:11:10,409 - numba.core.ssa - DEBUG - idom 166 from label 168\n", - "2024-10-16 10:11:10,409 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:10,410 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.5 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:10,410 - numba.core.ssa - DEBUG - find_def_from_bottom label 464\n", - "2024-10-16 10:11:10,411 - numba.core.ssa - DEBUG - find_def_from_top label 464\n", - "2024-10-16 10:11:10,411 - numba.core.ssa - DEBUG - idom 304 from label 464\n", - "2024-10-16 10:11:10,412 - numba.core.ssa - DEBUG - find_def_from_bottom label 304\n", - "2024-10-16 10:11:10,412 - numba.core.ssa - DEBUG - find_def_from_top label 304\n", - "2024-10-16 10:11:10,413 - numba.core.ssa - DEBUG - idom 296 from label 304\n", - "2024-10-16 10:11:10,414 - numba.core.ssa - DEBUG - find_def_from_bottom label 296\n", - "2024-10-16 10:11:10,415 - numba.core.ssa - DEBUG - find_def_from_top label 296\n", - "2024-10-16 10:11:10,415 - numba.core.ssa - DEBUG - idom 290 from label 296\n", - "2024-10-16 10:11:10,416 - numba.core.ssa - DEBUG - find_def_from_bottom label 290\n", - "2024-10-16 10:11:10,416 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.4 = phi(incoming_values=[Var(is_valid_quad_index.2, bruker.py:3067)], incoming_blocks=[280])\n", - "2024-10-16 10:11:10,417 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.6 = phi(incoming_values=[Var(is_valid_quad_index.4, bruker.py:3070), Var(is_valid_quad_index.5, bruker.py:3070), Var(is_valid_quad_index.4, bruker.py:3070)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,417 - numba.core.ssa - DEBUG - find_def_from_bottom label 124\n", - "2024-10-16 10:11:10,418 - numba.core.ssa - DEBUG - find_def_from_top label 124\n", - "2024-10-16 10:11:10,418 - numba.core.ssa - DEBUG - idom 122 from label 124\n", - "2024-10-16 10:11:10,419 - numba.core.ssa - DEBUG - find_def_from_bottom label 122\n", - "2024-10-16 10:11:10,419 - numba.core.ssa - DEBUG - find_def_from_top label 122\n", - "2024-10-16 10:11:10,420 - numba.core.ssa - DEBUG - insert phi node is_valid_quad_index.7 = phi(incoming_values=[], incoming_blocks=[]) at 122\n", - "2024-10-16 10:11:10,420 - numba.core.ssa - DEBUG - find_def_from_bottom label 112\n", - "2024-10-16 10:11:10,421 - numba.core.ssa - DEBUG - find_def_from_top label 112\n", - "2024-10-16 10:11:10,421 - numba.core.ssa - DEBUG - idom 110 from label 112\n", - "2024-10-16 10:11:10,421 - numba.core.ssa - DEBUG - find_def_from_bottom label 110\n", - "2024-10-16 10:11:10,422 - numba.core.ssa - DEBUG - find_def_from_top label 110\n", - "2024-10-16 10:11:10,423 - numba.core.ssa - DEBUG - insert phi node is_valid_quad_index.8 = phi(incoming_values=[], incoming_blocks=[]) at 110\n", - "2024-10-16 10:11:10,423 - numba.core.ssa - DEBUG - find_def_from_bottom label 468\n", - "2024-10-16 10:11:10,423 - numba.core.ssa - DEBUG - find_def_from_top label 468\n", - "2024-10-16 10:11:10,424 - numba.core.ssa - DEBUG - idom 122 from label 468\n", - "2024-10-16 10:11:10,424 - numba.core.ssa - DEBUG - find_def_from_bottom label 122\n", - "2024-10-16 10:11:10,425 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.7 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-10-16 10:11:10,425 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:10,426 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-10-16 10:11:10,429 - numba.core.ssa - DEBUG - idom 66 from label 68\n", - "2024-10-16 10:11:10,429 - numba.core.ssa - DEBUG - find_def_from_bottom label 66\n", - "2024-10-16 10:11:10,430 - numba.core.ssa - DEBUG - find_def_from_top label 66\n", - "2024-10-16 10:11:10,430 - numba.core.ssa - DEBUG - insert phi node is_valid_quad_index.9 = phi(incoming_values=[], incoming_blocks=[]) at 66\n", - "2024-10-16 10:11:10,431 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:10,431 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:10,432 - numba.core.ssa - DEBUG - find_def_from_bottom label 470\n", - "2024-10-16 10:11:10,432 - numba.core.ssa - DEBUG - find_def_from_top label 470\n", - "2024-10-16 10:11:10,433 - numba.core.ssa - DEBUG - idom 110 from label 470\n", - "2024-10-16 10:11:10,433 - numba.core.ssa - DEBUG - find_def_from_bottom label 110\n", - "2024-10-16 10:11:10,434 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.8 = phi(incoming_values=[Var(is_valid_quad_index.7, bruker.py:3070)], incoming_blocks=[468])\n", - "2024-10-16 10:11:10,434 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.9 = phi(incoming_values=[Var(is_valid_quad_index, bruker.py:3031), Var(is_valid_quad_index.8, bruker.py:3070)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,435 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.8 = phi(incoming_values=[Var(is_valid_quad_index.7, bruker.py:3070), Var(is_valid_quad_index.9, bruker.py:3070)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,437 - numba.core.ssa - DEBUG - find_def_from_bottom label 466\n", - "2024-10-16 10:11:10,437 - numba.core.ssa - DEBUG - find_def_from_top label 466\n", - "2024-10-16 10:11:10,438 - numba.core.ssa - DEBUG - idom 166 from label 466\n", - "2024-10-16 10:11:10,438 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-10-16 10:11:10,439 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.5 = phi(incoming_values=[Var(is_valid_quad_index.6, bruker.py:3070)], incoming_blocks=[473])\n", - "2024-10-16 10:11:10,440 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.7 = phi(incoming_values=[Var(is_valid_quad_index.8, bruker.py:3070), Var(is_valid_quad_index.5, bruker.py:3070)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,440 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.5 = phi(incoming_values=[Var(is_valid_quad_index.6, bruker.py:3070), Var(is_valid_quad_index.7, bruker.py:3070)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,441 - numba.core.ssa - DEBUG - find_def_from_bottom label 260\n", - "2024-10-16 10:11:10,441 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.1 = const(bool, False)\n", - "2024-10-16 10:11:10,442 - numba.core.ssa - DEBUG - find_def_from_bottom label 286\n", - "2024-10-16 10:11:10,443 - numba.core.ssa - DEBUG - incoming_def is_valid_quad_index.3 = const(bool, True)\n", - "2024-10-16 10:11:10,443 - numba.core.ssa - DEBUG - replaced with: $292pred = call bool292(is_valid_quad_index.4, func=bool292, args=(Var(is_valid_quad_index.4, bruker.py:3070),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,444 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:10,444 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:10,445 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,445 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,447 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:10,447 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,447 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:10,448 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:10,448 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:10,449 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:10,449 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:10,450 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,450 - numba.core.ssa - DEBUG - on stmt: idx.3 = phi(incoming_values=[Var(idx, bruker.py:3072), Var(idx.4, bruker.py:3073)], incoming_blocks=[296, 462])\n", - "2024-10-16 10:11:10,451 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:10,451 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:10,452 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:10,452 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:10,453 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:10,453 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:10,454 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,454 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:10,455 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,455 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,456 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,456 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:10,456 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:10,457 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:10,457 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:10,458 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:10,461 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:10,462 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx.3, sparse_end, func=$326build_slice.16, args=(Var(idx.3, bruker.py:3073), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,462 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:10,463 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,463 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx.3, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,464 - numba.core.ssa - DEBUG - on stmt: idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:10,464 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.1, fn=)\n", - "2024-10-16 10:11:10,466 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,466 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:10,467 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,467 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:10,468 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:10,468 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,469 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx.1 < sparse_end\n", - "2024-10-16 10:11:10,469 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:10,469 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,470 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:10,472 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:10,472 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,473 - numba.core.ssa - DEBUG - on stmt: idx.5 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094)], incoming_blocks=[354, 454])\n", - "2024-10-16 10:11:10,473 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:10,474 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,474 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:10,475 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:10,475 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,476 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:10,476 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:10,477 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,477 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx.5, fn=)\n", - "2024-10-16 10:11:10,478 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:10,478 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:10,479 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,479 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:10,480 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,480 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:10,481 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,481 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,482 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:10,482 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:10,485 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:10,486 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,488 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:10,488 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,489 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,490 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:10,490 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:10,491 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:10,492 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:10,492 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,493 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:10,494 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:10,494 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,495 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:10,495 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:10,496 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,497 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:10,497 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:10,498 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,499 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:10,499 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx.5, func=$416load_method.7, args=[Var(idx.5, bruker.py:3085)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,500 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:10,500 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:10,501 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,502 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,503 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:10,503 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,504 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:10,504 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx.5, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,505 - numba.core.ssa - DEBUG - on stmt: idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:10,506 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.2, fn=)\n", - "2024-10-16 10:11:10,506 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,507 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:10,508 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,508 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:10,509 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:10,509 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,510 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx.2 < sparse_end\n", - "2024-10-16 10:11:10,511 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:10,511 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,512 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:10,513 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:10,513 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,514 - numba.core.ssa - DEBUG - on stmt: idx.4 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094), Var(idx.2, bruker.py:3094), Var(idx.1, bruker.py:3074)], incoming_blocks=[306, 430, 454, 354])\n", - "2024-10-16 10:11:10,515 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:10,516 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:10,516 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,516 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,517 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:10,517 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,518 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:10,518 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:10,519 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,519 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:10,520 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:10,520 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,521 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:10,521 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:10,522 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,522 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:10,523 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:10,523 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,524 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:10,524 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:10,525 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:10,525 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,526 - numba.core.ssa - DEBUG - on stmt: quad_end.3 = phi(incoming_values=[Var(quad_end.4, bruker.py:3052), Var(quad_end.2, bruker.py:3052), Var(quad_end.4, bruker.py:3052)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,526 - numba.core.ssa - DEBUG - on stmt: quad_index.3 = phi(incoming_values=[Var(quad_index.4, bruker.py:3055), Var(quad_index.2, bruker.py:3055), Var(quad_index.4, bruker.py:3055)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,529 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,530 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:10,530 - numba.core.ssa - DEBUG - Fix SSA violator on var tof_value\n", - "2024-10-16 10:11:10,531 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:10,531 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,532 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:10,532 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:10,534 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:10,534 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:10,535 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:10,535 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:10,536 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:10,536 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:10,537 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:10,537 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:10,538 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:10,538 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:10,539 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:10,540 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:10,541 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:10,541 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:10,542 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:10,542 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:10,542 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:10,543 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:10,543 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:10,544 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:10,545 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,546 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:10,546 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:10,547 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,547 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:10,548 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:10,548 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:10,550 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,550 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:10,551 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:10,551 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,552 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:10,552 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:10,553 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:10,554 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:10,555 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,555 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.9 = phi(incoming_values=[Var(is_valid_quad_index, bruker.py:3031), Var(is_valid_quad_index.8, bruker.py:3070)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,556 - numba.core.ssa - DEBUG - on stmt: quad_end.7 = phi(incoming_values=[Var(quad_end, bruker.py:3030), Var(quad_end.6, bruker.py:3052)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,556 - numba.core.ssa - DEBUG - on stmt: quad_index.7 = phi(incoming_values=[Var(quad_index, bruker.py:3028), Var(quad_index.6, bruker.py:3055)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,557 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,557 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:10,558 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:10,559 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:10,559 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:10,560 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:10,560 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:10,561 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,561 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:10,563 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,563 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,564 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,564 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:10,565 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:10,565 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:10,566 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:10,566 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:10,567 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,567 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:10,569 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:10,569 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,570 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:10,570 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,571 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:10,571 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:10,572 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:10,573 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:10,573 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,574 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.8 = phi(incoming_values=[Var(is_valid_quad_index.7, bruker.py:3070), Var(is_valid_quad_index.9, bruker.py:3070)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,574 - numba.core.ssa - DEBUG - on stmt: quad_end.6 = phi(incoming_values=[Var(quad_end.5, bruker.py:3052), Var(quad_end.7, bruker.py:3052)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,575 - numba.core.ssa - DEBUG - on stmt: quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055), Var(quad_index.7, bruker.py:3055)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,575 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,576 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:10,576 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:10,577 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:10,577 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:10,579 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:10,579 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:10,580 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,580 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:10,581 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,581 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,582 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:10,582 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:10,583 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:10,583 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:10,584 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:10,584 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:10,585 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,587 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.7 = phi(incoming_values=[Var(is_valid_quad_index.8, bruker.py:3070), Var(is_valid_quad_index.5, bruker.py:3070)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,587 - numba.core.ssa - DEBUG - on stmt: quad_end.5 = phi(incoming_values=[Var(quad_end.6, bruker.py:3052), Var(quad_end.2, bruker.py:3052)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,588 - numba.core.ssa - DEBUG - on stmt: quad_index.5 = phi(incoming_values=[Var(quad_index.6, bruker.py:3055), Var(quad_index.2, bruker.py:3055)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,588 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,589 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:10,590 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:10,590 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:10,591 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:10,591 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:10,592 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:10,592 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,592 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:10,593 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,593 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,594 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,594 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:10,595 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:10,595 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:10,596 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:10,596 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:10,597 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,597 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:10,598 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:10,598 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,599 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:10,599 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,600 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:10,600 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:10,601 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:10,601 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:10,605 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,605 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.5 = phi(incoming_values=[Var(is_valid_quad_index.6, bruker.py:3070), Var(is_valid_quad_index.7, bruker.py:3070)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,606 - numba.core.ssa - DEBUG - on stmt: quad_end.2 = phi(incoming_values=[Var(quad_end.3, bruker.py:3052), Var(quad_end.5, bruker.py:3052)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,606 - numba.core.ssa - DEBUG - on stmt: quad_index.2 = phi(incoming_values=[Var(quad_index.3, bruker.py:3055), Var(quad_index.5, bruker.py:3055)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,607 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,607 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:10,608 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:10,609 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:10,610 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:10,610 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:10,611 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:10,611 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,612 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:10,613 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,613 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,614 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:10,614 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:10,615 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:10,615 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:10,616 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,616 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:10,617 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:10,617 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,618 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,618 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:10,619 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,619 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end.2 < sparse_end\n", - "2024-10-16 10:11:10,620 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:10,620 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,621 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:10,621 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:10,622 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,622 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,625 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:10,625 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,626 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:10,626 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:10,627 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:10,627 - numba.core.ssa - DEBUG - on stmt: quad_end.1 = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:10,628 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end.1 < sparse_end\n", - "2024-10-16 10:11:10,629 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:10,629 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,630 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:10,630 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:10,631 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,632 - numba.core.ssa - DEBUG - on stmt: quad_end.4 = phi(incoming_values=[Var(quad_end.2, bruker.py:3052), Var(quad_end.1, bruker.py:3054)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,633 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,633 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index.2 != new_quad_index.5\n", - "2024-10-16 10:11:10,634 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:10,635 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,635 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:10,636 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:10,637 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,637 - numba.core.ssa - DEBUG - on stmt: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:10,637 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:10,638 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:10,638 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:10,640 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:10,640 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:10,641 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:10,641 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:10,642 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,642 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:10,643 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,643 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:10,644 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:10,644 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,646 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.1 = const(bool, False)\n", - "2024-10-16 10:11:10,646 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,647 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:10,647 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,648 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:10,649 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index.1, fn=)\n", - "2024-10-16 10:11:10,649 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,650 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:10,651 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,651 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:10,652 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:10,653 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,653 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.2 = const(bool, False)\n", - "2024-10-16 10:11:10,653 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,654 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:10,654 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,655 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.3 = const(bool, True)\n", - "2024-10-16 10:11:10,655 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,656 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:10,656 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,657 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.4 = phi(incoming_values=[Var(is_valid_quad_index.2, bruker.py:3067), Var(is_valid_quad_index.5, bruker.py:3070), Var(is_valid_quad_index.1, bruker.py:3062), Var(is_valid_quad_index.3, bruker.py:3069)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:10,659 - numba.core.ssa - DEBUG - on stmt: quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:10,659 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:10,660 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index.4, func=bool292, args=(Var(is_valid_quad_index.4, bruker.py:3070),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,660 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:10,661 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:10,661 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,662 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,662 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:10,663 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,663 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:10,665 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:10,665 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:10,666 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:10,666 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:10,667 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,668 - numba.core.ssa - DEBUG - on stmt: idx.3 = phi(incoming_values=[Var(idx, bruker.py:3072), Var(idx.4, bruker.py:3073)], incoming_blocks=[296, 462])\n", - "2024-10-16 10:11:10,668 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:10,669 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:10,669 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:10,670 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:10,670 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:10,670 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:10,671 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,671 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:10,672 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,672 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,673 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,673 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:10,675 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:10,676 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:10,676 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:10,677 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:10,678 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:10,678 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx.3, sparse_end, func=$326build_slice.16, args=(Var(idx.3, bruker.py:3073), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,679 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:10,680 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,680 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx.3, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,681 - numba.core.ssa - DEBUG - on stmt: idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:10,681 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.1, fn=)\n", - "2024-10-16 10:11:10,682 - numba.core.ssa - DEBUG - first assign: tof_value\n", - "2024-10-16 10:11:10,682 - numba.core.ssa - DEBUG - replaced with: tof_value = getitem(value=tof_indices, index=idx.1, fn=)\n", - "2024-10-16 10:11:10,683 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,683 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:10,684 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,684 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:10,686 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:10,686 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,687 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx.1 < sparse_end\n", - "2024-10-16 10:11:10,688 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:10,688 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,689 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:10,689 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:10,690 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,690 - numba.core.ssa - DEBUG - on stmt: idx.5 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094)], incoming_blocks=[354, 454])\n", - "2024-10-16 10:11:10,691 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:10,691 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,692 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:10,692 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:10,693 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,693 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:10,694 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:10,696 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,696 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx.5, fn=)\n", - "2024-10-16 10:11:10,697 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:10,697 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:10,698 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,698 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:10,699 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,700 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:10,700 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,701 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,701 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:10,702 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:10,702 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:10,703 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,704 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:10,705 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,705 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,706 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:10,706 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:10,706 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:10,707 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:10,708 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,709 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:10,709 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:10,710 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,710 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:10,711 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:10,711 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,712 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:10,712 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:10,713 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,714 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:10,715 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx.5, func=$416load_method.7, args=[Var(idx.5, bruker.py:3085)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,715 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:10,716 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:10,716 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,717 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,717 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:10,718 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,718 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:10,719 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx.5, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,719 - numba.core.ssa - DEBUG - on stmt: idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:10,720 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.2, fn=)\n", - "2024-10-16 10:11:10,720 - numba.core.ssa - DEBUG - replaced with: tof_value.1 = getitem(value=tof_indices, index=idx.2, fn=)\n", - "2024-10-16 10:11:10,721 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,721 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:10,722 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,724 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:10,725 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:10,725 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,725 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx.2 < sparse_end\n", - "2024-10-16 10:11:10,726 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:10,727 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,727 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:10,728 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:10,729 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,729 - numba.core.ssa - DEBUG - on stmt: idx.4 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094), Var(idx.2, bruker.py:3094), Var(idx.1, bruker.py:3074)], incoming_blocks=[306, 430, 454, 354])\n", - "2024-10-16 10:11:10,730 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:10,731 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:10,731 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,732 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,732 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:10,733 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,734 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:10,734 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:10,735 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,736 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:10,736 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:10,737 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,737 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:10,738 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:10,739 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,739 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:10,740 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:10,741 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,741 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:10,742 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:10,742 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:10,743 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,744 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.6 = phi(incoming_values=[Var(is_valid_quad_index.4, bruker.py:3070), Var(is_valid_quad_index.5, bruker.py:3070), Var(is_valid_quad_index.4, bruker.py:3070)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,744 - numba.core.ssa - DEBUG - on stmt: quad_end.3 = phi(incoming_values=[Var(quad_end.4, bruker.py:3052), Var(quad_end.2, bruker.py:3052), Var(quad_end.4, bruker.py:3052)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,745 - numba.core.ssa - DEBUG - on stmt: quad_index.3 = phi(incoming_values=[Var(quad_index.4, bruker.py:3055), Var(quad_index.2, bruker.py:3055), Var(quad_index.4, bruker.py:3055)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,746 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,746 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:10,747 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {306: [],\n", - " 430: []})\n", - "2024-10-16 10:11:10,748 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:10,748 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,749 - numba.core.ssa - DEBUG - on stmt: frame_slices = arg(0, name=frame_slices)\n", - "2024-10-16 10:11:10,750 - numba.core.ssa - DEBUG - on stmt: scan_slices = arg(1, name=scan_slices)\n", - "2024-10-16 10:11:10,750 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(2, name=precursor_slices)\n", - "2024-10-16 10:11:10,751 - numba.core.ssa - DEBUG - on stmt: tof_slices = arg(3, name=tof_slices)\n", - "2024-10-16 10:11:10,752 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(4, name=quad_slices)\n", - "2024-10-16 10:11:10,752 - numba.core.ssa - DEBUG - on stmt: intensity_slices = arg(5, name=intensity_slices)\n", - "2024-10-16 10:11:10,753 - numba.core.ssa - DEBUG - on stmt: frame_max_index = arg(6, name=frame_max_index)\n", - "2024-10-16 10:11:10,753 - numba.core.ssa - DEBUG - on stmt: scan_max_index = arg(7, name=scan_max_index)\n", - "2024-10-16 10:11:10,754 - numba.core.ssa - DEBUG - on stmt: push_indptr = arg(8, name=push_indptr)\n", - "2024-10-16 10:11:10,755 - numba.core.ssa - DEBUG - on stmt: precursor_indices = arg(9, name=precursor_indices)\n", - "2024-10-16 10:11:10,755 - numba.core.ssa - DEBUG - on stmt: quad_mz_values = arg(10, name=quad_mz_values)\n", - "2024-10-16 10:11:10,755 - numba.core.ssa - DEBUG - on stmt: quad_indptr = arg(11, name=quad_indptr)\n", - "2024-10-16 10:11:10,756 - numba.core.ssa - DEBUG - on stmt: tof_indices = arg(12, name=tof_indices)\n", - "2024-10-16 10:11:10,757 - numba.core.ssa - DEBUG - on stmt: intensities = arg(13, name=intensities)\n", - "2024-10-16 10:11:10,758 - numba.core.ssa - DEBUG - on stmt: result = build_list(items=[])\n", - "2024-10-16 10:11:10,758 - numba.core.ssa - DEBUG - on stmt: quad_index = const(int, -1)\n", - "2024-10-16 10:11:10,759 - numba.core.ssa - DEBUG - on stmt: new_quad_index = const(int, -1)\n", - "2024-10-16 10:11:10,759 - numba.core.ssa - DEBUG - on stmt: quad_end = const(int, -1)\n", - "2024-10-16 10:11:10,759 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index = const(bool, True)\n", - "2024-10-16 10:11:10,760 - numba.core.ssa - DEBUG - on stmt: $const24.6 = const(NoneType, None)\n", - "2024-10-16 10:11:10,761 - numba.core.ssa - DEBUG - on stmt: $const26.7 = const(int, -1)\n", - "2024-10-16 10:11:10,761 - numba.core.ssa - DEBUG - on stmt: $28build_slice.8 = global(slice: )\n", - "2024-10-16 10:11:10,761 - numba.core.ssa - DEBUG - on stmt: $28build_slice.9 = call $28build_slice.8($const24.6, $const26.7, func=$28build_slice.8, args=(Var($const24.6, bruker.py:3032), Var($const26.7, bruker.py:3032)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,762 - numba.core.ssa - DEBUG - on stmt: $30binary_subscr.10 = static_getitem(value=push_indptr, index=slice(None, -1, None), index_var=$28build_slice.9, fn=)\n", - "2024-10-16 10:11:10,763 - numba.core.ssa - DEBUG - on stmt: $32load_method.11 = getattr(value=$30binary_subscr.10, attr=reshape)\n", - "2024-10-16 10:11:10,763 - numba.core.ssa - DEBUG - on stmt: starts = call $32load_method.11(frame_max_index, scan_max_index, func=$32load_method.11, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,765 - numba.core.ssa - DEBUG - on stmt: $const44.16 = const(int, 1)\n", - "2024-10-16 10:11:10,765 - numba.core.ssa - DEBUG - on stmt: $const46.17 = const(NoneType, None)\n", - "2024-10-16 10:11:10,766 - numba.core.ssa - DEBUG - on stmt: $48build_slice.18 = global(slice: )\n", - "2024-10-16 10:11:10,766 - numba.core.ssa - DEBUG - on stmt: $48build_slice.19 = call $48build_slice.18($const44.16, $const46.17, func=$48build_slice.18, args=(Var($const44.16, bruker.py:3036), Var($const46.17, bruker.py:3036)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,767 - numba.core.ssa - DEBUG - on stmt: $50binary_subscr.20 = static_getitem(value=push_indptr, index=slice(1, None, None), index_var=$48build_slice.19, fn=)\n", - "2024-10-16 10:11:10,767 - numba.core.ssa - DEBUG - on stmt: $52load_method.21 = getattr(value=$50binary_subscr.20, attr=reshape)\n", - "2024-10-16 10:11:10,768 - numba.core.ssa - DEBUG - on stmt: ends = call $52load_method.21(frame_max_index, scan_max_index, func=$52load_method.21, args=[Var(frame_max_index, bruker.py:2960), Var(scan_max_index, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,768 - numba.core.ssa - DEBUG - on stmt: $64get_iter.26 = getiter(value=frame_slices)\n", - "2024-10-16 10:11:10,769 - numba.core.ssa - DEBUG - on stmt: $phi66.0 = $64get_iter.26\n", - "2024-10-16 10:11:10,769 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:10,770 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 66\n", - "2024-10-16 10:11:10,770 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,771 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.9 = phi(incoming_values=[Var(is_valid_quad_index, bruker.py:3031), Var(is_valid_quad_index.8, bruker.py:3070)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,771 - numba.core.ssa - DEBUG - on stmt: quad_end.7 = phi(incoming_values=[Var(quad_end, bruker.py:3030), Var(quad_end.6, bruker.py:3052)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,772 - numba.core.ssa - DEBUG - on stmt: quad_index.7 = phi(incoming_values=[Var(quad_index, bruker.py:3028), Var(quad_index.6, bruker.py:3055)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,772 - numba.core.ssa - DEBUG - on stmt: new_quad_index.8 = phi(incoming_values=[Var(new_quad_index, bruker.py:3029), Var(new_quad_index.7, bruker.py:3053)], incoming_blocks=[0, 470])\n", - "2024-10-16 10:11:10,776 - numba.core.ssa - DEBUG - on stmt: $66for_iter.1 = iternext(value=$phi66.0)\n", - "2024-10-16 10:11:10,776 - numba.core.ssa - DEBUG - on stmt: $66for_iter.2 = pair_first(value=$66for_iter.1)\n", - "2024-10-16 10:11:10,777 - numba.core.ssa - DEBUG - on stmt: $66for_iter.3 = pair_second(value=$66for_iter.1)\n", - "2024-10-16 10:11:10,777 - numba.core.ssa - DEBUG - on stmt: $phi68.1 = $66for_iter.2\n", - "2024-10-16 10:11:10,778 - numba.core.ssa - DEBUG - on stmt: branch $66for_iter.3, 68, 472\n", - "2024-10-16 10:11:10,778 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:10,779 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,779 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.5 = exhaust_iter(value=$phi68.1, count=3)\n", - "2024-10-16 10:11:10,780 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.2 = static_getitem(value=$68unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,780 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.3 = static_getitem(value=$68unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,781 - numba.core.ssa - DEBUG - on stmt: $68unpack_sequence.4 = static_getitem(value=$68unpack_sequence.5, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,781 - numba.core.ssa - DEBUG - on stmt: frame_start = $68unpack_sequence.2\n", - "2024-10-16 10:11:10,783 - numba.core.ssa - DEBUG - on stmt: frame_stop = $68unpack_sequence.3\n", - "2024-10-16 10:11:10,784 - numba.core.ssa - DEBUG - on stmt: frame_step = $68unpack_sequence.4\n", - "2024-10-16 10:11:10,784 - numba.core.ssa - DEBUG - on stmt: $76load_global.6 = global(zip: )\n", - "2024-10-16 10:11:10,785 - numba.core.ssa - DEBUG - on stmt: $80load_global.8 = global(slice: )\n", - "2024-10-16 10:11:10,785 - numba.core.ssa - DEBUG - on stmt: $88call_function.12 = call $80load_global.8(frame_start, frame_stop, frame_step, func=$80load_global.8, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,786 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.13 = getitem(value=starts, index=$88call_function.12, fn=)\n", - "2024-10-16 10:11:10,787 - numba.core.ssa - DEBUG - on stmt: $94load_global.15 = global(slice: )\n", - "2024-10-16 10:11:10,787 - numba.core.ssa - DEBUG - on stmt: $102call_function.19 = call $94load_global.15(frame_start, frame_stop, frame_step, func=$94load_global.15, args=[Var(frame_start, bruker.py:3040), Var(frame_stop, bruker.py:3040), Var(frame_step, bruker.py:3040)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,788 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.20 = getitem(value=ends, index=$102call_function.19, fn=)\n", - "2024-10-16 10:11:10,789 - numba.core.ssa - DEBUG - on stmt: $106call_function.21 = call $76load_global.6($90binary_subscr.13, $104binary_subscr.20, func=$76load_global.6, args=[Var($90binary_subscr.13, bruker.py:3042), Var($104binary_subscr.20, bruker.py:3043)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,790 - numba.core.ssa - DEBUG - on stmt: $108get_iter.22 = getiter(value=$106call_function.21)\n", - "2024-10-16 10:11:10,790 - numba.core.ssa - DEBUG - on stmt: $phi110.1 = $108get_iter.22\n", - "2024-10-16 10:11:10,791 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:10,791 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 110\n", - "2024-10-16 10:11:10,792 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,792 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.8 = phi(incoming_values=[Var(is_valid_quad_index.7, bruker.py:3070), Var(is_valid_quad_index.9, bruker.py:3070)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,794 - numba.core.ssa - DEBUG - on stmt: quad_end.6 = phi(incoming_values=[Var(quad_end.5, bruker.py:3052), Var(quad_end.7, bruker.py:3052)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,794 - numba.core.ssa - DEBUG - on stmt: quad_index.6 = phi(incoming_values=[Var(quad_index.5, bruker.py:3055), Var(quad_index.7, bruker.py:3055)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,795 - numba.core.ssa - DEBUG - on stmt: new_quad_index.7 = phi(incoming_values=[Var(new_quad_index.6, bruker.py:3053), Var(new_quad_index.8, bruker.py:3053)], incoming_blocks=[468, 68])\n", - "2024-10-16 10:11:10,795 - numba.core.ssa - DEBUG - on stmt: $110for_iter.2 = iternext(value=$phi110.1)\n", - "2024-10-16 10:11:10,796 - numba.core.ssa - DEBUG - on stmt: $110for_iter.3 = pair_first(value=$110for_iter.2)\n", - "2024-10-16 10:11:10,796 - numba.core.ssa - DEBUG - on stmt: $110for_iter.4 = pair_second(value=$110for_iter.2)\n", - "2024-10-16 10:11:10,797 - numba.core.ssa - DEBUG - on stmt: $phi112.2 = $110for_iter.3\n", - "2024-10-16 10:11:10,797 - numba.core.ssa - DEBUG - on stmt: branch $110for_iter.4, 112, 470\n", - "2024-10-16 10:11:10,797 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 112\n", - "2024-10-16 10:11:10,798 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,798 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.5 = exhaust_iter(value=$phi112.2, count=2)\n", - "2024-10-16 10:11:10,799 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.3 = static_getitem(value=$112unpack_sequence.5, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,799 - numba.core.ssa - DEBUG - on stmt: $112unpack_sequence.4 = static_getitem(value=$112unpack_sequence.5, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,800 - numba.core.ssa - DEBUG - on stmt: frame_start_slice = $112unpack_sequence.3\n", - "2024-10-16 10:11:10,800 - numba.core.ssa - DEBUG - on stmt: frame_end_slice = $112unpack_sequence.4\n", - "2024-10-16 10:11:10,801 - numba.core.ssa - DEBUG - on stmt: $120get_iter.7 = getiter(value=scan_slices)\n", - "2024-10-16 10:11:10,801 - numba.core.ssa - DEBUG - on stmt: $phi122.2 = $120get_iter.7\n", - "2024-10-16 10:11:10,802 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:10,802 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 122\n", - "2024-10-16 10:11:10,802 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,803 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.7 = phi(incoming_values=[Var(is_valid_quad_index.8, bruker.py:3070), Var(is_valid_quad_index.5, bruker.py:3070)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,804 - numba.core.ssa - DEBUG - on stmt: quad_end.5 = phi(incoming_values=[Var(quad_end.6, bruker.py:3052), Var(quad_end.2, bruker.py:3052)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,807 - numba.core.ssa - DEBUG - on stmt: quad_index.5 = phi(incoming_values=[Var(quad_index.6, bruker.py:3055), Var(quad_index.2, bruker.py:3055)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,807 - numba.core.ssa - DEBUG - on stmt: new_quad_index.6 = phi(incoming_values=[Var(new_quad_index.7, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053)], incoming_blocks=[112, 466])\n", - "2024-10-16 10:11:10,808 - numba.core.ssa - DEBUG - on stmt: $122for_iter.3 = iternext(value=$phi122.2)\n", - "2024-10-16 10:11:10,808 - numba.core.ssa - DEBUG - on stmt: $122for_iter.4 = pair_first(value=$122for_iter.3)\n", - "2024-10-16 10:11:10,809 - numba.core.ssa - DEBUG - on stmt: $122for_iter.5 = pair_second(value=$122for_iter.3)\n", - "2024-10-16 10:11:10,810 - numba.core.ssa - DEBUG - on stmt: $phi124.3 = $122for_iter.4\n", - "2024-10-16 10:11:10,810 - numba.core.ssa - DEBUG - on stmt: branch $122for_iter.5, 124, 468\n", - "2024-10-16 10:11:10,811 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-10-16 10:11:10,811 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,812 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.7 = exhaust_iter(value=$phi124.3, count=3)\n", - "2024-10-16 10:11:10,812 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.4 = static_getitem(value=$124unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,813 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.5 = static_getitem(value=$124unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,813 - numba.core.ssa - DEBUG - on stmt: $124unpack_sequence.6 = static_getitem(value=$124unpack_sequence.7, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,814 - numba.core.ssa - DEBUG - on stmt: scan_start = $124unpack_sequence.4\n", - "2024-10-16 10:11:10,814 - numba.core.ssa - DEBUG - on stmt: scan_stop = $124unpack_sequence.5\n", - "2024-10-16 10:11:10,815 - numba.core.ssa - DEBUG - on stmt: scan_step = $124unpack_sequence.6\n", - "2024-10-16 10:11:10,815 - numba.core.ssa - DEBUG - on stmt: $132load_global.8 = global(zip: )\n", - "2024-10-16 10:11:10,816 - numba.core.ssa - DEBUG - on stmt: $136load_global.10 = global(slice: )\n", - "2024-10-16 10:11:10,818 - numba.core.ssa - DEBUG - on stmt: $144call_function.14 = call $136load_global.10(scan_start, scan_stop, scan_step, func=$136load_global.10, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,818 - numba.core.ssa - DEBUG - on stmt: $146binary_subscr.15 = getitem(value=frame_start_slice, index=$144call_function.14, fn=)\n", - "2024-10-16 10:11:10,819 - numba.core.ssa - DEBUG - on stmt: $150load_global.17 = global(slice: )\n", - "2024-10-16 10:11:10,819 - numba.core.ssa - DEBUG - on stmt: $158call_function.21 = call $150load_global.17(scan_start, scan_stop, scan_step, func=$150load_global.17, args=[Var(scan_start, bruker.py:3045), Var(scan_stop, bruker.py:3045), Var(scan_step, bruker.py:3045)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,820 - numba.core.ssa - DEBUG - on stmt: $160binary_subscr.22 = getitem(value=frame_end_slice, index=$158call_function.21, fn=)\n", - "2024-10-16 10:11:10,820 - numba.core.ssa - DEBUG - on stmt: $162call_function.23 = call $132load_global.8($146binary_subscr.15, $160binary_subscr.22, func=$132load_global.8, args=[Var($146binary_subscr.15, bruker.py:3047), Var($160binary_subscr.22, bruker.py:3048)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,821 - numba.core.ssa - DEBUG - on stmt: $164get_iter.24 = getiter(value=$162call_function.23)\n", - "2024-10-16 10:11:10,822 - numba.core.ssa - DEBUG - on stmt: $phi166.3 = $164get_iter.24\n", - "2024-10-16 10:11:10,823 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:10,823 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-10-16 10:11:10,824 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,824 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.5 = phi(incoming_values=[Var(is_valid_quad_index.6, bruker.py:3070), Var(is_valid_quad_index.7, bruker.py:3070)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,825 - numba.core.ssa - DEBUG - on stmt: quad_end.2 = phi(incoming_values=[Var(quad_end.3, bruker.py:3052), Var(quad_end.5, bruker.py:3052)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,825 - numba.core.ssa - DEBUG - on stmt: quad_index.2 = phi(incoming_values=[Var(quad_index.3, bruker.py:3055), Var(quad_index.5, bruker.py:3055)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,826 - numba.core.ssa - DEBUG - on stmt: new_quad_index.3 = phi(incoming_values=[Var(new_quad_index.4, bruker.py:3053), Var(new_quad_index.6, bruker.py:3053)], incoming_blocks=[473, 124])\n", - "2024-10-16 10:11:10,826 - numba.core.ssa - DEBUG - on stmt: $166for_iter.4 = iternext(value=$phi166.3)\n", - "2024-10-16 10:11:10,827 - numba.core.ssa - DEBUG - on stmt: $166for_iter.5 = pair_first(value=$166for_iter.4)\n", - "2024-10-16 10:11:10,828 - numba.core.ssa - DEBUG - on stmt: $166for_iter.6 = pair_second(value=$166for_iter.4)\n", - "2024-10-16 10:11:10,829 - numba.core.ssa - DEBUG - on stmt: $phi168.4 = $166for_iter.5\n", - "2024-10-16 10:11:10,829 - numba.core.ssa - DEBUG - on stmt: branch $166for_iter.6, 168, 466\n", - "2024-10-16 10:11:10,830 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-10-16 10:11:10,831 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,831 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.7 = exhaust_iter(value=$phi168.4, count=2)\n", - "2024-10-16 10:11:10,832 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.5 = static_getitem(value=$168unpack_sequence.7, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,832 - numba.core.ssa - DEBUG - on stmt: $168unpack_sequence.6 = static_getitem(value=$168unpack_sequence.7, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,833 - numba.core.ssa - DEBUG - on stmt: sparse_start = $168unpack_sequence.5\n", - "2024-10-16 10:11:10,833 - numba.core.ssa - DEBUG - on stmt: sparse_end = $168unpack_sequence.6\n", - "2024-10-16 10:11:10,834 - numba.core.ssa - DEBUG - on stmt: $178compare_op.10 = sparse_start == sparse_end\n", - "2024-10-16 10:11:10,834 - numba.core.ssa - DEBUG - on stmt: bool180 = global(bool: )\n", - "2024-10-16 10:11:10,835 - numba.core.ssa - DEBUG - on stmt: $180pred = call bool180($178compare_op.10, func=bool180, args=(Var($178compare_op.10, bruker.py:3050),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,835 - numba.core.ssa - DEBUG - on stmt: branch $180pred, 182, 184\n", - "2024-10-16 10:11:10,836 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 182\n", - "2024-10-16 10:11:10,836 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,837 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,837 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-10-16 10:11:10,838 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,838 - numba.core.ssa - DEBUG - on stmt: $188compare_op.6 = quad_end.2 < sparse_end\n", - "2024-10-16 10:11:10,839 - numba.core.ssa - DEBUG - on stmt: bool190 = global(bool: )\n", - "2024-10-16 10:11:10,839 - numba.core.ssa - DEBUG - on stmt: $190pred = call bool190($188compare_op.6, func=bool190, args=(Var($188compare_op.6, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,839 - numba.core.ssa - DEBUG - on stmt: branch $190pred, 192, 220\n", - "2024-10-16 10:11:10,840 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 192\n", - "2024-10-16 10:11:10,840 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,844 - numba.core.ssa - DEBUG - on stmt: new_quad_index.2 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,844 - numba.core.ssa - DEBUG - on stmt: $const194.5 = const(int, 1)\n", - "2024-10-16 10:11:10,845 - numba.core.ssa - DEBUG - on stmt: $196inplace_add.6 = inplace_binop(fn=, immutable_fn=, lhs=new_quad_index.2, rhs=$const194.5, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,845 - numba.core.ssa - DEBUG - on stmt: new_quad_index.1 = $196inplace_add.6\n", - "2024-10-16 10:11:10,846 - numba.core.ssa - DEBUG - on stmt: $const204.9 = const(int, 1)\n", - "2024-10-16 10:11:10,846 - numba.core.ssa - DEBUG - on stmt: $206binary_add.10 = new_quad_index.1 + $const204.9\n", - "2024-10-16 10:11:10,847 - numba.core.ssa - DEBUG - on stmt: quad_end.1 = getitem(value=quad_indptr, index=$206binary_add.10, fn=)\n", - "2024-10-16 10:11:10,848 - numba.core.ssa - DEBUG - on stmt: $216compare_op.14 = quad_end.1 < sparse_end\n", - "2024-10-16 10:11:10,849 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-10-16 10:11:10,849 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218($216compare_op.14, func=bool218, args=(Var($216compare_op.14, bruker.py:3052),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,850 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 192, 220\n", - "2024-10-16 10:11:10,850 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-10-16 10:11:10,851 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,851 - numba.core.ssa - DEBUG - on stmt: quad_end.4 = phi(incoming_values=[Var(quad_end.2, bruker.py:3052), Var(quad_end.1, bruker.py:3054)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,852 - numba.core.ssa - DEBUG - on stmt: new_quad_index.5 = phi(incoming_values=[Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.1, bruker.py:3053)], incoming_blocks=[184, 192])\n", - "2024-10-16 10:11:10,853 - numba.core.ssa - DEBUG - on stmt: $224compare_op.6 = quad_index.2 != new_quad_index.5\n", - "2024-10-16 10:11:10,853 - numba.core.ssa - DEBUG - on stmt: bool226 = global(bool: )\n", - "2024-10-16 10:11:10,854 - numba.core.ssa - DEBUG - on stmt: $226pred = call bool226($224compare_op.6, func=bool226, args=(Var($224compare_op.6, bruker.py:3055),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,854 - numba.core.ssa - DEBUG - on stmt: branch $226pred, 228, 290\n", - "2024-10-16 10:11:10,855 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 228\n", - "2024-10-16 10:11:10,855 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,857 - numba.core.ssa - DEBUG - on stmt: quad_index.1 = new_quad_index.5\n", - "2024-10-16 10:11:10,857 - numba.core.ssa - DEBUG - on stmt: $232load_global.5 = global(valid_quad_mz_values: CPUDispatcher())\n", - "2024-10-16 10:11:10,858 - numba.core.ssa - DEBUG - on stmt: $const238.8 = const(int, 0)\n", - "2024-10-16 10:11:10,858 - numba.core.ssa - DEBUG - on stmt: $240build_tuple.9 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const238.8, bruker.py:3058)])\n", - "2024-10-16 10:11:10,859 - numba.core.ssa - DEBUG - on stmt: $242binary_subscr.10 = getitem(value=quad_mz_values, index=$240build_tuple.9, fn=)\n", - "2024-10-16 10:11:10,859 - numba.core.ssa - DEBUG - on stmt: $const248.13 = const(int, 1)\n", - "2024-10-16 10:11:10,860 - numba.core.ssa - DEBUG - on stmt: $250build_tuple.14 = build_tuple(items=[Var(quad_index.1, bruker.py:3056), Var($const248.13, bruker.py:3059)])\n", - "2024-10-16 10:11:10,860 - numba.core.ssa - DEBUG - on stmt: $252binary_subscr.15 = getitem(value=quad_mz_values, index=$250build_tuple.14, fn=)\n", - "2024-10-16 10:11:10,861 - numba.core.ssa - DEBUG - on stmt: $256call_function.17 = call $232load_global.5($242binary_subscr.10, $252binary_subscr.15, quad_slices, func=$232load_global.5, args=[Var($242binary_subscr.10, bruker.py:3058), Var($252binary_subscr.15, bruker.py:3059), Var(quad_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,861 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-10-16 10:11:10,862 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256call_function.17, func=bool258, args=(Var($256call_function.17, bruker.py:3057),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,862 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 266, 260\n", - "2024-10-16 10:11:10,863 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-10-16 10:11:10,865 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,865 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.1 = const(bool, False)\n", - "2024-10-16 10:11:10,866 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,866 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 266\n", - "2024-10-16 10:11:10,867 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,867 - numba.core.ssa - DEBUG - on stmt: $266load_global.4 = global(valid_precursor_index: CPUDispatcher())\n", - "2024-10-16 10:11:10,867 - numba.core.ssa - DEBUG - on stmt: $272binary_subscr.7 = getitem(value=precursor_indices, index=quad_index.1, fn=)\n", - "2024-10-16 10:11:10,868 - numba.core.ssa - DEBUG - on stmt: $276call_function.9 = call $266load_global.4($272binary_subscr.7, precursor_slices, func=$266load_global.4, args=[Var($272binary_subscr.7, bruker.py:3064), Var(precursor_slices, bruker.py:2960)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,869 - numba.core.ssa - DEBUG - on stmt: bool278 = global(bool: )\n", - "2024-10-16 10:11:10,869 - numba.core.ssa - DEBUG - on stmt: $278pred = call bool278($276call_function.9, func=bool278, args=(Var($276call_function.9, bruker.py:3063),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,870 - numba.core.ssa - DEBUG - on stmt: branch $278pred, 286, 280\n", - "2024-10-16 10:11:10,870 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 280\n", - "2024-10-16 10:11:10,871 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,873 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.2 = const(bool, False)\n", - "2024-10-16 10:11:10,873 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,874 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 286\n", - "2024-10-16 10:11:10,874 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,875 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.3 = const(bool, True)\n", - "2024-10-16 10:11:10,875 - numba.core.ssa - DEBUG - on stmt: jump 290\n", - "2024-10-16 10:11:10,876 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 290\n", - "2024-10-16 10:11:10,876 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,877 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.4 = phi(incoming_values=[Var(is_valid_quad_index.2, bruker.py:3067), Var(is_valid_quad_index.5, bruker.py:3070), Var(is_valid_quad_index.1, bruker.py:3062), Var(is_valid_quad_index.3, bruker.py:3069)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:10,877 - numba.core.ssa - DEBUG - on stmt: quad_index.4 = phi(incoming_values=[Var(quad_index.1, bruker.py:3056), Var(quad_index.2, bruker.py:3055), Var(quad_index.1, bruker.py:3056), Var(quad_index.1, bruker.py:3056)], incoming_blocks=[280, 220, 260, 286])\n", - "2024-10-16 10:11:10,878 - numba.core.ssa - DEBUG - on stmt: bool292 = global(bool: )\n", - "2024-10-16 10:11:10,878 - numba.core.ssa - DEBUG - on stmt: $292pred = call bool292(is_valid_quad_index.4, func=bool292, args=(Var(is_valid_quad_index.4, bruker.py:3070),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,878 - numba.core.ssa - DEBUG - on stmt: branch $292pred, 296, 294\n", - "2024-10-16 10:11:10,879 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 294\n", - "2024-10-16 10:11:10,879 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,880 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,880 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 296\n", - "2024-10-16 10:11:10,880 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,881 - numba.core.ssa - DEBUG - on stmt: idx = sparse_start\n", - "2024-10-16 10:11:10,881 - numba.core.ssa - DEBUG - on stmt: $302get_iter.6 = getiter(value=tof_slices)\n", - "2024-10-16 10:11:10,881 - numba.core.ssa - DEBUG - on stmt: $phi304.4 = $302get_iter.6\n", - "2024-10-16 10:11:10,882 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:10,882 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 304\n", - "2024-10-16 10:11:10,883 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,883 - numba.core.ssa - DEBUG - on stmt: idx.3 = phi(incoming_values=[Var(idx, bruker.py:3072), Var(idx.4, bruker.py:3073)], incoming_blocks=[296, 462])\n", - "2024-10-16 10:11:10,883 - numba.core.ssa - DEBUG - on stmt: $304for_iter.5 = iternext(value=$phi304.4)\n", - "2024-10-16 10:11:10,884 - numba.core.ssa - DEBUG - on stmt: $304for_iter.6 = pair_first(value=$304for_iter.5)\n", - "2024-10-16 10:11:10,884 - numba.core.ssa - DEBUG - on stmt: $304for_iter.7 = pair_second(value=$304for_iter.5)\n", - "2024-10-16 10:11:10,885 - numba.core.ssa - DEBUG - on stmt: $phi306.5 = $304for_iter.6\n", - "2024-10-16 10:11:10,885 - numba.core.ssa - DEBUG - on stmt: branch $304for_iter.7, 306, 464\n", - "2024-10-16 10:11:10,885 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 306\n", - "2024-10-16 10:11:10,886 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,888 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.9 = exhaust_iter(value=$phi306.5, count=3)\n", - "2024-10-16 10:11:10,888 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.6 = static_getitem(value=$306unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,888 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.7 = static_getitem(value=$306unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,889 - numba.core.ssa - DEBUG - on stmt: $306unpack_sequence.8 = static_getitem(value=$306unpack_sequence.9, index=2, index_var=None, fn=)\n", - "2024-10-16 10:11:10,889 - numba.core.ssa - DEBUG - on stmt: tof_start = $306unpack_sequence.6\n", - "2024-10-16 10:11:10,890 - numba.core.ssa - DEBUG - on stmt: tof_stop = $306unpack_sequence.7\n", - "2024-10-16 10:11:10,890 - numba.core.ssa - DEBUG - on stmt: tof_step = $306unpack_sequence.8\n", - "2024-10-16 10:11:10,891 - numba.core.ssa - DEBUG - on stmt: $316load_global.11 = global(np: )\n", - "2024-10-16 10:11:10,891 - numba.core.ssa - DEBUG - on stmt: $318load_method.12 = getattr(value=$316load_global.11, attr=searchsorted)\n", - "2024-10-16 10:11:10,891 - numba.core.ssa - DEBUG - on stmt: $326build_slice.16 = global(slice: )\n", - "2024-10-16 10:11:10,892 - numba.core.ssa - DEBUG - on stmt: $326build_slice.17 = call $326build_slice.16(idx.3, sparse_end, func=$326build_slice.16, args=(Var(idx.3, bruker.py:3073), Var(sparse_end, bruker.py:3046)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,892 - numba.core.ssa - DEBUG - on stmt: $328binary_subscr.18 = getitem(value=tof_indices, index=$326build_slice.17, fn=)\n", - "2024-10-16 10:11:10,893 - numba.core.ssa - DEBUG - on stmt: $332call_method.20 = call $318load_method.12($328binary_subscr.18, tof_start, func=$318load_method.12, args=[Var($328binary_subscr.18, bruker.py:3075), Var(tof_start, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,893 - numba.core.ssa - DEBUG - on stmt: $334inplace_add.21 = inplace_binop(fn=, immutable_fn=, lhs=idx.3, rhs=$332call_method.20, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,894 - numba.core.ssa - DEBUG - on stmt: idx.1 = $334inplace_add.21\n", - "2024-10-16 10:11:10,894 - numba.core.ssa - DEBUG - on stmt: tof_value = getitem(value=tof_indices, index=idx.1, fn=)\n", - "2024-10-16 10:11:10,894 - numba.core.ssa - DEBUG - on stmt: $350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,895 - numba.core.ssa - DEBUG - find_def var='tof_value' stmt=$350compare_op.27 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,895 - numba.core.ssa - DEBUG - on stmt: bool352 = global(bool: )\n", - "2024-10-16 10:11:10,896 - numba.core.ssa - DEBUG - on stmt: $352pred = call bool352($350compare_op.27, func=bool352, args=(Var($350compare_op.27, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,896 - numba.core.ssa - DEBUG - on stmt: branch $352pred, 354, 462\n", - "2024-10-16 10:11:10,896 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 354\n", - "2024-10-16 10:11:10,897 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,897 - numba.core.ssa - DEBUG - on stmt: $358compare_op.7 = idx.1 < sparse_end\n", - "2024-10-16 10:11:10,898 - numba.core.ssa - DEBUG - on stmt: bool360 = global(bool: )\n", - "2024-10-16 10:11:10,898 - numba.core.ssa - DEBUG - on stmt: $360pred = call bool360($358compare_op.7, func=bool360, args=(Var($358compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,899 - numba.core.ssa - DEBUG - on stmt: branch $360pred, 362, 462\n", - "2024-10-16 10:11:10,899 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 362\n", - "2024-10-16 10:11:10,899 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,900 - numba.core.ssa - DEBUG - on stmt: idx.5 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094)], incoming_blocks=[354, 454])\n", - "2024-10-16 10:11:10,900 - numba.core.ssa - DEBUG - on stmt: $364load_global.6 = global(range: )\n", - "2024-10-16 10:11:10,901 - numba.core.ssa - DEBUG - on stmt: $372call_function.10 = call $364load_global.6(tof_start, tof_stop, tof_step, func=$364load_global.6, args=[Var(tof_start, bruker.py:3073), Var(tof_stop, bruker.py:3073), Var(tof_step, bruker.py:3073)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,901 - numba.core.ssa - DEBUG - on stmt: $374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:10,901 - numba.core.ssa - DEBUG - find_def var='tof_value' stmt=$374contains_op.11 = tof_value in $372call_function.10\n", - "2024-10-16 10:11:10,902 - numba.core.ssa - DEBUG - find_def_from_top label 362\n", - "2024-10-16 10:11:10,902 - numba.core.ssa - DEBUG - insert phi node tof_value.2 = phi(incoming_values=[], incoming_blocks=[]) at 362\n", - "2024-10-16 10:11:10,903 - numba.core.ssa - DEBUG - find_def_from_bottom label 354\n", - "2024-10-16 10:11:10,903 - numba.core.ssa - DEBUG - find_def_from_top label 354\n", - "2024-10-16 10:11:10,910 - numba.core.ssa - DEBUG - idom 306 from label 354\n", - "2024-10-16 10:11:10,911 - numba.core.ssa - DEBUG - find_def_from_bottom label 306\n", - "2024-10-16 10:11:10,911 - numba.core.ssa - DEBUG - incoming_def tof_value = getitem(value=tof_indices, index=idx.1, fn=)\n", - "2024-10-16 10:11:10,912 - numba.core.ssa - DEBUG - find_def_from_bottom label 454\n", - "2024-10-16 10:11:10,912 - numba.core.ssa - DEBUG - find_def_from_top label 454\n", - "2024-10-16 10:11:10,912 - numba.core.ssa - DEBUG - idom 430 from label 454\n", - "2024-10-16 10:11:10,913 - numba.core.ssa - DEBUG - find_def_from_bottom label 430\n", - "2024-10-16 10:11:10,913 - numba.core.ssa - DEBUG - incoming_def tof_value.1 = getitem(value=tof_indices, index=idx.2, fn=)\n", - "2024-10-16 10:11:10,914 - numba.core.ssa - DEBUG - replaced with: $374contains_op.11 = tof_value.2 in $372call_function.10\n", - "2024-10-16 10:11:10,915 - numba.core.ssa - DEBUG - on stmt: bool376 = global(bool: )\n", - "2024-10-16 10:11:10,915 - numba.core.ssa - DEBUG - on stmt: $376pred = call bool376($374contains_op.11, func=bool376, args=(Var($374contains_op.11, bruker.py:3080),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,916 - numba.core.ssa - DEBUG - on stmt: branch $376pred, 378, 430\n", - "2024-10-16 10:11:10,916 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 378\n", - "2024-10-16 10:11:10,917 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,917 - numba.core.ssa - DEBUG - on stmt: intensity = getitem(value=intensities, index=idx.5, fn=)\n", - "2024-10-16 10:11:10,919 - numba.core.ssa - DEBUG - on stmt: $388get_iter.9 = getiter(value=intensity_slices)\n", - "2024-10-16 10:11:10,920 - numba.core.ssa - DEBUG - on stmt: $phi390.5 = $388get_iter.9\n", - "2024-10-16 10:11:10,920 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,921 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 390\n", - "2024-10-16 10:11:10,921 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,922 - numba.core.ssa - DEBUG - on stmt: $390for_iter.6 = iternext(value=$phi390.5)\n", - "2024-10-16 10:11:10,922 - numba.core.ssa - DEBUG - on stmt: $390for_iter.7 = pair_first(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,923 - numba.core.ssa - DEBUG - on stmt: $390for_iter.8 = pair_second(value=$390for_iter.6)\n", - "2024-10-16 10:11:10,923 - numba.core.ssa - DEBUG - on stmt: $phi392.6 = $390for_iter.7\n", - "2024-10-16 10:11:10,924 - numba.core.ssa - DEBUG - on stmt: branch $390for_iter.8, 392, 430\n", - "2024-10-16 10:11:10,924 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 392\n", - "2024-10-16 10:11:10,925 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,925 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.9 = exhaust_iter(value=$phi392.6, count=2)\n", - "2024-10-16 10:11:10,926 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.7 = static_getitem(value=$392unpack_sequence.9, index=0, index_var=None, fn=)\n", - "2024-10-16 10:11:10,926 - numba.core.ssa - DEBUG - on stmt: $392unpack_sequence.8 = static_getitem(value=$392unpack_sequence.9, index=1, index_var=None, fn=)\n", - "2024-10-16 10:11:10,927 - numba.core.ssa - DEBUG - on stmt: low_intensity = $392unpack_sequence.7\n", - "2024-10-16 10:11:10,929 - numba.core.ssa - DEBUG - on stmt: high_intensity = $392unpack_sequence.8\n", - "2024-10-16 10:11:10,929 - numba.core.ssa - DEBUG - on stmt: $402compare_op.12 = low_intensity <= intensity\n", - "2024-10-16 10:11:10,930 - numba.core.ssa - DEBUG - on stmt: bool404 = global(bool: )\n", - "2024-10-16 10:11:10,930 - numba.core.ssa - DEBUG - on stmt: $404pred = call bool404($402compare_op.12, func=bool404, args=(Var($402compare_op.12, bruker.py:3090),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,931 - numba.core.ssa - DEBUG - on stmt: branch $404pred, 406, 428\n", - "2024-10-16 10:11:10,931 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 406\n", - "2024-10-16 10:11:10,932 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,933 - numba.core.ssa - DEBUG - on stmt: $410compare_op.8 = intensity <= high_intensity\n", - "2024-10-16 10:11:10,934 - numba.core.ssa - DEBUG - on stmt: bool412 = global(bool: )\n", - "2024-10-16 10:11:10,934 - numba.core.ssa - DEBUG - on stmt: $412pred = call bool412($410compare_op.8, func=bool412, args=(Var($410compare_op.8, bruker.py:3091),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,935 - numba.core.ssa - DEBUG - on stmt: branch $412pred, 414, 428\n", - "2024-10-16 10:11:10,935 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 414\n", - "2024-10-16 10:11:10,936 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,936 - numba.core.ssa - DEBUG - on stmt: $416load_method.7 = getattr(value=result, attr=append)\n", - "2024-10-16 10:11:10,937 - numba.core.ssa - DEBUG - on stmt: $420call_method.9 = call $416load_method.7(idx.5, func=$416load_method.7, args=[Var(idx.5, bruker.py:3085)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,937 - numba.core.ssa - DEBUG - on stmt: jump 430\n", - "2024-10-16 10:11:10,938 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 428\n", - "2024-10-16 10:11:10,938 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,939 - numba.core.ssa - DEBUG - on stmt: jump 390\n", - "2024-10-16 10:11:10,939 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 430\n", - "2024-10-16 10:11:10,939 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,940 - numba.core.ssa - DEBUG - on stmt: $const432.6 = const(int, 1)\n", - "2024-10-16 10:11:10,940 - numba.core.ssa - DEBUG - on stmt: $434inplace_add.7 = inplace_binop(fn=, immutable_fn=, lhs=idx.5, rhs=$const432.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-10-16 10:11:10,941 - numba.core.ssa - DEBUG - on stmt: idx.2 = $434inplace_add.7\n", - "2024-10-16 10:11:10,941 - numba.core.ssa - DEBUG - on stmt: tof_value.1 = getitem(value=tof_indices, index=idx.2, fn=)\n", - "2024-10-16 10:11:10,942 - numba.core.ssa - DEBUG - on stmt: $450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,945 - numba.core.ssa - DEBUG - find_def var='tof_value' stmt=$450compare_op.13 = tof_value < tof_stop\n", - "2024-10-16 10:11:10,945 - numba.core.ssa - DEBUG - replaced with: $450compare_op.13 = tof_value.1 < tof_stop\n", - "2024-10-16 10:11:10,946 - numba.core.ssa - DEBUG - on stmt: bool452 = global(bool: )\n", - "2024-10-16 10:11:10,946 - numba.core.ssa - DEBUG - on stmt: $452pred = call bool452($450compare_op.13, func=bool452, args=(Var($450compare_op.13, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,947 - numba.core.ssa - DEBUG - on stmt: branch $452pred, 454, 462\n", - "2024-10-16 10:11:10,948 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 454\n", - "2024-10-16 10:11:10,948 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,949 - numba.core.ssa - DEBUG - on stmt: $458compare_op.7 = idx.2 < sparse_end\n", - "2024-10-16 10:11:10,949 - numba.core.ssa - DEBUG - on stmt: bool460 = global(bool: )\n", - "2024-10-16 10:11:10,950 - numba.core.ssa - DEBUG - on stmt: $460pred = call bool460($458compare_op.7, func=bool460, args=(Var($458compare_op.7, bruker.py:3079),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,951 - numba.core.ssa - DEBUG - on stmt: branch $460pred, 362, 462\n", - "2024-10-16 10:11:10,951 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 462\n", - "2024-10-16 10:11:10,952 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,952 - numba.core.ssa - DEBUG - on stmt: idx.4 = phi(incoming_values=[Var(idx.1, bruker.py:3074), Var(idx.2, bruker.py:3094), Var(idx.2, bruker.py:3094), Var(idx.1, bruker.py:3074)], incoming_blocks=[306, 430, 454, 354])\n", - "2024-10-16 10:11:10,953 - numba.core.ssa - DEBUG - on stmt: jump 304\n", - "2024-10-16 10:11:10,953 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 464\n", - "2024-10-16 10:11:10,954 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,954 - numba.core.ssa - DEBUG - on stmt: jump 473\n", - "2024-10-16 10:11:10,955 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 466\n", - "2024-10-16 10:11:10,955 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,956 - numba.core.ssa - DEBUG - on stmt: jump 122\n", - "2024-10-16 10:11:10,956 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 468\n", - "2024-10-16 10:11:10,958 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,959 - numba.core.ssa - DEBUG - on stmt: jump 110\n", - "2024-10-16 10:11:10,959 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 470\n", - "2024-10-16 10:11:10,959 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,960 - numba.core.ssa - DEBUG - on stmt: jump 66\n", - "2024-10-16 10:11:10,961 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 472\n", - "2024-10-16 10:11:10,961 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,962 - numba.core.ssa - DEBUG - on stmt: $472load_global.0 = global(np: )\n", - "2024-10-16 10:11:10,962 - numba.core.ssa - DEBUG - on stmt: $474load_method.1 = getattr(value=$472load_global.0, attr=array)\n", - "2024-10-16 10:11:10,964 - numba.core.ssa - DEBUG - on stmt: $478call_method.3 = call $474load_method.1(result, func=$474load_method.1, args=[Var(result, bruker.py:3027)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:10,964 - numba.core.ssa - DEBUG - on stmt: $480return_value.4 = cast(value=$478call_method.3)\n", - "2024-10-16 10:11:10,965 - numba.core.ssa - DEBUG - on stmt: return $480return_value.4\n", - "2024-10-16 10:11:10,965 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 473\n", - "2024-10-16 10:11:10,966 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:10,966 - numba.core.ssa - DEBUG - on stmt: is_valid_quad_index.6 = phi(incoming_values=[Var(is_valid_quad_index.4, bruker.py:3070), Var(is_valid_quad_index.5, bruker.py:3070), Var(is_valid_quad_index.4, bruker.py:3070)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,967 - numba.core.ssa - DEBUG - on stmt: quad_end.3 = phi(incoming_values=[Var(quad_end.4, bruker.py:3052), Var(quad_end.2, bruker.py:3052), Var(quad_end.4, bruker.py:3052)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,967 - numba.core.ssa - DEBUG - on stmt: quad_index.3 = phi(incoming_values=[Var(quad_index.4, bruker.py:3055), Var(quad_index.2, bruker.py:3055), Var(quad_index.4, bruker.py:3055)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,968 - numba.core.ssa - DEBUG - on stmt: new_quad_index.4 = phi(incoming_values=[Var(new_quad_index.5, bruker.py:3053), Var(new_quad_index.3, bruker.py:3053), Var(new_quad_index.5, bruker.py:3053)], incoming_blocks=[294, 182, 464])\n", - "2024-10-16 10:11:10,968 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-10-16 10:11:11,045 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=2884)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=2912)\n", - " 4\tLOAD_METHOD(arg=1, lineno=2912)\n", - " 6\tLOAD_FAST(arg=2, lineno=2913)\n", - " 8\tLOAD_CONST(arg=1, lineno=2913)\n", - " 10\tLOAD_CONST(arg=1, lineno=2913)\n", - " 12\tBUILD_SLICE(arg=2, lineno=2913)\n", - " 14\tLOAD_CONST(arg=2, lineno=2913)\n", - " 16\tBUILD_TUPLE(arg=2, lineno=2913)\n", - " 18\tBINARY_SUBSCR(arg=None, lineno=2913)\n", - " 20\tLOAD_METHOD(arg=2, lineno=2913)\n", - " 22\tCALL_METHOD(arg=0, lineno=2913)\n", - " 24\tLOAD_FAST(arg=1, lineno=2914)\n", - " 26\tLOAD_CONST(arg=3, lineno=2915)\n", - " 28\tCALL_METHOD(arg=3, lineno=2912)\n", - " 30\tSTORE_FAST(arg=3, lineno=2912)\n", - " 32\tLOAD_FAST(arg=3, lineno=2917)\n", - " 34\tLOAD_CONST(arg=2, lineno=2917)\n", - " 36\tCOMPARE_OP(arg=2, lineno=2917)\n", - " 38\tPOP_JUMP_IF_FALSE(arg=23, lineno=2917)\n", - " 40\tLOAD_CONST(arg=4, lineno=2918)\n", - " 42\tRETURN_VALUE(arg=None, lineno=2918)\n", - "> 44\tLOAD_FAST(arg=0, lineno=2919)\n", - " 46\tLOAD_FAST(arg=2, lineno=2919)\n", - " 48\tLOAD_FAST(arg=3, lineno=2919)\n", - " 50\tLOAD_CONST(arg=5, lineno=2919)\n", - " 52\tBINARY_SUBTRACT(arg=None, lineno=2919)\n", - " 54\tLOAD_CONST(arg=5, lineno=2919)\n", - " 56\tBUILD_TUPLE(arg=2, lineno=2919)\n", - " 58\tBINARY_SUBSCR(arg=None, lineno=2919)\n", - " 60\tCOMPARE_OP(arg=1, lineno=2919)\n", - " 62\tPOP_JUMP_IF_FALSE(arg=35, lineno=2919)\n", - " 64\tLOAD_CONST(arg=6, lineno=2920)\n", - " 66\tRETURN_VALUE(arg=None, lineno=2920)\n", - "> 68\tLOAD_CONST(arg=4, lineno=2921)\n", - " 70\tRETURN_VALUE(arg=None, lineno=2921)\n", - "2024-10-16 10:11:11,046 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:11,047 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,047 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:11,048 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=2884)\n", - "2024-10-16 10:11:11,049 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,050 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=2912)\n", - "2024-10-16 10:11:11,055 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,056 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=1, lineno=2912)\n", - "2024-10-16 10:11:11,057 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:11:11,058 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=2, lineno=2913)\n", - "2024-10-16 10:11:11,059 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:11:11,060 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_CONST(arg=1, lineno=2913)\n", - "2024-10-16 10:11:11,060 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$quad_slices6.2']\n", - "2024-10-16 10:11:11,061 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_CONST(arg=1, lineno=2913)\n", - "2024-10-16 10:11:11,062 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$quad_slices6.2', '$const8.3']\n", - "2024-10-16 10:11:11,063 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=BUILD_SLICE(arg=2, lineno=2913)\n", - "2024-10-16 10:11:11,063 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$quad_slices6.2', '$const8.3', '$const10.4']\n", - "2024-10-16 10:11:11,064 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_CONST(arg=2, lineno=2913)\n", - "2024-10-16 10:11:11,065 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$quad_slices6.2', '$12build_slice.6']\n", - "2024-10-16 10:11:11,066 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=BUILD_TUPLE(arg=2, lineno=2913)\n", - "2024-10-16 10:11:11,067 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$quad_slices6.2', '$12build_slice.6', '$const14.7']\n", - "2024-10-16 10:11:11,067 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=BINARY_SUBSCR(arg=None, lineno=2913)\n", - "2024-10-16 10:11:11,068 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$quad_slices6.2', '$16build_tuple.8']\n", - "2024-10-16 10:11:11,069 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_METHOD(arg=2, lineno=2913)\n", - "2024-10-16 10:11:11,070 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$18binary_subscr.9']\n", - "2024-10-16 10:11:11,070 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=CALL_METHOD(arg=0, lineno=2913)\n", - "2024-10-16 10:11:11,071 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$20load_method.10']\n", - "2024-10-16 10:11:11,072 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_FAST(arg=1, lineno=2914)\n", - "2024-10-16 10:11:11,073 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$22call_method.11']\n", - "2024-10-16 10:11:11,074 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_CONST(arg=3, lineno=2915)\n", - "2024-10-16 10:11:11,074 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$22call_method.11', '$high_mz_value24.12']\n", - "2024-10-16 10:11:11,075 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=CALL_METHOD(arg=3, lineno=2912)\n", - "2024-10-16 10:11:11,076 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$22call_method.11', '$high_mz_value24.12', '$const26.13']\n", - "2024-10-16 10:11:11,077 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=STORE_FAST(arg=3, lineno=2912)\n", - "2024-10-16 10:11:11,077 - numba.core.byteflow - DEBUG - stack ['$28call_method.14']\n", - "2024-10-16 10:11:11,078 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_FAST(arg=3, lineno=2917)\n", - "2024-10-16 10:11:11,079 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,080 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_CONST(arg=2, lineno=2917)\n", - "2024-10-16 10:11:11,081 - numba.core.byteflow - DEBUG - stack ['$slice_index32.15']\n", - "2024-10-16 10:11:11,081 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=COMPARE_OP(arg=2, lineno=2917)\n", - "2024-10-16 10:11:11,082 - numba.core.byteflow - DEBUG - stack ['$slice_index32.15', '$const34.16']\n", - "2024-10-16 10:11:11,083 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=POP_JUMP_IF_FALSE(arg=23, lineno=2917)\n", - "2024-10-16 10:11:11,084 - numba.core.byteflow - DEBUG - stack ['$36compare_op.17']\n", - "2024-10-16 10:11:11,084 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=40, stack=(), blockstack=(), npush=0), Edge(pc=44, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,085 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=40 nstack_initial=0), State(pc_initial=44 nstack_initial=0)])\n", - "2024-10-16 10:11:11,086 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,087 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=40 nstack_initial=0)\n", - "2024-10-16 10:11:11,088 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_CONST(arg=4, lineno=2918)\n", - "2024-10-16 10:11:11,089 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,089 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=RETURN_VALUE(arg=None, lineno=2918)\n", - "2024-10-16 10:11:11,090 - numba.core.byteflow - DEBUG - stack ['$const40.0']\n", - "2024-10-16 10:11:11,091 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:11,092 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=44 nstack_initial=0)])\n", - "2024-10-16 10:11:11,092 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,093 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=44 nstack_initial=0)\n", - "2024-10-16 10:11:11,094 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=LOAD_FAST(arg=0, lineno=2919)\n", - "2024-10-16 10:11:11,095 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,095 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=2, lineno=2919)\n", - "2024-10-16 10:11:11,096 - numba.core.byteflow - DEBUG - stack ['$low_mz_value44.0']\n", - "2024-10-16 10:11:11,097 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_FAST(arg=3, lineno=2919)\n", - "2024-10-16 10:11:11,098 - numba.core.byteflow - DEBUG - stack ['$low_mz_value44.0', '$quad_slices46.1']\n", - "2024-10-16 10:11:11,107 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_CONST(arg=5, lineno=2919)\n", - "2024-10-16 10:11:11,107 - numba.core.byteflow - DEBUG - stack ['$low_mz_value44.0', '$quad_slices46.1', '$slice_index48.2']\n", - "2024-10-16 10:11:11,108 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=BINARY_SUBTRACT(arg=None, lineno=2919)\n", - "2024-10-16 10:11:11,108 - numba.core.byteflow - DEBUG - stack ['$low_mz_value44.0', '$quad_slices46.1', '$slice_index48.2', '$const50.3']\n", - "2024-10-16 10:11:11,109 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=LOAD_CONST(arg=5, lineno=2919)\n", - "2024-10-16 10:11:11,109 - numba.core.byteflow - DEBUG - stack ['$low_mz_value44.0', '$quad_slices46.1', '$52binary_subtract.4']\n", - "2024-10-16 10:11:11,110 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=BUILD_TUPLE(arg=2, lineno=2919)\n", - "2024-10-16 10:11:11,110 - numba.core.byteflow - DEBUG - stack ['$low_mz_value44.0', '$quad_slices46.1', '$52binary_subtract.4', '$const54.5']\n", - "2024-10-16 10:11:11,111 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=BINARY_SUBSCR(arg=None, lineno=2919)\n", - "2024-10-16 10:11:11,111 - numba.core.byteflow - DEBUG - stack ['$low_mz_value44.0', '$quad_slices46.1', '$56build_tuple.6']\n", - "2024-10-16 10:11:11,112 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=COMPARE_OP(arg=1, lineno=2919)\n", - "2024-10-16 10:11:11,112 - numba.core.byteflow - DEBUG - stack ['$low_mz_value44.0', '$58binary_subscr.7']\n", - "2024-10-16 10:11:11,113 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=POP_JUMP_IF_FALSE(arg=35, lineno=2919)\n", - "2024-10-16 10:11:11,113 - numba.core.byteflow - DEBUG - stack ['$60compare_op.8']\n", - "2024-10-16 10:11:11,114 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=64, stack=(), blockstack=(), npush=0), Edge(pc=68, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,114 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=64 nstack_initial=0), State(pc_initial=68 nstack_initial=0)])\n", - "2024-10-16 10:11:11,114 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,115 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=64 nstack_initial=0)\n", - "2024-10-16 10:11:11,115 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_CONST(arg=6, lineno=2920)\n", - "2024-10-16 10:11:11,116 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,116 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=RETURN_VALUE(arg=None, lineno=2920)\n", - "2024-10-16 10:11:11,117 - numba.core.byteflow - DEBUG - stack ['$const64.0']\n", - "2024-10-16 10:11:11,117 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:11,118 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=68 nstack_initial=0)])\n", - "2024-10-16 10:11:11,118 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,119 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=68 nstack_initial=0)\n", - "2024-10-16 10:11:11,119 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_CONST(arg=4, lineno=2921)\n", - "2024-10-16 10:11:11,120 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,123 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=RETURN_VALUE(arg=None, lineno=2921)\n", - "2024-10-16 10:11:11,124 - numba.core.byteflow - DEBUG - stack ['$const68.0']\n", - "2024-10-16 10:11:11,124 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:11,125 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:11,126 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=40 nstack_initial=0): set(),\n", - " State(pc_initial=44 nstack_initial=0): set(),\n", - " State(pc_initial=64 nstack_initial=0): set(),\n", - " State(pc_initial=68 nstack_initial=0): set()})\n", - "2024-10-16 10:11:11,126 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:11,128 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:11,128 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:11,129 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:11,129 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:11,130 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:11,130 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_method.1'}), (6, {'res': '$quad_slices6.2'}), (8, {'res': '$const8.3'}), (10, {'res': '$const10.4'}), (12, {'start': '$const8.3', 'stop': '$const10.4', 'step': None, 'res': '$12build_slice.6', 'slicevar': '$12build_slice.5'}), (14, {'res': '$const14.7'}), (16, {'items': ['$12build_slice.6', '$const14.7'], 'res': '$16build_tuple.8'}), (18, {'index': '$16build_tuple.8', 'target': '$quad_slices6.2', 'res': '$18binary_subscr.9'}), (20, {'item': '$18binary_subscr.9', 'res': '$20load_method.10'}), (22, {'func': '$20load_method.10', 'args': [], 'res': '$22call_method.11'}), (24, {'res': '$high_mz_value24.12'}), (26, {'res': '$const26.13'}), (28, {'func': '$4load_method.1', 'args': ['$22call_method.11', '$high_mz_value24.12', '$const26.13'], 'res': '$28call_method.14'}), (30, {'value': '$28call_method.14'}), (32, {'res': '$slice_index32.15'}), (34, {'res': '$const34.16'}), (36, {'lhs': '$slice_index32.15', 'rhs': '$const34.16', 'res': '$36compare_op.17'}), (38, {'pred': '$36compare_op.17'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={40: (), 44: ()})\n", - "2024-10-16 10:11:11,131 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=40 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((40, {'res': '$const40.0'}), (42, {'retval': '$const40.0', 'castval': '$42return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:11,131 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=44 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((44, {'res': '$low_mz_value44.0'}), (46, {'res': '$quad_slices46.1'}), (48, {'res': '$slice_index48.2'}), (50, {'res': '$const50.3'}), (52, {'lhs': '$slice_index48.2', 'rhs': '$const50.3', 'res': '$52binary_subtract.4'}), (54, {'res': '$const54.5'}), (56, {'items': ['$52binary_subtract.4', '$const54.5'], 'res': '$56build_tuple.6'}), (58, {'index': '$56build_tuple.6', 'target': '$quad_slices46.1', 'res': '$58binary_subscr.7'}), (60, {'lhs': '$low_mz_value44.0', 'rhs': '$58binary_subscr.7', 'res': '$60compare_op.8'}), (62, {'pred': '$60compare_op.8'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={64: (), 68: ()})\n", - "2024-10-16 10:11:11,133 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=64 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((64, {'res': '$const64.0'}), (66, {'retval': '$const64.0', 'castval': '$66return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:11,133 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=68 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((68, {'res': '$const68.0'}), (70, {'retval': '$const68.0', 'castval': '$70return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:11,137 - numba.core.interpreter - DEBUG - label 0:\n", - " low_mz_value = arg(0, name=low_mz_value) ['low_mz_value']\n", - " high_mz_value = arg(1, name=high_mz_value) ['high_mz_value']\n", - " quad_slices = arg(2, name=quad_slices) ['quad_slices']\n", - " $2load_global.0 = global(np: ) ['$2load_global.0']\n", - " $4load_method.1 = getattr(value=$2load_global.0, attr=searchsorted) ['$2load_global.0', '$4load_method.1']\n", - " $const8.3 = const(NoneType, None) ['$const8.3']\n", - " $const10.4 = const(NoneType, None) ['$const10.4']\n", - " $12build_slice.5 = global(slice: ) ['$12build_slice.5']\n", - " $12build_slice.6 = call $12build_slice.5($const8.3, $const10.4, func=$12build_slice.5, args=(Var($const8.3, bruker.py:2913), Var($const10.4, bruker.py:2913)), kws=(), vararg=None, varkwarg=None, target=None) ['$12build_slice.5', '$12build_slice.6', '$const10.4', '$const8.3']\n", - " $const14.7 = const(int, 0) ['$const14.7']\n", - " $16build_tuple.8 = build_tuple(items=[Var($12build_slice.6, bruker.py:2913), Var($const14.7, bruker.py:2913)]) ['$12build_slice.6', '$16build_tuple.8', '$const14.7']\n", - " $18binary_subscr.9 = getitem(value=quad_slices, index=$16build_tuple.8, fn=) ['$16build_tuple.8', '$18binary_subscr.9', 'quad_slices']\n", - " $20load_method.10 = getattr(value=$18binary_subscr.9, attr=ravel) ['$18binary_subscr.9', '$20load_method.10']\n", - " $22call_method.11 = call $20load_method.10(func=$20load_method.10, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$20load_method.10', '$22call_method.11']\n", - " $const26.13 = const(str, right) ['$const26.13']\n", - " slice_index = call $4load_method.1($22call_method.11, high_mz_value, $const26.13, func=$4load_method.1, args=[Var($22call_method.11, bruker.py:2913), Var(high_mz_value, bruker.py:2884), Var($const26.13, bruker.py:2915)], kws=(), vararg=None, varkwarg=None, target=None) ['$22call_method.11', '$4load_method.1', '$const26.13', 'high_mz_value', 'slice_index']\n", - " $const34.16 = const(int, 0) ['$const34.16']\n", - " $36compare_op.17 = slice_index == $const34.16 ['$36compare_op.17', '$const34.16', 'slice_index']\n", - " bool38 = global(bool: ) ['bool38']\n", - " $38pred = call bool38($36compare_op.17, func=bool38, args=(Var($36compare_op.17, bruker.py:2917),), kws=(), vararg=None, varkwarg=None, target=None) ['$36compare_op.17', '$38pred', 'bool38']\n", - " branch $38pred, 40, 44 ['$38pred']\n", - "label 40:\n", - " $const40.0 = const(bool, False) ['$const40.0']\n", - " $42return_value.1 = cast(value=$const40.0) ['$42return_value.1', '$const40.0']\n", - " return $42return_value.1 ['$42return_value.1']\n", - "label 44:\n", - " $const50.3 = const(int, 1) ['$const50.3']\n", - " $52binary_subtract.4 = slice_index - $const50.3 ['$52binary_subtract.4', '$const50.3', 'slice_index']\n", - " $const54.5 = const(int, 1) ['$const54.5']\n", - " $56build_tuple.6 = build_tuple(items=[Var($52binary_subtract.4, bruker.py:2919), Var($const54.5, bruker.py:2919)]) ['$52binary_subtract.4', '$56build_tuple.6', '$const54.5']\n", - " $58binary_subscr.7 = getitem(value=quad_slices, index=$56build_tuple.6, fn=) ['$56build_tuple.6', '$58binary_subscr.7', 'quad_slices']\n", - " $60compare_op.8 = low_mz_value <= $58binary_subscr.7 ['$58binary_subscr.7', '$60compare_op.8', 'low_mz_value']\n", - " bool62 = global(bool: ) ['bool62']\n", - " $62pred = call bool62($60compare_op.8, func=bool62, args=(Var($60compare_op.8, bruker.py:2919),), kws=(), vararg=None, varkwarg=None, target=None) ['$60compare_op.8', '$62pred', 'bool62']\n", - " branch $62pred, 64, 68 ['$62pred']\n", - "label 64:\n", - " $const64.0 = const(bool, True) ['$const64.0']\n", - " $66return_value.1 = cast(value=$const64.0) ['$66return_value.1', '$const64.0']\n", - " return $66return_value.1 ['$66return_value.1']\n", - "label 68:\n", - " $const68.0 = const(bool, False) ['$const68.0']\n", - " $70return_value.1 = cast(value=$const68.0) ['$70return_value.1', '$const68.0']\n", - " return $70return_value.1 ['$70return_value.1']\n", - "\n", - "2024-10-16 10:11:11,164 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:11,165 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,166 - numba.core.ssa - DEBUG - on stmt: low_mz_value = arg(0, name=low_mz_value)\n", - "2024-10-16 10:11:11,167 - numba.core.ssa - DEBUG - on stmt: high_mz_value = arg(1, name=high_mz_value)\n", - "2024-10-16 10:11:11,168 - numba.core.ssa - DEBUG - on stmt: quad_slices = arg(2, name=quad_slices)\n", - "2024-10-16 10:11:11,168 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:11,170 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=searchsorted)\n", - "2024-10-16 10:11:11,171 - numba.core.ssa - DEBUG - on stmt: $const8.3 = const(NoneType, None)\n", - "2024-10-16 10:11:11,171 - numba.core.ssa - DEBUG - on stmt: $const10.4 = const(NoneType, None)\n", - "2024-10-16 10:11:11,172 - numba.core.ssa - DEBUG - on stmt: $12build_slice.5 = global(slice: )\n", - "2024-10-16 10:11:11,173 - numba.core.ssa - DEBUG - on stmt: $12build_slice.6 = call $12build_slice.5($const8.3, $const10.4, func=$12build_slice.5, args=(Var($const8.3, bruker.py:2913), Var($const10.4, bruker.py:2913)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,174 - numba.core.ssa - DEBUG - on stmt: $const14.7 = const(int, 0)\n", - "2024-10-16 10:11:11,174 - numba.core.ssa - DEBUG - on stmt: $16build_tuple.8 = build_tuple(items=[Var($12build_slice.6, bruker.py:2913), Var($const14.7, bruker.py:2913)])\n", - "2024-10-16 10:11:11,175 - numba.core.ssa - DEBUG - on stmt: $18binary_subscr.9 = static_getitem(value=quad_slices, index=(slice(None, None, None), 0), index_var=$16build_tuple.8, fn=)\n", - "2024-10-16 10:11:11,176 - numba.core.ssa - DEBUG - on stmt: $20load_method.10 = getattr(value=$18binary_subscr.9, attr=ravel)\n", - "2024-10-16 10:11:11,177 - numba.core.ssa - DEBUG - on stmt: $22call_method.11 = call $20load_method.10(func=$20load_method.10, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,178 - numba.core.ssa - DEBUG - on stmt: $const26.13 = const(str, right)\n", - "2024-10-16 10:11:11,178 - numba.core.ssa - DEBUG - on stmt: slice_index = call $4load_method.1($22call_method.11, high_mz_value, $const26.13, func=$4load_method.1, args=[Var($22call_method.11, bruker.py:2913), Var(high_mz_value, bruker.py:2884), Var($const26.13, bruker.py:2915)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,179 - numba.core.ssa - DEBUG - on stmt: $const34.16 = const(int, 0)\n", - "2024-10-16 10:11:11,180 - numba.core.ssa - DEBUG - on stmt: $36compare_op.17 = slice_index == $const34.16\n", - "2024-10-16 10:11:11,181 - numba.core.ssa - DEBUG - on stmt: bool38 = global(bool: )\n", - "2024-10-16 10:11:11,181 - numba.core.ssa - DEBUG - on stmt: $38pred = call bool38($36compare_op.17, func=bool38, args=(Var($36compare_op.17, bruker.py:2917),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,182 - numba.core.ssa - DEBUG - on stmt: branch $38pred, 40, 44\n", - "2024-10-16 10:11:11,183 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 40\n", - "2024-10-16 10:11:11,184 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,188 - numba.core.ssa - DEBUG - on stmt: $const40.0 = const(bool, False)\n", - "2024-10-16 10:11:11,189 - numba.core.ssa - DEBUG - on stmt: $42return_value.1 = cast(value=$const40.0)\n", - "2024-10-16 10:11:11,190 - numba.core.ssa - DEBUG - on stmt: return $42return_value.1\n", - "2024-10-16 10:11:11,190 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 44\n", - "2024-10-16 10:11:11,192 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,193 - numba.core.ssa - DEBUG - on stmt: $const50.3 = const(int, 1)\n", - "2024-10-16 10:11:11,193 - numba.core.ssa - DEBUG - on stmt: $52binary_subtract.4 = slice_index - $const50.3\n", - "2024-10-16 10:11:11,194 - numba.core.ssa - DEBUG - on stmt: $const54.5 = const(int, 1)\n", - "2024-10-16 10:11:11,195 - numba.core.ssa - DEBUG - on stmt: $56build_tuple.6 = build_tuple(items=[Var($52binary_subtract.4, bruker.py:2919), Var($const54.5, bruker.py:2919)])\n", - "2024-10-16 10:11:11,196 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.7 = getitem(value=quad_slices, index=$56build_tuple.6, fn=)\n", - "2024-10-16 10:11:11,196 - numba.core.ssa - DEBUG - on stmt: $60compare_op.8 = low_mz_value <= $58binary_subscr.7\n", - "2024-10-16 10:11:11,197 - numba.core.ssa - DEBUG - on stmt: bool62 = global(bool: )\n", - "2024-10-16 10:11:11,198 - numba.core.ssa - DEBUG - on stmt: $62pred = call bool62($60compare_op.8, func=bool62, args=(Var($60compare_op.8, bruker.py:2919),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,199 - numba.core.ssa - DEBUG - on stmt: branch $62pred, 64, 68\n", - "2024-10-16 10:11:11,200 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 64\n", - "2024-10-16 10:11:11,200 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,201 - numba.core.ssa - DEBUG - on stmt: $const64.0 = const(bool, True)\n", - "2024-10-16 10:11:11,202 - numba.core.ssa - DEBUG - on stmt: $66return_value.1 = cast(value=$const64.0)\n", - "2024-10-16 10:11:11,203 - numba.core.ssa - DEBUG - on stmt: return $66return_value.1\n", - "2024-10-16 10:11:11,203 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 68\n", - "2024-10-16 10:11:11,204 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,205 - numba.core.ssa - DEBUG - on stmt: $const68.0 = const(bool, False)\n", - "2024-10-16 10:11:11,206 - numba.core.ssa - DEBUG - on stmt: $70return_value.1 = cast(value=$const68.0)\n", - "2024-10-16 10:11:11,206 - numba.core.ssa - DEBUG - on stmt: return $70return_value.1\n", - "2024-10-16 10:11:11,208 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12build_slice.5': [],\n", - " '$12build_slice.6': [],\n", - " '$16build_tuple.8': [],\n", - " '$18binary_subscr.9': [],\n", - " '$20load_method.10': [],\n", - " '$22call_method.11': [],\n", - " '$2load_global.0': [],\n", - " '$36compare_op.17': [],\n", - " '$38pred': [],\n", - " '$42return_value.1': [],\n", - " '$4load_method.1': [],\n", - " '$52binary_subtract.4': [],\n", - " '$56build_tuple.6': [],\n", - " '$58binary_subscr.7': [],\n", - " '$60compare_op.8': [],\n", - " '$62pred': [],\n", - " '$66return_value.1': [],\n", - " '$70return_value.1': [],\n", - " '$const10.4': [],\n", - " '$const14.7': [],\n", - " '$const26.13': [],\n", - " '$const34.16': [],\n", - " '$const40.0': [],\n", - " '$const50.3': [],\n", - " '$const54.5': [],\n", - " '$const64.0': [],\n", - " '$const68.0': [],\n", - " '$const8.3': [],\n", - " 'bool38': [],\n", - " 'bool62': [],\n", - " 'high_mz_value': [],\n", - " 'low_mz_value': [],\n", - " 'quad_slices': [],\n", - " 'slice_index': []})\n", - "2024-10-16 10:11:11,211 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:11,227 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3773)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3774)\n", - " 4\tLOAD_FAST(arg=0, lineno=3774)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=3774)\n", - " 8\tSTORE_FAST(arg=3, lineno=3774)\n", - " 10\tLOAD_DEREF(arg=0, lineno=3775)\n", - " 12\tLOAD_FAST(arg=0, lineno=3775)\n", - " 14\tLOAD_FAST(arg=1, lineno=3775)\n", - " 16\tLOAD_FAST(arg=1, lineno=3775)\n", - " 18\tLOAD_CONST(arg=1, lineno=3775)\n", - " 20\tLOAD_FAST(arg=3, lineno=3775)\n", - " 22\tLOAD_FAST(arg=3, lineno=3775)\n", - " 24\tCALL_FUNCTION(arg=6, lineno=3775)\n", - " 26\tRETURN_VALUE(arg=None, lineno=3775)\n", - "2024-10-16 10:11:11,228 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:11,229 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,229 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:11,230 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3773)\n", - "2024-10-16 10:11:11,230 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,231 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3774)\n", - "2024-10-16 10:11:11,232 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,232 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=3774)\n", - "2024-10-16 10:11:11,233 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:11:11,233 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=3774)\n", - "2024-10-16 10:11:11,234 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$a4.1']\n", - "2024-10-16 10:11:11,235 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=3, lineno=3774)\n", - "2024-10-16 10:11:11,235 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-10-16 10:11:11,236 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_DEREF(arg=0, lineno=3775)\n", - "2024-10-16 10:11:11,236 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,237 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=0, lineno=3775)\n", - "2024-10-16 10:11:11,238 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3']\n", - "2024-10-16 10:11:11,238 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-10-16 10:11:11,239 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4']\n", - "2024-10-16 10:11:11,240 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-10-16 10:11:11,240 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5']\n", - "2024-10-16 10:11:11,241 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=1, lineno=3775)\n", - "2024-10-16 10:11:11,241 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6']\n", - "2024-10-16 10:11:11,242 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-10-16 10:11:11,242 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7']\n", - "2024-10-16 10:11:11,243 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-10-16 10:11:11,243 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8']\n", - "2024-10-16 10:11:11,244 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=CALL_FUNCTION(arg=6, lineno=3775)\n", - "2024-10-16 10:11:11,244 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9']\n", - "2024-10-16 10:11:11,245 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=RETURN_VALUE(arg=None, lineno=3775)\n", - "2024-10-16 10:11:11,246 - numba.core.byteflow - DEBUG - stack ['$24call_function.10']\n", - "2024-10-16 10:11:11,246 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:11,247 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:11,247 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:11,248 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:11,248 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:11,249 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:11,251 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:11,251 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:11,252 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:11,252 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$a4.1'}), (6, {'func': '$2load_global.0', 'args': ['$a4.1'], 'res': '$6call_function.2'}), (8, {'value': '$6call_function.2'}), (10, {'res': '$10load_deref.3'}), (12, {'res': '$a12.4'}), (14, {'res': '$v14.5'}), (16, {'res': '$v16.6'}), (18, {'res': '$const18.7'}), (20, {'res': '$n20.8'}), (22, {'res': '$n22.9'}), (24, {'func': '$10load_deref.3', 'args': ['$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9'], 'res': '$24call_function.10'}), (26, {'retval': '$24call_function.10', 'castval': '$26return_value.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:11,254 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " side = arg(2, name=side) ['side']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'a', 'n']\n", - " $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f33dd9a25f0>) ['$10load_deref.3']\n", - " $const18.7 = const(int, 0) ['$const18.7']\n", - " $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_deref.3', '$24call_function.10', '$const18.7', 'a', 'n', 'n', 'v', 'v']\n", - " $26return_value.11 = cast(value=$24call_function.10) ['$24call_function.10', '$26return_value.11']\n", - " return $26return_value.11 ['$26return_value.11']\n", - "\n", - "2024-10-16 10:11:11,267 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:11,268 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,269 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:11,269 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:11,270 - numba.core.ssa - DEBUG - on stmt: side = arg(2, name=side)\n", - "2024-10-16 10:11:11,271 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-10-16 10:11:11,272 - numba.core.ssa - DEBUG - on stmt: n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,272 - numba.core.ssa - DEBUG - on stmt: $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f33dd9a25f0>)\n", - "2024-10-16 10:11:11,273 - numba.core.ssa - DEBUG - on stmt: $const18.7 = const(int, 0)\n", - "2024-10-16 10:11:11,274 - numba.core.ssa - DEBUG - on stmt: $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,275 - numba.core.ssa - DEBUG - on stmt: $26return_value.11 = cast(value=$24call_function.10)\n", - "2024-10-16 10:11:11,275 - numba.core.ssa - DEBUG - on stmt: return $26return_value.11\n", - "2024-10-16 10:11:11,276 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_deref.3': [],\n", - " '$24call_function.10': [],\n", - " '$26return_value.11': [],\n", - " '$2load_global.0': [],\n", - " '$const18.7': [],\n", - " 'a': [],\n", - " 'n': [],\n", - " 'side': [],\n", - " 'v': []})\n", - "2024-10-16 10:11:11,277 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:11,285 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3678)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3701)\n", - " 4\tLOAD_METHOD(arg=1, lineno=3701)\n", - " 6\tLOAD_FAST(arg=1, lineno=3701)\n", - " 8\tCALL_METHOD(arg=1, lineno=3701)\n", - " 10\tPOP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - " 12\tLOAD_GLOBAL(arg=2, lineno=3704)\n", - " 14\tLOAD_FAST(arg=5, lineno=3704)\n", - " 16\tLOAD_CONST(arg=1, lineno=3704)\n", - " 18\tLOAD_CONST(arg=2, lineno=3704)\n", - " 20\tCALL_FUNCTION(arg=3, lineno=3704)\n", - " 22\tGET_ITER(arg=None, lineno=3704)\n", - "> 24\tFOR_ITER(arg=15, lineno=3704)\n", - " 26\tSTORE_FAST(arg=6, lineno=3704)\n", - " 28\tLOAD_GLOBAL(arg=0, lineno=3705)\n", - " 30\tLOAD_METHOD(arg=1, lineno=3705)\n", - " 32\tLOAD_FAST(arg=0, lineno=3705)\n", - " 34\tLOAD_FAST(arg=6, lineno=3705)\n", - " 36\tLOAD_CONST(arg=3, lineno=3705)\n", - " 38\tBINARY_SUBTRACT(arg=None, lineno=3705)\n", - " 40\tBINARY_SUBSCR(arg=None, lineno=3705)\n", - " 42\tCALL_METHOD(arg=1, lineno=3705)\n", - " 44\tPOP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - " 46\tLOAD_FAST(arg=6, lineno=3706)\n", - " 48\tROT_TWO(arg=None, lineno=3706)\n", - " 50\tPOP_TOP(arg=None, lineno=3706)\n", - " 52\tRETURN_VALUE(arg=None, lineno=3706)\n", - "> 54\tJUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "> 56\tLOAD_CONST(arg=1, lineno=3707)\n", - " 58\tRETURN_VALUE(arg=None, lineno=3707)\n", - "> 60\tLOAD_FAST(arg=2, lineno=3709)\n", - " 62\tLOAD_FAST(arg=1, lineno=3709)\n", - " 64\tCOMPARE_OP(arg=0, lineno=3709)\n", - " 66\tPOP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - " 68\tLOAD_FAST(arg=5, lineno=3710)\n", - " 70\tSTORE_FAST(arg=4, lineno=3710)\n", - " 72\tJUMP_FORWARD(arg=12, lineno=3710)\n", - "> 74\tLOAD_CONST(arg=1, lineno=3712)\n", - " 76\tSTORE_FAST(arg=3, lineno=3712)\n", - " 78\tLOAD_FAST(arg=4, lineno=3713)\n", - " 80\tLOAD_FAST(arg=5, lineno=3713)\n", - " 82\tCOMPARE_OP(arg=0, lineno=3713)\n", - " 84\tPOP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - " 86\tLOAD_FAST(arg=4, lineno=3713)\n", - " 88\tLOAD_CONST(arg=3, lineno=3713)\n", - " 90\tBINARY_ADD(arg=None, lineno=3713)\n", - " 92\tJUMP_FORWARD(arg=1, lineno=3713)\n", - "> 94\tLOAD_FAST(arg=5, lineno=3713)\n", - "> 96\tSTORE_FAST(arg=4, lineno=3713)\n", - "> 98\tLOAD_FAST(arg=4, lineno=3715)\n", - " 100\tLOAD_FAST(arg=3, lineno=3715)\n", - " 102\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 104\tPOP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "> 106\tLOAD_FAST(arg=3, lineno=3716)\n", - " 108\tLOAD_FAST(arg=4, lineno=3716)\n", - " 110\tBINARY_ADD(arg=None, lineno=3716)\n", - " 112\tLOAD_CONST(arg=3, lineno=3716)\n", - " 114\tBINARY_RSHIFT(arg=None, lineno=3716)\n", - " 116\tSTORE_FAST(arg=7, lineno=3716)\n", - " 118\tLOAD_DEREF(arg=0, lineno=3717)\n", - " 120\tLOAD_FAST(arg=0, lineno=3717)\n", - " 122\tLOAD_FAST(arg=7, lineno=3717)\n", - " 124\tBINARY_SUBSCR(arg=None, lineno=3717)\n", - " 126\tLOAD_FAST(arg=1, lineno=3717)\n", - " 128\tCALL_FUNCTION(arg=2, lineno=3717)\n", - " 130\tPOP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - " 132\tLOAD_FAST(arg=7, lineno=3719)\n", - " 134\tLOAD_CONST(arg=3, lineno=3719)\n", - " 136\tBINARY_ADD(arg=None, lineno=3719)\n", - " 138\tSTORE_FAST(arg=3, lineno=3719)\n", - " 140\tJUMP_FORWARD(arg=2, lineno=3719)\n", - "> 142\tLOAD_FAST(arg=7, lineno=3722)\n", - " 144\tSTORE_FAST(arg=4, lineno=3722)\n", - "> 146\tLOAD_FAST(arg=4, lineno=3715)\n", - " 148\tLOAD_FAST(arg=3, lineno=3715)\n", - " 150\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 152\tPOP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "> 154\tLOAD_FAST(arg=3, lineno=3723)\n", - " 156\tRETURN_VALUE(arg=None, lineno=3723)\n", - "2024-10-16 10:11:11,286 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:11,287 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,287 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:11,288 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3678)\n", - "2024-10-16 10:11:11,289 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,289 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3701)\n", - "2024-10-16 10:11:11,290 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,291 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=1, lineno=3701)\n", - "2024-10-16 10:11:11,292 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:11:11,292 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=3701)\n", - "2024-10-16 10:11:11,293 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:11:11,294 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_METHOD(arg=1, lineno=3701)\n", - "2024-10-16 10:11:11,294 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$v6.2']\n", - "2024-10-16 10:11:11,295 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=POP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - "2024-10-16 10:11:11,296 - numba.core.byteflow - DEBUG - stack ['$8call_method.3']\n", - "2024-10-16 10:11:11,297 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=12, stack=(), blockstack=(), npush=0), Edge(pc=60, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,297 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=12 nstack_initial=0), State(pc_initial=60 nstack_initial=0)])\n", - "2024-10-16 10:11:11,298 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,299 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=12 nstack_initial=0)\n", - "2024-10-16 10:11:11,300 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_GLOBAL(arg=2, lineno=3704)\n", - "2024-10-16 10:11:11,300 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,301 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=5, lineno=3704)\n", - "2024-10-16 10:11:11,302 - numba.core.byteflow - DEBUG - stack ['$12load_global.0']\n", - "2024-10-16 10:11:11,302 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_CONST(arg=1, lineno=3704)\n", - "2024-10-16 10:11:11,303 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1']\n", - "2024-10-16 10:11:11,304 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=2, lineno=3704)\n", - "2024-10-16 10:11:11,312 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2']\n", - "2024-10-16 10:11:11,313 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=CALL_FUNCTION(arg=3, lineno=3704)\n", - "2024-10-16 10:11:11,313 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2', '$const18.3']\n", - "2024-10-16 10:11:11,314 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=GET_ITER(arg=None, lineno=3704)\n", - "2024-10-16 10:11:11,315 - numba.core.byteflow - DEBUG - stack ['$20call_function.4']\n", - "2024-10-16 10:11:11,315 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$22get_iter.5',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,316 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=0), State(pc_initial=24 nstack_initial=1)])\n", - "2024-10-16 10:11:11,319 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,320 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=60 nstack_initial=0)\n", - "2024-10-16 10:11:11,321 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_FAST(arg=2, lineno=3709)\n", - "2024-10-16 10:11:11,321 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,322 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_FAST(arg=1, lineno=3709)\n", - "2024-10-16 10:11:11,323 - numba.core.byteflow - DEBUG - stack ['$v_last60.0']\n", - "2024-10-16 10:11:11,324 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=COMPARE_OP(arg=0, lineno=3709)\n", - "2024-10-16 10:11:11,324 - numba.core.byteflow - DEBUG - stack ['$v_last60.0', '$v62.1']\n", - "2024-10-16 10:11:11,325 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=POP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - "2024-10-16 10:11:11,326 - numba.core.byteflow - DEBUG - stack ['$64compare_op.2']\n", - "2024-10-16 10:11:11,326 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=68, stack=(), blockstack=(), npush=0), Edge(pc=74, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,327 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0)])\n", - "2024-10-16 10:11:11,328 - numba.core.byteflow - DEBUG - stack: ['$phi24.0']\n", - "2024-10-16 10:11:11,328 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=24 nstack_initial=1)\n", - "2024-10-16 10:11:11,329 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=FOR_ITER(arg=15, lineno=3704)\n", - "2024-10-16 10:11:11,330 - numba.core.byteflow - DEBUG - stack ['$phi24.0']\n", - "2024-10-16 10:11:11,330 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=56, stack=(), blockstack=(), npush=0), Edge(pc=26, stack=('$phi24.0', '$24for_iter.2'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,331 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2)])\n", - "2024-10-16 10:11:11,332 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,336 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=68 nstack_initial=0)\n", - "2024-10-16 10:11:11,337 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_FAST(arg=5, lineno=3710)\n", - "2024-10-16 10:11:11,338 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,338 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=STORE_FAST(arg=4, lineno=3710)\n", - "2024-10-16 10:11:11,339 - numba.core.byteflow - DEBUG - stack ['$n68.0']\n", - "2024-10-16 10:11:11,340 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=JUMP_FORWARD(arg=12, lineno=3710)\n", - "2024-10-16 10:11:11,340 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,342 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,343 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:11,344 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,345 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=0)\n", - "2024-10-16 10:11:11,346 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=1, lineno=3712)\n", - "2024-10-16 10:11:11,346 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,347 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=STORE_FAST(arg=3, lineno=3712)\n", - "2024-10-16 10:11:11,348 - numba.core.byteflow - DEBUG - stack ['$const74.0']\n", - "2024-10-16 10:11:11,348 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-10-16 10:11:11,349 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,350 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-10-16 10:11:11,350 - numba.core.byteflow - DEBUG - stack ['$hi78.1']\n", - "2024-10-16 10:11:11,351 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=COMPARE_OP(arg=0, lineno=3713)\n", - "2024-10-16 10:11:11,352 - numba.core.byteflow - DEBUG - stack ['$hi78.1', '$n80.2']\n", - "2024-10-16 10:11:11,352 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=POP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - "2024-10-16 10:11:11,353 - numba.core.byteflow - DEBUG - stack ['$82compare_op.3']\n", - "2024-10-16 10:11:11,354 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=86, stack=(), blockstack=(), npush=0), Edge(pc=94, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,355 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-10-16 10:11:11,355 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,356 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=0)\n", - "2024-10-16 10:11:11,357 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_CONST(arg=1, lineno=3707)\n", - "2024-10-16 10:11:11,357 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,358 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=RETURN_VALUE(arg=None, lineno=3707)\n", - "2024-10-16 10:11:11,359 - numba.core.byteflow - DEBUG - stack ['$const56.0']\n", - "2024-10-16 10:11:11,359 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:11,360 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-10-16 10:11:11,361 - numba.core.byteflow - DEBUG - stack: ['$phi26.0', '$phi26.1']\n", - "2024-10-16 10:11:11,361 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=26 nstack_initial=2)\n", - "2024-10-16 10:11:11,362 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=STORE_FAST(arg=6, lineno=3704)\n", - "2024-10-16 10:11:11,363 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$phi26.1']\n", - "2024-10-16 10:11:11,363 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_GLOBAL(arg=0, lineno=3705)\n", - "2024-10-16 10:11:11,364 - numba.core.byteflow - DEBUG - stack ['$phi26.0']\n", - "2024-10-16 10:11:11,365 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_METHOD(arg=1, lineno=3705)\n", - "2024-10-16 10:11:11,366 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$28load_global.2']\n", - "2024-10-16 10:11:11,366 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_FAST(arg=0, lineno=3705)\n", - "2024-10-16 10:11:11,367 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3']\n", - "2024-10-16 10:11:11,368 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=6, lineno=3705)\n", - "2024-10-16 10:11:11,368 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4']\n", - "2024-10-16 10:11:11,369 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_CONST(arg=3, lineno=3705)\n", - "2024-10-16 10:11:11,370 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5']\n", - "2024-10-16 10:11:11,370 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=BINARY_SUBTRACT(arg=None, lineno=3705)\n", - "2024-10-16 10:11:11,371 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5', '$const36.6']\n", - "2024-10-16 10:11:11,372 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=BINARY_SUBSCR(arg=None, lineno=3705)\n", - "2024-10-16 10:11:11,372 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$38binary_subtract.7']\n", - "2024-10-16 10:11:11,373 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=CALL_METHOD(arg=1, lineno=3705)\n", - "2024-10-16 10:11:11,374 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$40binary_subscr.8']\n", - "2024-10-16 10:11:11,374 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - "2024-10-16 10:11:11,375 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$42call_method.9']\n", - "2024-10-16 10:11:11,376 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=('$phi26.0',), blockstack=(), npush=0), Edge(pc=54, stack=('$phi26.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,376 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1)])\n", - "2024-10-16 10:11:11,377 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,378 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=98 nstack_initial=0)\n", - "2024-10-16 10:11:11,379 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-10-16 10:11:11,379 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,380 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-10-16 10:11:11,380 - numba.core.byteflow - DEBUG - stack ['$hi98.0']\n", - "2024-10-16 10:11:11,381 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-10-16 10:11:11,382 - numba.core.byteflow - DEBUG - stack ['$hi98.0', '$lo100.1']\n", - "2024-10-16 10:11:11,382 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=POP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "2024-10-16 10:11:11,383 - numba.core.byteflow - DEBUG - stack ['$102compare_op.2']\n", - "2024-10-16 10:11:11,384 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=106, stack=(), blockstack=(), npush=0), Edge(pc=154, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,385 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0)])\n", - "2024-10-16 10:11:11,385 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,386 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=86 nstack_initial=0)\n", - "2024-10-16 10:11:11,387 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-10-16 10:11:11,387 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,388 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_CONST(arg=3, lineno=3713)\n", - "2024-10-16 10:11:11,388 - numba.core.byteflow - DEBUG - stack ['$hi86.0']\n", - "2024-10-16 10:11:11,389 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=BINARY_ADD(arg=None, lineno=3713)\n", - "2024-10-16 10:11:11,390 - numba.core.byteflow - DEBUG - stack ['$hi86.0', '$const88.1']\n", - "2024-10-16 10:11:11,390 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=JUMP_FORWARD(arg=1, lineno=3713)\n", - "2024-10-16 10:11:11,391 - numba.core.byteflow - DEBUG - stack ['$90binary_add.2']\n", - "2024-10-16 10:11:11,392 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$90binary_add.2',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,392 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1)])\n", - "2024-10-16 10:11:11,393 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,394 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=94 nstack_initial=0)\n", - "2024-10-16 10:11:11,394 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-10-16 10:11:11,395 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,396 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$n94.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,396 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-10-16 10:11:11,397 - numba.core.byteflow - DEBUG - stack: ['$phi46.0']\n", - "2024-10-16 10:11:11,398 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=1)\n", - "2024-10-16 10:11:11,398 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=6, lineno=3706)\n", - "2024-10-16 10:11:11,399 - numba.core.byteflow - DEBUG - stack ['$phi46.0']\n", - "2024-10-16 10:11:11,400 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=ROT_TWO(arg=None, lineno=3706)\n", - "2024-10-16 10:11:11,400 - numba.core.byteflow - DEBUG - stack ['$phi46.0', '$i46.1']\n", - "2024-10-16 10:11:11,401 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=POP_TOP(arg=None, lineno=3706)\n", - "2024-10-16 10:11:11,401 - numba.core.byteflow - DEBUG - stack ['$i46.1', '$phi46.0']\n", - "2024-10-16 10:11:11,402 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=RETURN_VALUE(arg=None, lineno=3706)\n", - "2024-10-16 10:11:11,403 - numba.core.byteflow - DEBUG - stack ['$i46.1']\n", - "2024-10-16 10:11:11,403 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:11,404 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-10-16 10:11:11,405 - numba.core.byteflow - DEBUG - stack: ['$phi54.0']\n", - "2024-10-16 10:11:11,405 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=1)\n", - "2024-10-16 10:11:11,406 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=JUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "2024-10-16 10:11:11,406 - numba.core.byteflow - DEBUG - stack ['$phi54.0']\n", - "2024-10-16 10:11:11,407 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$phi54.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,408 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1)])\n", - "2024-10-16 10:11:11,408 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,409 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=106 nstack_initial=0)\n", - "2024-10-16 10:11:11,409 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_FAST(arg=3, lineno=3716)\n", - "2024-10-16 10:11:11,419 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,419 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_FAST(arg=4, lineno=3716)\n", - "2024-10-16 10:11:11,420 - numba.core.byteflow - DEBUG - stack ['$lo106.0']\n", - "2024-10-16 10:11:11,420 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=BINARY_ADD(arg=None, lineno=3716)\n", - "2024-10-16 10:11:11,421 - numba.core.byteflow - DEBUG - stack ['$lo106.0', '$hi108.1']\n", - "2024-10-16 10:11:11,421 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=3, lineno=3716)\n", - "2024-10-16 10:11:11,422 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2']\n", - "2024-10-16 10:11:11,423 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BINARY_RSHIFT(arg=None, lineno=3716)\n", - "2024-10-16 10:11:11,423 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2', '$const112.3']\n", - "2024-10-16 10:11:11,424 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=STORE_FAST(arg=7, lineno=3716)\n", - "2024-10-16 10:11:11,424 - numba.core.byteflow - DEBUG - stack ['$114binary_rshift.4']\n", - "2024-10-16 10:11:11,425 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_DEREF(arg=0, lineno=3717)\n", - "2024-10-16 10:11:11,425 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,426 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=0, lineno=3717)\n", - "2024-10-16 10:11:11,426 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5']\n", - "2024-10-16 10:11:11,427 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_FAST(arg=7, lineno=3717)\n", - "2024-10-16 10:11:11,427 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6']\n", - "2024-10-16 10:11:11,428 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=BINARY_SUBSCR(arg=None, lineno=3717)\n", - "2024-10-16 10:11:11,428 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6', '$mid122.7']\n", - "2024-10-16 10:11:11,429 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_FAST(arg=1, lineno=3717)\n", - "2024-10-16 10:11:11,429 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8']\n", - "2024-10-16 10:11:11,430 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=CALL_FUNCTION(arg=2, lineno=3717)\n", - "2024-10-16 10:11:11,430 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8', '$v126.9']\n", - "2024-10-16 10:11:11,432 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=POP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - "2024-10-16 10:11:11,433 - numba.core.byteflow - DEBUG - stack ['$128call_function.10']\n", - "2024-10-16 10:11:11,433 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=132, stack=(), blockstack=(), npush=0), Edge(pc=142, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,434 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-10-16 10:11:11,434 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,435 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=154 nstack_initial=0)\n", - "2024-10-16 10:11:11,435 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_FAST(arg=3, lineno=3723)\n", - "2024-10-16 10:11:11,437 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,437 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=RETURN_VALUE(arg=None, lineno=3723)\n", - "2024-10-16 10:11:11,438 - numba.core.byteflow - DEBUG - stack ['$lo154.0']\n", - "2024-10-16 10:11:11,438 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:11,439 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-10-16 10:11:11,440 - numba.core.byteflow - DEBUG - stack: ['$phi96.0']\n", - "2024-10-16 10:11:11,440 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=96 nstack_initial=1)\n", - "2024-10-16 10:11:11,441 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=STORE_FAST(arg=4, lineno=3713)\n", - "2024-10-16 10:11:11,441 - numba.core.byteflow - DEBUG - stack ['$phi96.0']\n", - "2024-10-16 10:11:11,442 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,443 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:11,443 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:11,444 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:11,444 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,444 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=132 nstack_initial=0)\n", - "2024-10-16 10:11:11,445 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_FAST(arg=7, lineno=3719)\n", - "2024-10-16 10:11:11,446 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,447 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_CONST(arg=3, lineno=3719)\n", - "2024-10-16 10:11:11,447 - numba.core.byteflow - DEBUG - stack ['$mid132.0']\n", - "2024-10-16 10:11:11,448 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BINARY_ADD(arg=None, lineno=3719)\n", - "2024-10-16 10:11:11,448 - numba.core.byteflow - DEBUG - stack ['$mid132.0', '$const134.1']\n", - "2024-10-16 10:11:11,449 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=STORE_FAST(arg=3, lineno=3719)\n", - "2024-10-16 10:11:11,449 - numba.core.byteflow - DEBUG - stack ['$136binary_add.2']\n", - "2024-10-16 10:11:11,451 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=JUMP_FORWARD(arg=2, lineno=3719)\n", - "2024-10-16 10:11:11,451 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,452 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,452 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-10-16 10:11:11,453 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,453 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=142 nstack_initial=0)\n", - "2024-10-16 10:11:11,454 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=7, lineno=3722)\n", - "2024-10-16 10:11:11,454 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,455 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=STORE_FAST(arg=4, lineno=3722)\n", - "2024-10-16 10:11:11,455 - numba.core.byteflow - DEBUG - stack ['$mid142.0']\n", - "2024-10-16 10:11:11,456 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,456 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-10-16 10:11:11,458 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-10-16 10:11:11,458 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:11,459 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=146 nstack_initial=0)\n", - "2024-10-16 10:11:11,459 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-10-16 10:11:11,460 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:11,460 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-10-16 10:11:11,461 - numba.core.byteflow - DEBUG - stack ['$hi146.0']\n", - "2024-10-16 10:11:11,461 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-10-16 10:11:11,462 - numba.core.byteflow - DEBUG - stack ['$hi146.0', '$lo148.1']\n", - "2024-10-16 10:11:11,462 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=POP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "2024-10-16 10:11:11,463 - numba.core.byteflow - DEBUG - stack ['$150compare_op.2']\n", - "2024-10-16 10:11:11,463 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=154, stack=(), blockstack=(), npush=0), Edge(pc=106, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:11,464 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-10-16 10:11:11,466 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-10-16 10:11:11,466 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0)])\n", - "2024-10-16 10:11:11,467 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:11,467 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=12 nstack_initial=0): set(),\n", - " State(pc_initial=24 nstack_initial=1): {'$phi24.0'},\n", - " State(pc_initial=26 nstack_initial=2): {'$phi26.1'},\n", - " State(pc_initial=46 nstack_initial=1): set(),\n", - " State(pc_initial=54 nstack_initial=1): set(),\n", - " State(pc_initial=56 nstack_initial=0): set(),\n", - " State(pc_initial=60 nstack_initial=0): set(),\n", - " State(pc_initial=68 nstack_initial=0): set(),\n", - " State(pc_initial=74 nstack_initial=0): set(),\n", - " State(pc_initial=86 nstack_initial=0): set(),\n", - " State(pc_initial=94 nstack_initial=0): set(),\n", - " State(pc_initial=96 nstack_initial=1): {'$phi96.0'},\n", - " State(pc_initial=98 nstack_initial=0): set(),\n", - " State(pc_initial=106 nstack_initial=0): set(),\n", - " State(pc_initial=132 nstack_initial=0): set(),\n", - " State(pc_initial=142 nstack_initial=0): set(),\n", - " State(pc_initial=146 nstack_initial=0): set(),\n", - " State(pc_initial=154 nstack_initial=0): set()})\n", - "2024-10-16 10:11:11,469 - numba.core.byteflow - DEBUG - defmap: {'$phi24.0': State(pc_initial=12 nstack_initial=0),\n", - " '$phi26.1': State(pc_initial=24 nstack_initial=1),\n", - " '$phi96.0': State(pc_initial=86 nstack_initial=0)}\n", - "2024-10-16 10:11:11,470 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi54.0', State(pc_initial=54 nstack_initial=1))},\n", - " '$phi26.0': {('$phi24.0', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi54.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:11,471 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:11,473 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:11,474 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:11,475 - numba.core.byteflow - DEBUG - keep phismap: {'$phi24.0': {('$22get_iter.5', State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi96.0': {('$90binary_add.2', State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}}\n", - "2024-10-16 10:11:11,476 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=12 nstack_initial=0): {'$phi24.0': '$22get_iter.5'},\n", - " State(pc_initial=24 nstack_initial=1): {'$phi26.1': '$24for_iter.2'},\n", - " State(pc_initial=86 nstack_initial=0): {'$phi96.0': '$90binary_add.2'},\n", - " State(pc_initial=94 nstack_initial=0): {'$phi96.0': '$n94.0'}})\n", - "2024-10-16 10:11:11,477 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:11,477 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_method.1'}), (6, {'res': '$v6.2'}), (8, {'func': '$4load_method.1', 'args': ['$v6.2'], 'res': '$8call_method.3'}), (10, {'pred': '$8call_method.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={12: (), 60: ()})\n", - "2024-10-16 10:11:11,478 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=12 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((12, {'res': '$12load_global.0'}), (14, {'res': '$n14.1'}), (16, {'res': '$const16.2'}), (18, {'res': '$const18.3'}), (20, {'func': '$12load_global.0', 'args': ['$n14.1', '$const16.2', '$const18.3'], 'res': '$20call_function.4'}), (22, {'value': '$20call_function.4', 'res': '$22get_iter.5'})), outgoing_phis={'$phi24.0': '$22get_iter.5'}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$22get_iter.5',)})\n", - "2024-10-16 10:11:11,479 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=24 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((24, {'iterator': '$phi24.0', 'pair': '$24for_iter.1', 'indval': '$24for_iter.2', 'pred': '$24for_iter.3'}),), outgoing_phis={'$phi26.1': '$24for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={56: (), 26: ('$phi24.0', '$24for_iter.2')})\n", - "2024-10-16 10:11:11,479 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=26 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((26, {'value': '$phi26.1'}), (28, {'res': '$28load_global.2'}), (30, {'item': '$28load_global.2', 'res': '$30load_method.3'}), (32, {'res': '$a32.4'}), (34, {'res': '$i34.5'}), (36, {'res': '$const36.6'}), (38, {'lhs': '$i34.5', 'rhs': '$const36.6', 'res': '$38binary_subtract.7'}), (40, {'index': '$38binary_subtract.7', 'target': '$a32.4', 'res': '$40binary_subscr.8'}), (42, {'func': '$30load_method.3', 'args': ['$40binary_subscr.8'], 'res': '$42call_method.9'}), (44, {'pred': '$42call_method.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: ('$phi26.0',), 54: ('$phi26.0',)})\n", - "2024-10-16 10:11:11,480 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((46, {'res': '$i46.1'}), (52, {'retval': '$i46.1', 'castval': '$52return_value.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:11,480 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((54, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$phi54.0',)})\n", - "2024-10-16 10:11:11,481 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((56, {'res': '$const56.0'}), (58, {'retval': '$const56.0', 'castval': '$58return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:11,482 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=60 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((60, {'res': '$v_last60.0'}), (62, {'res': '$v62.1'}), (64, {'lhs': '$v_last60.0', 'rhs': '$v62.1', 'res': '$64compare_op.2'}), (66, {'pred': '$64compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={68: (), 74: ()})\n", - "2024-10-16 10:11:11,482 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=68 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((68, {'res': '$n68.0'}), (70, {'value': '$n68.0'}), (72, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-10-16 10:11:11,483 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((74, {'res': '$const74.0'}), (76, {'value': '$const74.0'}), (78, {'res': '$hi78.1'}), (80, {'res': '$n80.2'}), (82, {'lhs': '$hi78.1', 'rhs': '$n80.2', 'res': '$82compare_op.3'}), (84, {'pred': '$82compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={86: (), 94: ()})\n", - "2024-10-16 10:11:11,483 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=86 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((86, {'res': '$hi86.0'}), (88, {'res': '$const88.1'}), (90, {'lhs': '$hi86.0', 'rhs': '$const88.1', 'res': '$90binary_add.2'}), (92, {})), outgoing_phis={'$phi96.0': '$90binary_add.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$90binary_add.2',)})\n", - "2024-10-16 10:11:11,484 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=94 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((94, {'res': '$n94.0'}),), outgoing_phis={'$phi96.0': '$n94.0'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$n94.0',)})\n", - "2024-10-16 10:11:11,484 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=96 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((96, {'value': '$phi96.0'}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-10-16 10:11:11,485 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=98 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((98, {'res': '$hi98.0'}), (100, {'res': '$lo100.1'}), (102, {'lhs': '$hi98.0', 'rhs': '$lo100.1', 'res': '$102compare_op.2'}), (104, {'pred': '$102compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={106: (), 154: ()})\n", - "2024-10-16 10:11:11,486 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=106 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((106, {'res': '$lo106.0'}), (108, {'res': '$hi108.1'}), (110, {'lhs': '$lo106.0', 'rhs': '$hi108.1', 'res': '$110binary_add.2'}), (112, {'res': '$const112.3'}), (114, {'lhs': '$110binary_add.2', 'rhs': '$const112.3', 'res': '$114binary_rshift.4'}), (116, {'value': '$114binary_rshift.4'}), (118, {'res': '$118load_deref.5'}), (120, {'res': '$a120.6'}), (122, {'res': '$mid122.7'}), (124, {'index': '$mid122.7', 'target': '$a120.6', 'res': '$124binary_subscr.8'}), (126, {'res': '$v126.9'}), (128, {'func': '$118load_deref.5', 'args': ['$124binary_subscr.8', '$v126.9'], 'res': '$128call_function.10'}), (130, {'pred': '$128call_function.10'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={132: (), 142: ()})\n", - "2024-10-16 10:11:11,486 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=132 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((132, {'res': '$mid132.0'}), (134, {'res': '$const134.1'}), (136, {'lhs': '$mid132.0', 'rhs': '$const134.1', 'res': '$136binary_add.2'}), (138, {'value': '$136binary_add.2'}), (140, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-10-16 10:11:11,487 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=142 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((142, {'res': '$mid142.0'}), (144, {'value': '$mid142.0'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-10-16 10:11:11,487 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=146 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((146, {'res': '$hi146.0'}), (148, {'res': '$lo148.1'}), (150, {'lhs': '$hi146.0', 'rhs': '$lo148.1', 'res': '$150compare_op.2'}), (152, {'pred': '$150compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={154: (), 106: ()})\n", - "2024-10-16 10:11:11,488 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=154 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((154, {'res': '$lo154.0'}), (156, {'retval': '$lo154.0', 'castval': '$156return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:11,491 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " v_last = arg(2, name=v_last) ['v_last']\n", - " lo = arg(3, name=lo) ['lo']\n", - " hi = arg(4, name=hi) ['hi']\n", - " n = arg(5, name=n) ['n']\n", - " $2load_global.0 = global(np: ) ['$2load_global.0']\n", - " $4load_method.1 = getattr(value=$2load_global.0, attr=isnan) ['$2load_global.0', '$4load_method.1']\n", - " $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$8call_method.3', 'v']\n", - " bool10 = global(bool: ) ['bool10']\n", - " $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None) ['$10pred', '$8call_method.3', 'bool10']\n", - " branch $10pred, 12, 60 ['$10pred']\n", - "label 12:\n", - " $12load_global.0 = global(range: ) ['$12load_global.0']\n", - " $const16.2 = const(int, 0) ['$const16.2']\n", - " $const18.3 = const(int, -1) ['$const18.3']\n", - " $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_global.0', '$20call_function.4', '$const16.2', '$const18.3', 'n']\n", - " $22get_iter.5 = getiter(value=$20call_function.4) ['$20call_function.4', '$22get_iter.5']\n", - " $phi24.0 = $22get_iter.5 ['$22get_iter.5', '$phi24.0']\n", - " jump 24 []\n", - "label 24:\n", - " $24for_iter.1 = iternext(value=$phi24.0) ['$24for_iter.1', '$phi24.0']\n", - " $24for_iter.2 = pair_first(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.2']\n", - " $24for_iter.3 = pair_second(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.3']\n", - " $phi26.1 = $24for_iter.2 ['$24for_iter.2', '$phi26.1']\n", - " branch $24for_iter.3, 26, 56 ['$24for_iter.3']\n", - "label 26:\n", - " i = $phi26.1 ['$phi26.1', 'i']\n", - " $28load_global.2 = global(np: ) ['$28load_global.2']\n", - " $30load_method.3 = getattr(value=$28load_global.2, attr=isnan) ['$28load_global.2', '$30load_method.3']\n", - " $const36.6 = const(int, 1) ['$const36.6']\n", - " $38binary_subtract.7 = i - $const36.6 ['$38binary_subtract.7', '$const36.6', 'i']\n", - " $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=) ['$38binary_subtract.7', '$40binary_subscr.8', 'a']\n", - " $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None) ['$30load_method.3', '$40binary_subscr.8', '$42call_method.9']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None) ['$42call_method.9', '$44pred', 'bool44']\n", - " branch $44pred, 54, 46 ['$44pred']\n", - "label 46:\n", - " $52return_value.2 = cast(value=i) ['$52return_value.2', 'i']\n", - " return $52return_value.2 ['$52return_value.2']\n", - "label 54:\n", - " jump 24 []\n", - "label 56:\n", - " $const56.0 = const(int, 0) ['$const56.0']\n", - " $58return_value.1 = cast(value=$const56.0) ['$58return_value.1', '$const56.0']\n", - " return $58return_value.1 ['$58return_value.1']\n", - "label 60:\n", - " $64compare_op.2 = v_last < v ['$64compare_op.2', 'v', 'v_last']\n", - " bool66 = global(bool: ) ['bool66']\n", - " $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None) ['$64compare_op.2', '$66pred', 'bool66']\n", - " branch $66pred, 68, 74 ['$66pred']\n", - "label 68:\n", - " hi = n ['hi', 'n']\n", - " jump 98 []\n", - "label 74:\n", - " lo = const(int, 0) ['lo']\n", - " $82compare_op.3 = hi < n ['$82compare_op.3', 'hi', 'n']\n", - " bool84 = global(bool: ) ['bool84']\n", - " $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None) ['$82compare_op.3', '$84pred', 'bool84']\n", - " branch $84pred, 86, 94 ['$84pred']\n", - "label 86:\n", - " $const88.1 = const(int, 1) ['$const88.1']\n", - " $90binary_add.2 = hi + $const88.1 ['$90binary_add.2', '$const88.1', 'hi']\n", - " $phi96.0 = $90binary_add.2 ['$90binary_add.2', '$phi96.0']\n", - " jump 96 []\n", - "label 94:\n", - " $phi96.0 = n ['$phi96.0', 'n']\n", - " jump 96 []\n", - "label 96:\n", - " hi = $phi96.0 ['$phi96.0', 'hi']\n", - " jump 98 []\n", - "label 98:\n", - " $102compare_op.2 = hi > lo ['$102compare_op.2', 'hi', 'lo']\n", - " bool104 = global(bool: ) ['bool104']\n", - " $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$102compare_op.2', '$104pred', 'bool104']\n", - " branch $104pred, 106, 154 ['$104pred']\n", - "label 106:\n", - " $110binary_add.2 = lo + hi ['$110binary_add.2', 'hi', 'lo']\n", - " $const112.3 = const(int, 1) ['$const112.3']\n", - " mid = $110binary_add.2 >> $const112.3 ['$110binary_add.2', '$const112.3', 'mid']\n", - " $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>) ['$118load_deref.5']\n", - " $124binary_subscr.8 = getitem(value=a, index=mid, fn=) ['$124binary_subscr.8', 'a', 'mid']\n", - " $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$118load_deref.5', '$124binary_subscr.8', '$128call_function.10', 'v']\n", - " bool130 = global(bool: ) ['bool130']\n", - " $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None) ['$128call_function.10', '$130pred', 'bool130']\n", - " branch $130pred, 132, 142 ['$130pred']\n", - "label 132:\n", - " $const134.1 = const(int, 1) ['$const134.1']\n", - " lo = mid + $const134.1 ['$const134.1', 'lo', 'mid']\n", - " jump 146 []\n", - "label 142:\n", - " hi = mid ['hi', 'mid']\n", - " jump 146 []\n", - "label 146:\n", - " $150compare_op.2 = hi > lo ['$150compare_op.2', 'hi', 'lo']\n", - " bool152 = global(bool: ) ['bool152']\n", - " $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$150compare_op.2', '$152pred', 'bool152']\n", - " branch $152pred, 106, 154 ['$152pred']\n", - "label 154:\n", - " $156return_value.1 = cast(value=lo) ['$156return_value.1', 'lo']\n", - " return $156return_value.1 ['$156return_value.1']\n", - "\n", - "2024-10-16 10:11:11,508 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:11,509 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,509 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:11,510 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:11,510 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:11,511 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:11,512 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:11,512 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:11,513 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:11,513 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:11,514 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,514 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:11,515 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,515 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:11,516 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 12\n", - "2024-10-16 10:11:11,516 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,517 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:11,518 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:11,518 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:11,519 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,519 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:11,520 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:11,520 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,521 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 24\n", - "2024-10-16 10:11:11,521 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,522 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:11,522 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,523 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,523 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:11,524 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:11,525 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 26\n", - "2024-10-16 10:11:11,525 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,525 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:11,526 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:11,527 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:11,527 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:11,528 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:11,528 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:11,529 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,529 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:11,530 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,530 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:11,531 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-10-16 10:11:11,531 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,532 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:11,533 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:11,533 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-10-16 10:11:11,534 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,534 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,535 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-10-16 10:11:11,535 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,536 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:11,536 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:11,537 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:11,537 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 60\n", - "2024-10-16 10:11:11,538 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,538 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:11,546 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:11,551 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,551 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:11,552 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 68\n", - "2024-10-16 10:11:11,552 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,553 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:11,553 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,554 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-10-16 10:11:11,554 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,555 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-10-16 10:11:11,555 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:11,556 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:11,556 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,557 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:11,557 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 86\n", - "2024-10-16 10:11:11,558 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,559 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:11,559 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:11,560 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:11,560 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,561 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 94\n", - "2024-10-16 10:11:11,561 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,562 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:11,562 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,563 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 96\n", - "2024-10-16 10:11:11,563 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,564 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:11,564 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,565 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 98\n", - "2024-10-16 10:11:11,565 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,566 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:11,566 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:11,567 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,568 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:11,568 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 106\n", - "2024-10-16 10:11:11,569 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,569 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:11,570 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:11,570 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:11,571 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:11,571 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:11,572 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,572 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:11,573 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,573 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:11,574 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 132\n", - "2024-10-16 10:11:11,574 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,575 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:11,575 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-10-16 10:11:11,576 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,576 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 142\n", - "2024-10-16 10:11:11,577 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,577 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:11,578 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,578 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 146\n", - "2024-10-16 10:11:11,579 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,579 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:11,579 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:11,580 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,581 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:11,581 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 154\n", - "2024-10-16 10:11:11,582 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,582 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:11,582 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:11,584 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102compare_op.2': [],\n", - " '$104pred': [],\n", - " '$10pred': [],\n", - " '$110binary_add.2': [],\n", - " '$118load_deref.5': [],\n", - " '$124binary_subscr.8': [],\n", - " '$128call_function.10': [],\n", - " '$12load_global.0': [],\n", - " '$130pred': [],\n", - " '$150compare_op.2': [],\n", - " '$152pred': [],\n", - " '$156return_value.1': [],\n", - " '$20call_function.4': [],\n", - " '$22get_iter.5': [],\n", - " '$24for_iter.1': [],\n", - " '$24for_iter.2': [],\n", - " '$24for_iter.3': [],\n", - " '$28load_global.2': [],\n", - " '$2load_global.0': [],\n", - " '$30load_method.3': [],\n", - " '$38binary_subtract.7': [],\n", - " '$40binary_subscr.8': [],\n", - " '$42call_method.9': [],\n", - " '$44pred': [],\n", - " '$4load_method.1': [],\n", - " '$52return_value.2': [],\n", - " '$58return_value.1': [],\n", - " '$64compare_op.2': [],\n", - " '$66pred': [],\n", - " '$82compare_op.3': [],\n", - " '$84pred': [],\n", - " '$8call_method.3': [],\n", - " '$90binary_add.2': [],\n", - " '$const112.3': [],\n", - " '$const134.1': [],\n", - " '$const16.2': [],\n", - " '$const18.3': [],\n", - " '$const36.6': [],\n", - " '$const56.0': [],\n", - " '$const88.1': [],\n", - " '$phi24.0': [],\n", - " '$phi26.1': [],\n", - " '$phi96.0': [,\n", - " ],\n", - " 'a': [],\n", - " 'bool10': [],\n", - " 'bool104': [],\n", - " 'bool130': [],\n", - " 'bool152': [],\n", - " 'bool44': [],\n", - " 'bool66': [],\n", - " 'bool84': [],\n", - " 'hi': [,\n", - " ,\n", - " ,\n", - " ],\n", - " 'i': [],\n", - " 'lo': [,\n", - " ,\n", - " ],\n", - " 'mid': [],\n", - " 'n': [],\n", - " 'v': [],\n", - " 'v_last': []})\n", - "2024-10-16 10:11:11,584 - numba.core.ssa - DEBUG - SSA violators {'lo', 'hi', '$phi96.0'}\n", - "2024-10-16 10:11:11,585 - numba.core.ssa - DEBUG - Fix SSA violator on var lo\n", - "2024-10-16 10:11:11,585 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:11,586 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,586 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:11,587 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:11,587 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:11,588 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:11,588 - numba.core.ssa - DEBUG - first assign: lo\n", - "2024-10-16 10:11:11,589 - numba.core.ssa - DEBUG - replaced with: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:11,589 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:11,590 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:11,590 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:11,591 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:11,602 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,603 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:11,603 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,604 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:11,604 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:11,605 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,605 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:11,606 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:11,606 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:11,607 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,608 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:11,608 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:11,608 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,609 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:11,610 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,610 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:11,610 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,611 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,611 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:11,612 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:11,612 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:11,613 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,613 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:11,614 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:11,614 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:11,615 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:11,615 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:11,616 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:11,616 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,617 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:11,617 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,618 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:11,619 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:11,619 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,619 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:11,620 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:11,620 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:11,621 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,621 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,622 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:11,622 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,623 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:11,623 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:11,624 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:11,625 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:11,625 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,626 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:11,626 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:11,627 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,627 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:11,628 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:11,628 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,629 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:11,629 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,630 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:11,630 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,631 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-10-16 10:11:11,631 - numba.core.ssa - DEBUG - replaced with: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:11,632 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:11,632 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:11,633 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,633 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:11,634 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:11,634 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,635 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:11,635 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:11,636 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:11,636 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,637 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:11,637 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,637 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:11,638 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,638 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:11,639 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,640 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:11,640 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,640 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:11,641 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,641 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:11,642 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:11,642 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,643 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:11,644 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:11,644 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,645 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:11,645 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:11,645 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:11,646 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:11,646 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:11,647 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,647 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:11,648 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,649 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:11,649 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:11,649 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,650 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:11,650 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-10-16 10:11:11,651 - numba.core.ssa - DEBUG - replaced with: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:11,651 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,652 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:11,652 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,653 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:11,653 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,654 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:11,654 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,655 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:11,656 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:11,656 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,657 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:11,657 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:11,658 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,658 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:11,659 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:11,659 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 74: [],\n", - " 132: []})\n", - "2024-10-16 10:11:11,660 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:11,660 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,661 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:11,661 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:11,662 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:11,662 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:11,663 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:11,663 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:11,664 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:11,664 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:11,665 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,665 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:11,666 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,666 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:11,667 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:11,667 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,668 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:11,668 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:11,669 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:11,669 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,670 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:11,670 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:11,671 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,671 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:11,672 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,672 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:11,673 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,673 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,674 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:11,674 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:11,675 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:11,675 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,676 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:11,676 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:11,677 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:11,677 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:11,678 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:11,678 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:11,679 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,679 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:11,680 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,680 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:11,681 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:11,681 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,682 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:11,682 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:11,683 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:11,683 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,684 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,684 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:11,685 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,685 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:11,686 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:11,686 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:11,687 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:11,687 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,688 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:11,688 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:11,689 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,689 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:11,690 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:11,690 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,691 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:11,691 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,692 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:11,692 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,693 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:11,693 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:11,694 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:11,694 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,695 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:11,695 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:11,696 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,696 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:11,697 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:11,697 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:11,698 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,698 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:11,699 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,699 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:11,700 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,700 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:11,701 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,701 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:11,702 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,702 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:11,703 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,703 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:11,704 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:11,704 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-10-16 10:11:11,705 - numba.core.ssa - DEBUG - insert phi node lo.3 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-10-16 10:11:11,705 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-10-16 10:11:11,706 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-10-16 10:11:11,706 - numba.core.ssa - DEBUG - idom 74 from label 96\n", - "2024-10-16 10:11:11,707 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-10-16 10:11:11,707 - numba.core.ssa - DEBUG - incoming_def lo.1 = const(int, 0)\n", - "2024-10-16 10:11:11,708 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:11,708 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-10-16 10:11:11,709 - numba.core.ssa - DEBUG - idom 60 from label 68\n", - "2024-10-16 10:11:11,709 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-10-16 10:11:11,710 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-10-16 10:11:11,710 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-10-16 10:11:11,711 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:11,711 - numba.core.ssa - DEBUG - incoming_def lo = arg(3, name=lo)\n", - "2024-10-16 10:11:11,712 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:11,712 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:11,713 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,713 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:11,714 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:11,714 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,715 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:11,715 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:11,716 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-10-16 10:11:11,716 - numba.core.ssa - DEBUG - insert phi node lo.4 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-10-16 10:11:11,717 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-10-16 10:11:11,717 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:11,718 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-10-16 10:11:11,718 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-10-16 10:11:11,719 - numba.core.ssa - DEBUG - insert phi node lo.5 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-10-16 10:11:11,719 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-10-16 10:11:11,720 - numba.core.ssa - DEBUG - incoming_def lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:11,720 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-10-16 10:11:11,721 - numba.core.ssa - DEBUG - find_def_from_top label 142\n", - "2024-10-16 10:11:11,721 - numba.core.ssa - DEBUG - idom 106 from label 142\n", - "2024-10-16 10:11:11,722 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-10-16 10:11:11,722 - numba.core.ssa - DEBUG - incoming_def lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-10-16 10:11:11,723 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:11,723 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:11,724 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:11,724 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:11,725 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:11,725 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:11,726 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,726 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:11,727 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,727 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:11,728 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:11,728 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,729 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:11,729 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:11,730 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,730 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:11,731 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,731 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:11,732 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,732 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:11,733 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,733 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:11,734 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:11,734 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:11,735 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:11,735 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,736 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:11,736 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:11,737 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,737 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:11,738 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:11,738 - numba.core.ssa - DEBUG - find_def_from_top label 154\n", - "2024-10-16 10:11:11,739 - numba.core.ssa - DEBUG - insert phi node lo.6 = phi(incoming_values=[], incoming_blocks=[]) at 154\n", - "2024-10-16 10:11:11,739 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-10-16 10:11:11,740 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:11,740 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-10-16 10:11:11,741 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:11,741 - numba.core.ssa - DEBUG - replaced with: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:11,742 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:11,743 - numba.core.ssa - DEBUG - Fix SSA violator on var hi\n", - "2024-10-16 10:11:11,743 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:11,744 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,744 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:11,745 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:11,745 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:11,746 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:11,746 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:11,747 - numba.core.ssa - DEBUG - first assign: hi\n", - "2024-10-16 10:11:11,747 - numba.core.ssa - DEBUG - replaced with: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:11,748 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:11,748 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:11,749 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:11,749 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,750 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:11,750 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,751 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:11,751 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:11,752 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,752 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:11,753 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:11,753 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:11,754 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,754 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:11,755 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:11,755 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,756 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:11,756 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,757 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:11,757 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,758 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,758 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:11,759 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:11,759 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:11,760 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,760 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:11,761 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:11,761 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:11,762 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:11,762 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:11,763 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:11,763 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,764 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:11,764 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,765 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:11,765 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:11,766 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,766 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:11,767 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:11,767 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:11,768 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,768 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,769 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:11,769 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,770 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:11,770 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:11,771 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:11,771 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:11,771 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,772 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:11,773 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:11,773 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,773 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:11,774 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:11,809 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,809 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:11,810 - numba.core.ssa - DEBUG - replaced with: hi.1 = n\n", - "2024-10-16 10:11:11,810 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,811 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:11,811 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,811 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:11,812 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:11,812 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:11,813 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,813 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:11,814 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:11,814 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,815 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:11,815 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:11,816 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:11,816 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,817 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:11,817 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,820 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:11,820 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,821 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:11,821 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,822 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:11,822 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0\n", - "2024-10-16 10:11:11,823 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,823 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:11,824 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,824 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:11,825 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:11,825 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:11,826 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,826 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:11,827 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:11,827 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,829 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:11,830 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:11,830 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:11,831 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:11,831 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:11,833 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:11,833 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,834 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:11,834 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,835 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:11,835 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:11,835 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,836 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:11,836 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:11,837 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,839 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:11,839 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,840 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:11,840 - numba.core.ssa - DEBUG - replaced with: hi.3 = mid\n", - "2024-10-16 10:11:11,841 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,841 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:11,841 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,842 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:11,842 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:11,843 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:11,843 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,844 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:11,844 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:11,845 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,845 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:11,846 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:11,846 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:11,847 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 68: [],\n", - " 96: [],\n", - " 142: []})\n", - "2024-10-16 10:11:11,847 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:11,848 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,848 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:11,851 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:11,852 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:11,852 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:11,853 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:11,853 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:11,854 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:11,854 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:11,856 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,856 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:11,857 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,857 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:11,858 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:11,859 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,859 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:11,860 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:11,860 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:11,861 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,861 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:11,862 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:11,862 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,863 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:11,863 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,863 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:11,864 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,864 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,865 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:11,865 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:11,866 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:11,866 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,867 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:11,867 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:11,868 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:11,868 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:11,869 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:11,869 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:11,870 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,870 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:11,874 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,875 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:11,875 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:11,876 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,876 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:11,877 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:11,877 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:11,877 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,878 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,878 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:11,878 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,879 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:11,879 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:11,880 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:11,882 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:11,882 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,883 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:11,883 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:11,884 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,885 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:11,886 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:11,886 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,887 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-10-16 10:11:11,887 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,888 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:11,889 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,889 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:11,890 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:11,890 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$82compare_op.3 = hi < n\n", - "2024-10-16 10:11:11,891 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-10-16 10:11:11,892 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-10-16 10:11:11,892 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-10-16 10:11:11,893 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-10-16 10:11:11,894 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-10-16 10:11:11,894 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:11,894 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:11,895 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,895 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:11,897 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:11,897 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,898 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:11,898 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:11,899 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:11,899 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-10-16 10:11:11,900 - numba.core.ssa - DEBUG - idom 74 from label 86\n", - "2024-10-16 10:11:11,900 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-10-16 10:11:11,901 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-10-16 10:11:11,901 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-10-16 10:11:11,902 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-10-16 10:11:11,902 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-10-16 10:11:11,902 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-10-16 10:11:11,904 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:11,905 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:11,905 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,906 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:11,906 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,907 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:11,907 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:11,908 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:11,908 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,909 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-10-16 10:11:11,909 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,910 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:11,910 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,912 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:11,912 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:11,913 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:11,913 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-10-16 10:11:11,914 - numba.core.ssa - DEBUG - insert phi node hi.4 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-10-16 10:11:11,915 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-10-16 10:11:11,915 - numba.core.ssa - DEBUG - incoming_def hi.2 = $phi96.0\n", - "2024-10-16 10:11:11,916 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:11,917 - numba.core.ssa - DEBUG - incoming_def hi.1 = n\n", - "2024-10-16 10:11:11,917 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi.4 > lo.3\n", - "2024-10-16 10:11:11,918 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:11,918 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,919 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:11,919 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:11,921 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,921 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:11,922 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:11,922 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:11,923 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-10-16 10:11:11,923 - numba.core.ssa - DEBUG - insert phi node hi.5 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-10-16 10:11:11,924 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-10-16 10:11:11,925 - numba.core.ssa - DEBUG - incoming_def hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:11,925 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-10-16 10:11:11,926 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-10-16 10:11:11,927 - numba.core.ssa - DEBUG - insert phi node hi.6 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-10-16 10:11:11,927 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-10-16 10:11:11,928 - numba.core.ssa - DEBUG - find_def_from_top label 132\n", - "2024-10-16 10:11:11,928 - numba.core.ssa - DEBUG - idom 106 from label 132\n", - "2024-10-16 10:11:11,929 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-10-16 10:11:11,929 - numba.core.ssa - DEBUG - incoming_def hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-10-16 10:11:11,930 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-10-16 10:11:11,930 - numba.core.ssa - DEBUG - incoming_def hi.3 = mid\n", - "2024-10-16 10:11:11,931 - numba.core.ssa - DEBUG - incoming_def hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:11,931 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi.5\n", - "2024-10-16 10:11:11,932 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:11,932 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:11,933 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:11,933 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:11,934 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,936 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:11,937 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,937 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:11,937 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:11,939 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,939 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:11,940 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:11,940 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,941 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:11,942 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,942 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-10-16 10:11:11,943 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:11,944 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:11,944 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,945 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:11,945 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:11,946 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:11,947 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi.6 > lo.5\n", - "2024-10-16 10:11:11,948 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:11,948 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,949 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:11,950 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:11,950 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,951 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:11,951 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:11,952 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:11,953 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi96.0\n", - "2024-10-16 10:11:11,953 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:11,954 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,954 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:11,955 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:11,955 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:11,956 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:11,957 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:11,958 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:11,958 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:11,959 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:11,959 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,960 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:11,961 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,961 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:11,962 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:11,962 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,963 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:11,964 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:11,964 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:11,965 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,965 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:11,966 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:11,966 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,968 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:11,968 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,969 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:11,969 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,969 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:11,970 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:11,970 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:11,971 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:11,971 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,972 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:11,972 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:11,973 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:11,973 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:11,974 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:11,974 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:11,975 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,975 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:11,976 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,976 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:11,979 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:11,979 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,980 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:11,981 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:11,981 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:11,982 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,982 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:11,983 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:11,983 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,984 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:11,984 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:11,985 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:11,985 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:11,986 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,987 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:11,988 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:11,988 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,989 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:11,989 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:11,990 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,990 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-10-16 10:11:11,991 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:11,991 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:11,992 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,992 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:11,993 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:11,994 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:11,995 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:11,995 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:11,996 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:11,996 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:11,997 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:11,997 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:11,998 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:11,998 - numba.core.ssa - DEBUG - first assign: $phi96.0\n", - "2024-10-16 10:11:11,999 - numba.core.ssa - DEBUG - replaced with: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:11,999 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:12,000 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:12,000 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,000 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:12,001 - numba.core.ssa - DEBUG - replaced with: $phi96.0.1 = n\n", - "2024-10-16 10:11:12,001 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:12,002 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:12,002 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,003 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-10-16 10:11:12,003 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:12,006 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:12,006 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,007 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:12,007 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:12,008 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-10-16 10:11:12,008 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:12,009 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,010 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:12,011 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:12,011 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,012 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:12,012 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:12,013 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-10-16 10:11:12,013 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:12,014 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:12,015 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:12,015 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:12,016 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,016 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:12,017 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,017 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:12,019 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:12,019 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,020 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:12,020 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:12,021 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:12,021 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:12,022 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,023 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-10-16 10:11:12,023 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:12,024 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:12,024 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,025 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:12,025 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:12,026 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-10-16 10:11:12,026 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:12,027 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,027 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:12,028 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:12,028 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,028 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:12,029 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:12,029 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:12,030 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {86: [],\n", - " 94: []})\n", - "2024-10-16 10:11:12,033 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:12,033 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,033 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:12,034 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:12,035 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:12,036 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:12,036 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:12,037 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:12,038 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:12,038 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:12,039 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,039 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:12,040 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,040 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:12,041 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:12,041 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,042 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:12,042 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:12,043 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:12,043 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,044 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:12,046 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:12,046 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:12,047 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:12,047 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,048 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:12,048 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:12,049 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:12,050 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:12,050 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:12,051 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:12,051 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,052 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:12,053 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:12,054 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:12,054 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:12,055 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:12,055 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:12,056 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,056 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:12,057 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,058 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:12,058 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:12,059 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,060 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:12,060 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:12,061 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:12,062 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,062 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:12,063 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:12,063 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,063 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:12,065 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:12,065 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:12,066 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:12,066 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,067 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:12,067 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:12,068 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,068 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:12,069 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:12,069 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,070 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-10-16 10:11:12,071 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:12,071 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:12,072 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,072 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:12,073 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:12,073 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:12,073 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,074 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:12,075 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:12,075 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,075 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:12,076 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:12,076 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:12,077 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:12,077 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:12,078 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,078 - numba.core.ssa - DEBUG - on stmt: $phi96.0.1 = n\n", - "2024-10-16 10:11:12,079 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:12,079 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:12,079 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,080 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-10-16 10:11:12,080 - numba.core.ssa - DEBUG - find_def var='$phi96.0' stmt=hi.2 = $phi96.0\n", - "2024-10-16 10:11:12,081 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-10-16 10:11:12,081 - numba.core.ssa - DEBUG - insert phi node $phi96.0.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-10-16 10:11:12,082 - numba.core.ssa - DEBUG - find_def_from_bottom label 94\n", - "2024-10-16 10:11:12,082 - numba.core.ssa - DEBUG - incoming_def $phi96.0.1 = n\n", - "2024-10-16 10:11:12,083 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-10-16 10:11:12,083 - numba.core.ssa - DEBUG - incoming_def $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:12,088 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0.2\n", - "2024-10-16 10:11:12,088 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:12,089 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:12,089 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,090 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:12,090 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:12,091 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-10-16 10:11:12,091 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:12,092 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,092 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:12,093 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:12,093 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,094 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:12,094 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:12,095 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-10-16 10:11:12,095 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:12,096 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:12,096 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:12,099 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:12,099 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,100 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:12,100 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,101 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:12,101 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:12,102 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,103 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:12,104 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:12,104 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:12,105 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:12,105 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,106 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-10-16 10:11:12,106 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:12,107 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:12,108 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,108 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:12,109 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:12,110 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-10-16 10:11:12,110 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:12,111 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,112 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:12,112 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:12,113 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,113 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:12,114 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:12,114 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:12,151 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3728)\n", - " 2\tLOAD_FAST(arg=0, lineno=3728)\n", - " 4\tLOAD_FAST(arg=1, lineno=3728)\n", - " 6\tCOMPARE_OP(arg=1, lineno=3728)\n", - " 8\tRETURN_VALUE(arg=None, lineno=3728)\n", - "2024-10-16 10:11:12,152 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:12,153 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,154 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:12,155 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3728)\n", - "2024-10-16 10:11:12,155 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,156 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=3728)\n", - "2024-10-16 10:11:12,156 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,157 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=1, lineno=3728)\n", - "2024-10-16 10:11:12,158 - numba.core.byteflow - DEBUG - stack ['$x2.0']\n", - "2024-10-16 10:11:12,159 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=COMPARE_OP(arg=1, lineno=3728)\n", - "2024-10-16 10:11:12,159 - numba.core.byteflow - DEBUG - stack ['$x2.0', '$y4.1']\n", - "2024-10-16 10:11:12,160 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=3728)\n", - "2024-10-16 10:11:12,160 - numba.core.byteflow - DEBUG - stack ['$6compare_op.2']\n", - "2024-10-16 10:11:12,161 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:12,162 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:12,162 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:12,163 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:12,164 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,164 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,165 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:12,165 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:12,166 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:12,167 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$x2.0'}), (4, {'res': '$y4.1'}), (6, {'lhs': '$x2.0', 'rhs': '$y4.1', 'res': '$6compare_op.2'}), (8, {'retval': '$6compare_op.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:12,168 - numba.core.interpreter - DEBUG - label 0:\n", - " x = arg(0, name=x) ['x']\n", - " y = arg(1, name=y) ['y']\n", - " $6compare_op.2 = x <= y ['$6compare_op.2', 'x', 'y']\n", - " $8return_value.3 = cast(value=$6compare_op.2) ['$6compare_op.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:11:12,180 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:12,181 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,181 - numba.core.ssa - DEBUG - on stmt: x = arg(0, name=x)\n", - "2024-10-16 10:11:12,182 - numba.core.ssa - DEBUG - on stmt: y = arg(1, name=y)\n", - "2024-10-16 10:11:12,183 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = x <= y\n", - "2024-10-16 10:11:12,184 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6compare_op.2)\n", - "2024-10-16 10:11:12,184 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:11:12,185 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$6compare_op.2': [],\n", - " '$8return_value.3': [],\n", - " 'x': [],\n", - " 'y': []})\n", - "2024-10-16 10:11:12,186 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:12,418 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=2232)\n", - " 2\tLOAD_FAST(arg=0, lineno=2234)\n", - " 4\tLOAD_METHOD(arg=0, lineno=2234)\n", - " 6\tCALL_METHOD(arg=0, lineno=2234)\n", - " 8\tRETURN_VALUE(arg=None, lineno=2234)\n", - "2024-10-16 10:11:12,418 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:12,419 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,419 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:12,420 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=2232)\n", - "2024-10-16 10:11:12,420 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,420 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=2234)\n", - "2024-10-16 10:11:12,421 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,421 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=0, lineno=2234)\n", - "2024-10-16 10:11:12,422 - numba.core.byteflow - DEBUG - stack ['$ary2.0']\n", - "2024-10-16 10:11:12,422 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_METHOD(arg=0, lineno=2234)\n", - "2024-10-16 10:11:12,422 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:11:12,423 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=2234)\n", - "2024-10-16 10:11:12,423 - numba.core.byteflow - DEBUG - stack ['$6call_method.2']\n", - "2024-10-16 10:11:12,424 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:12,424 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:12,424 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:12,425 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:12,425 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,426 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,426 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:12,426 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:12,427 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:12,427 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$ary2.0'}), (4, {'item': '$ary2.0', 'res': '$4load_method.1'}), (6, {'func': '$4load_method.1', 'args': [], 'res': '$6call_method.2'}), (8, {'retval': '$6call_method.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:12,428 - numba.core.interpreter - DEBUG - label 0:\n", - " ary = arg(0, name=ary) ['ary']\n", - " $4load_method.1 = getattr(value=ary, attr=flatten) ['$4load_method.1', 'ary']\n", - " $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$6call_method.2']\n", - " $8return_value.3 = cast(value=$6call_method.2) ['$6call_method.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:11:12,436 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:12,437 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,437 - numba.core.ssa - DEBUG - on stmt: ary = arg(0, name=ary)\n", - "2024-10-16 10:11:12,438 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=ary, attr=flatten)\n", - "2024-10-16 10:11:12,438 - numba.core.ssa - DEBUG - on stmt: $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,439 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6call_method.2)\n", - "2024-10-16 10:11:12,439 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:11:12,439 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$4load_method.1': [],\n", - " '$6call_method.2': [],\n", - " '$8return_value.3': [],\n", - " 'ary': []})\n", - "2024-10-16 10:11:12,440 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:12,449 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=2259)\n", - " 2\tLOAD_FAST(arg=0, lineno=2260)\n", - " 4\tLOAD_METHOD(arg=0, lineno=2260)\n", - " 6\tCALL_METHOD(arg=0, lineno=2260)\n", - " 8\tLOAD_METHOD(arg=1, lineno=2260)\n", - " 10\tLOAD_FAST(arg=0, lineno=2260)\n", - " 12\tLOAD_ATTR(arg=2, lineno=2260)\n", - " 14\tCALL_METHOD(arg=1, lineno=2260)\n", - " 16\tRETURN_VALUE(arg=None, lineno=2260)\n", - "2024-10-16 10:11:12,449 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:12,450 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,450 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:12,450 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=2259)\n", - "2024-10-16 10:11:12,451 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,451 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=2260)\n", - "2024-10-16 10:11:12,452 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,452 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=0, lineno=2260)\n", - "2024-10-16 10:11:12,452 - numba.core.byteflow - DEBUG - stack ['$ary2.0']\n", - "2024-10-16 10:11:12,453 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_METHOD(arg=0, lineno=2260)\n", - "2024-10-16 10:11:12,453 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:11:12,454 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=1, lineno=2260)\n", - "2024-10-16 10:11:12,454 - numba.core.byteflow - DEBUG - stack ['$6call_method.2']\n", - "2024-10-16 10:11:12,454 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_FAST(arg=0, lineno=2260)\n", - "2024-10-16 10:11:12,455 - numba.core.byteflow - DEBUG - stack ['$8load_method.3']\n", - "2024-10-16 10:11:12,455 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=2, lineno=2260)\n", - "2024-10-16 10:11:12,456 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$ary10.4']\n", - "2024-10-16 10:11:12,456 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=CALL_METHOD(arg=1, lineno=2260)\n", - "2024-10-16 10:11:12,456 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$12load_attr.5']\n", - "2024-10-16 10:11:12,457 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=RETURN_VALUE(arg=None, lineno=2260)\n", - "2024-10-16 10:11:12,457 - numba.core.byteflow - DEBUG - stack ['$14call_method.6']\n", - "2024-10-16 10:11:12,457 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:12,458 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:12,458 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:12,459 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:12,459 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,460 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,460 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:12,460 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:12,461 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:12,461 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$ary2.0'}), (4, {'item': '$ary2.0', 'res': '$4load_method.1'}), (6, {'func': '$4load_method.1', 'args': [], 'res': '$6call_method.2'}), (8, {'item': '$6call_method.2', 'res': '$8load_method.3'}), (10, {'res': '$ary10.4'}), (12, {'item': '$ary10.4', 'res': '$12load_attr.5'}), (14, {'func': '$8load_method.3', 'args': ['$12load_attr.5'], 'res': '$14call_method.6'}), (16, {'retval': '$14call_method.6', 'castval': '$16return_value.7'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:12,462 - numba.core.interpreter - DEBUG - label 0:\n", - " ary = arg(0, name=ary) ['ary']\n", - " $4load_method.1 = getattr(value=ary, attr=copy) ['$4load_method.1', 'ary']\n", - " $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$6call_method.2']\n", - " $8load_method.3 = getattr(value=$6call_method.2, attr=reshape) ['$6call_method.2', '$8load_method.3']\n", - " $12load_attr.5 = getattr(value=ary, attr=size) ['$12load_attr.5', 'ary']\n", - " $14call_method.6 = call $8load_method.3($12load_attr.5, func=$8load_method.3, args=[Var($12load_attr.5, arrayobj.py:2260)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_attr.5', '$14call_method.6', '$8load_method.3']\n", - " $16return_value.7 = cast(value=$14call_method.6) ['$14call_method.6', '$16return_value.7']\n", - " return $16return_value.7 ['$16return_value.7']\n", - "\n", - "2024-10-16 10:11:12,472 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:12,472 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,473 - numba.core.ssa - DEBUG - on stmt: ary = arg(0, name=ary)\n", - "2024-10-16 10:11:12,473 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=ary, attr=copy)\n", - "2024-10-16 10:11:12,474 - numba.core.ssa - DEBUG - on stmt: $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,474 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6call_method.2, attr=reshape)\n", - "2024-10-16 10:11:12,474 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=ary, attr=size)\n", - "2024-10-16 10:11:12,475 - numba.core.ssa - DEBUG - on stmt: $14call_method.6 = call $8load_method.3($12load_attr.5, func=$8load_method.3, args=[Var($12load_attr.5, arrayobj.py:2260)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,475 - numba.core.ssa - DEBUG - on stmt: $16return_value.7 = cast(value=$14call_method.6)\n", - "2024-10-16 10:11:12,476 - numba.core.ssa - DEBUG - on stmt: return $16return_value.7\n", - "2024-10-16 10:11:12,476 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12load_attr.5': [],\n", - " '$14call_method.6': [],\n", - " '$16return_value.7': [],\n", - " '$4load_method.1': [],\n", - " '$6call_method.2': [],\n", - " '$8load_method.3': [],\n", - " 'ary': []})\n", - "2024-10-16 10:11:12,477 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:12,728 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=2924)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=2946)\n", - " 4\tLOAD_ATTR(arg=1, lineno=2946)\n", - " 6\tLOAD_FAST(arg=1, lineno=2947)\n", - " 8\tLOAD_CONST(arg=1, lineno=2947)\n", - " 10\tLOAD_CONST(arg=1, lineno=2947)\n", - " 12\tBUILD_SLICE(arg=2, lineno=2947)\n", - " 14\tLOAD_CONST(arg=2, lineno=2947)\n", - " 16\tBUILD_TUPLE(arg=2, lineno=2947)\n", - " 18\tBINARY_SUBSCR(arg=None, lineno=2947)\n", - " 20\tLOAD_METHOD(arg=2, lineno=2947)\n", - " 22\tCALL_METHOD(arg=0, lineno=2947)\n", - " 24\tLOAD_FAST(arg=0, lineno=2948)\n", - " 26\tLOAD_CONST(arg=3, lineno=2949)\n", - " 28\tLOAD_CONST(arg=4, lineno=2946)\n", - " 30\tCALL_FUNCTION_KW(arg=3, lineno=2946)\n", - " 32\tSTORE_FAST(arg=2, lineno=2946)\n", - " 34\tLOAD_FAST(arg=2, lineno=2951)\n", - " 36\tLOAD_CONST(arg=2, lineno=2951)\n", - " 38\tCOMPARE_OP(arg=2, lineno=2951)\n", - " 40\tPOP_JUMP_IF_FALSE(arg=24, lineno=2951)\n", - " 42\tLOAD_CONST(arg=5, lineno=2952)\n", - " 44\tRETURN_VALUE(arg=None, lineno=2952)\n", - "> 46\tLOAD_FAST(arg=0, lineno=2953)\n", - " 48\tLOAD_GLOBAL(arg=3, lineno=2953)\n", - " 50\tLOAD_FAST(arg=1, lineno=2954)\n", - " 52\tLOAD_FAST(arg=2, lineno=2954)\n", - " 54\tLOAD_CONST(arg=6, lineno=2954)\n", - " 56\tBINARY_SUBTRACT(arg=None, lineno=2954)\n", - " 58\tLOAD_CONST(arg=2, lineno=2954)\n", - " 60\tBUILD_TUPLE(arg=2, lineno=2954)\n", - " 62\tBINARY_SUBSCR(arg=None, lineno=2954)\n", - " 64\tLOAD_FAST(arg=1, lineno=2955)\n", - " 66\tLOAD_FAST(arg=2, lineno=2955)\n", - " 68\tLOAD_CONST(arg=6, lineno=2955)\n", - " 70\tBINARY_SUBTRACT(arg=None, lineno=2955)\n", - " 72\tLOAD_CONST(arg=6, lineno=2955)\n", - " 74\tBUILD_TUPLE(arg=2, lineno=2955)\n", - " 76\tBINARY_SUBSCR(arg=None, lineno=2955)\n", - " 78\tLOAD_FAST(arg=1, lineno=2956)\n", - " 80\tLOAD_FAST(arg=2, lineno=2956)\n", - " 82\tLOAD_CONST(arg=6, lineno=2956)\n", - " 84\tBINARY_SUBTRACT(arg=None, lineno=2956)\n", - " 86\tLOAD_CONST(arg=7, lineno=2956)\n", - " 88\tBUILD_TUPLE(arg=2, lineno=2956)\n", - " 90\tBINARY_SUBSCR(arg=None, lineno=2956)\n", - " 92\tCALL_FUNCTION(arg=3, lineno=2953)\n", - " 94\tCONTAINS_OP(arg=0, lineno=2953)\n", - " 96\tRETURN_VALUE(arg=None, lineno=2953)\n", - "2024-10-16 10:11:12,729 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:12,729 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,730 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:12,730 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=2924)\n", - "2024-10-16 10:11:12,731 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,731 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=2946)\n", - "2024-10-16 10:11:12,731 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,732 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=2946)\n", - "2024-10-16 10:11:12,732 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:11:12,733 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=2947)\n", - "2024-10-16 10:11:12,733 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-10-16 10:11:12,733 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_CONST(arg=1, lineno=2947)\n", - "2024-10-16 10:11:12,734 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$precursor_slices6.2']\n", - "2024-10-16 10:11:12,734 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_CONST(arg=1, lineno=2947)\n", - "2024-10-16 10:11:12,735 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$precursor_slices6.2', '$const8.3']\n", - "2024-10-16 10:11:12,735 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=BUILD_SLICE(arg=2, lineno=2947)\n", - "2024-10-16 10:11:12,735 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$precursor_slices6.2', '$const8.3', '$const10.4']\n", - "2024-10-16 10:11:12,736 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_CONST(arg=2, lineno=2947)\n", - "2024-10-16 10:11:12,736 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$precursor_slices6.2', '$12build_slice.6']\n", - "2024-10-16 10:11:12,737 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=BUILD_TUPLE(arg=2, lineno=2947)\n", - "2024-10-16 10:11:12,737 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$precursor_slices6.2', '$12build_slice.6', '$const14.7']\n", - "2024-10-16 10:11:12,737 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=BINARY_SUBSCR(arg=None, lineno=2947)\n", - "2024-10-16 10:11:12,738 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$precursor_slices6.2', '$16build_tuple.8']\n", - "2024-10-16 10:11:12,738 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_METHOD(arg=2, lineno=2947)\n", - "2024-10-16 10:11:12,739 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$18binary_subscr.9']\n", - "2024-10-16 10:11:12,739 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=CALL_METHOD(arg=0, lineno=2947)\n", - "2024-10-16 10:11:12,740 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$20load_method.10']\n", - "2024-10-16 10:11:12,740 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_FAST(arg=0, lineno=2948)\n", - "2024-10-16 10:11:12,740 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$22call_method.11']\n", - "2024-10-16 10:11:12,741 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_CONST(arg=3, lineno=2949)\n", - "2024-10-16 10:11:12,741 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$22call_method.11', '$precursor_index24.12']\n", - "2024-10-16 10:11:12,742 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_CONST(arg=4, lineno=2946)\n", - "2024-10-16 10:11:12,742 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$22call_method.11', '$precursor_index24.12', '$const26.13']\n", - "2024-10-16 10:11:12,742 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=CALL_FUNCTION_KW(arg=3, lineno=2946)\n", - "2024-10-16 10:11:12,743 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$22call_method.11', '$precursor_index24.12', '$const26.13', '$const28.14']\n", - "2024-10-16 10:11:12,743 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=STORE_FAST(arg=2, lineno=2946)\n", - "2024-10-16 10:11:12,744 - numba.core.byteflow - DEBUG - stack ['$30call_function_kw.15']\n", - "2024-10-16 10:11:12,744 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=2, lineno=2951)\n", - "2024-10-16 10:11:12,744 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,745 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_CONST(arg=2, lineno=2951)\n", - "2024-10-16 10:11:12,745 - numba.core.byteflow - DEBUG - stack ['$slice_index34.16']\n", - "2024-10-16 10:11:12,746 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=COMPARE_OP(arg=2, lineno=2951)\n", - "2024-10-16 10:11:12,746 - numba.core.byteflow - DEBUG - stack ['$slice_index34.16', '$const36.17']\n", - "2024-10-16 10:11:12,747 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=POP_JUMP_IF_FALSE(arg=24, lineno=2951)\n", - "2024-10-16 10:11:12,747 - numba.core.byteflow - DEBUG - stack ['$38compare_op.18']\n", - "2024-10-16 10:11:12,751 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=42, stack=(), blockstack=(), npush=0), Edge(pc=46, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,752 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=42 nstack_initial=0), State(pc_initial=46 nstack_initial=0)])\n", - "2024-10-16 10:11:12,752 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,753 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=42 nstack_initial=0)\n", - "2024-10-16 10:11:12,753 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_CONST(arg=5, lineno=2952)\n", - "2024-10-16 10:11:12,753 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,754 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=RETURN_VALUE(arg=None, lineno=2952)\n", - "2024-10-16 10:11:12,754 - numba.core.byteflow - DEBUG - stack ['$const42.0']\n", - "2024-10-16 10:11:12,755 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:12,755 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=0)])\n", - "2024-10-16 10:11:12,756 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,756 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=0)\n", - "2024-10-16 10:11:12,756 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=0, lineno=2953)\n", - "2024-10-16 10:11:12,757 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,757 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_GLOBAL(arg=3, lineno=2953)\n", - "2024-10-16 10:11:12,758 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0']\n", - "2024-10-16 10:11:12,758 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_FAST(arg=1, lineno=2954)\n", - "2024-10-16 10:11:12,758 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1']\n", - "2024-10-16 10:11:12,759 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=LOAD_FAST(arg=2, lineno=2954)\n", - "2024-10-16 10:11:12,759 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$precursor_slices50.2']\n", - "2024-10-16 10:11:12,760 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=LOAD_CONST(arg=6, lineno=2954)\n", - "2024-10-16 10:11:12,760 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$precursor_slices50.2', '$slice_index52.3']\n", - "2024-10-16 10:11:12,761 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=BINARY_SUBTRACT(arg=None, lineno=2954)\n", - "2024-10-16 10:11:12,761 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$precursor_slices50.2', '$slice_index52.3', '$const54.4']\n", - "2024-10-16 10:11:12,761 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_CONST(arg=2, lineno=2954)\n", - "2024-10-16 10:11:12,762 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$precursor_slices50.2', '$56binary_subtract.5']\n", - "2024-10-16 10:11:12,762 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=BUILD_TUPLE(arg=2, lineno=2954)\n", - "2024-10-16 10:11:12,763 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$precursor_slices50.2', '$56binary_subtract.5', '$const58.6']\n", - "2024-10-16 10:11:12,763 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=BINARY_SUBSCR(arg=None, lineno=2954)\n", - "2024-10-16 10:11:12,764 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$precursor_slices50.2', '$60build_tuple.7']\n", - "2024-10-16 10:11:12,764 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_FAST(arg=1, lineno=2955)\n", - "2024-10-16 10:11:12,764 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8']\n", - "2024-10-16 10:11:12,765 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_FAST(arg=2, lineno=2955)\n", - "2024-10-16 10:11:12,765 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$precursor_slices64.9']\n", - "2024-10-16 10:11:12,766 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_CONST(arg=6, lineno=2955)\n", - "2024-10-16 10:11:12,766 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$precursor_slices64.9', '$slice_index66.10']\n", - "2024-10-16 10:11:12,766 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=BINARY_SUBTRACT(arg=None, lineno=2955)\n", - "2024-10-16 10:11:12,767 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$precursor_slices64.9', '$slice_index66.10', '$const68.11']\n", - "2024-10-16 10:11:12,767 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=LOAD_CONST(arg=6, lineno=2955)\n", - "2024-10-16 10:11:12,768 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$precursor_slices64.9', '$70binary_subtract.12']\n", - "2024-10-16 10:11:12,768 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=BUILD_TUPLE(arg=2, lineno=2955)\n", - "2024-10-16 10:11:12,768 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$precursor_slices64.9', '$70binary_subtract.12', '$const72.13']\n", - "2024-10-16 10:11:12,769 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=BINARY_SUBSCR(arg=None, lineno=2955)\n", - "2024-10-16 10:11:12,769 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$precursor_slices64.9', '$74build_tuple.14']\n", - "2024-10-16 10:11:12,770 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=1, lineno=2956)\n", - "2024-10-16 10:11:12,770 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$76binary_subscr.15']\n", - "2024-10-16 10:11:12,770 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_FAST(arg=2, lineno=2956)\n", - "2024-10-16 10:11:12,771 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$76binary_subscr.15', '$precursor_slices78.16']\n", - "2024-10-16 10:11:12,771 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=LOAD_CONST(arg=6, lineno=2956)\n", - "2024-10-16 10:11:12,772 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$76binary_subscr.15', '$precursor_slices78.16', '$slice_index80.17']\n", - "2024-10-16 10:11:12,772 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=BINARY_SUBTRACT(arg=None, lineno=2956)\n", - "2024-10-16 10:11:12,772 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$76binary_subscr.15', '$precursor_slices78.16', '$slice_index80.17', '$const82.18']\n", - "2024-10-16 10:11:12,773 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_CONST(arg=7, lineno=2956)\n", - "2024-10-16 10:11:12,773 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$76binary_subscr.15', '$precursor_slices78.16', '$84binary_subtract.19']\n", - "2024-10-16 10:11:12,774 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=BUILD_TUPLE(arg=2, lineno=2956)\n", - "2024-10-16 10:11:12,774 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$76binary_subscr.15', '$precursor_slices78.16', '$84binary_subtract.19', '$const86.20']\n", - "2024-10-16 10:11:12,775 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=BINARY_SUBSCR(arg=None, lineno=2956)\n", - "2024-10-16 10:11:12,780 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$76binary_subscr.15', '$precursor_slices78.16', '$88build_tuple.21']\n", - "2024-10-16 10:11:12,781 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=CALL_FUNCTION(arg=3, lineno=2953)\n", - "2024-10-16 10:11:12,781 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$48load_global.1', '$62binary_subscr.8', '$76binary_subscr.15', '$90binary_subscr.22']\n", - "2024-10-16 10:11:12,781 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=CONTAINS_OP(arg=0, lineno=2953)\n", - "2024-10-16 10:11:12,782 - numba.core.byteflow - DEBUG - stack ['$precursor_index46.0', '$92call_function.23']\n", - "2024-10-16 10:11:12,782 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=RETURN_VALUE(arg=None, lineno=2953)\n", - "2024-10-16 10:11:12,783 - numba.core.byteflow - DEBUG - stack ['$94contains_op.24']\n", - "2024-10-16 10:11:12,783 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:12,783 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:12,784 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=42 nstack_initial=0): set(),\n", - " State(pc_initial=46 nstack_initial=0): set()})\n", - "2024-10-16 10:11:12,784 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:12,785 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,785 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,786 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:12,786 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:12,786 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:12,787 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'res': '$precursor_slices6.2'}), (8, {'res': '$const8.3'}), (10, {'res': '$const10.4'}), (12, {'start': '$const8.3', 'stop': '$const10.4', 'step': None, 'res': '$12build_slice.6', 'slicevar': '$12build_slice.5'}), (14, {'res': '$const14.7'}), (16, {'items': ['$12build_slice.6', '$const14.7'], 'res': '$16build_tuple.8'}), (18, {'index': '$16build_tuple.8', 'target': '$precursor_slices6.2', 'res': '$18binary_subscr.9'}), (20, {'item': '$18binary_subscr.9', 'res': '$20load_method.10'}), (22, {'func': '$20load_method.10', 'args': [], 'res': '$22call_method.11'}), (24, {'res': '$precursor_index24.12'}), (26, {'res': '$const26.13'}), (28, {'res': '$const28.14'}), (30, {'func': '$4load_attr.1', 'args': ['$22call_method.11', '$precursor_index24.12', '$const26.13'], 'names': '$const28.14', 'res': '$30call_function_kw.15'}), (32, {'value': '$30call_function_kw.15'}), (34, {'res': '$slice_index34.16'}), (36, {'res': '$const36.17'}), (38, {'lhs': '$slice_index34.16', 'rhs': '$const36.17', 'res': '$38compare_op.18'}), (40, {'pred': '$38compare_op.18'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={42: (), 46: ()})\n", - "2024-10-16 10:11:12,787 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=42 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((42, {'res': '$const42.0'}), (44, {'retval': '$const42.0', 'castval': '$44return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:12,788 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((46, {'res': '$precursor_index46.0'}), (48, {'res': '$48load_global.1'}), (50, {'res': '$precursor_slices50.2'}), (52, {'res': '$slice_index52.3'}), (54, {'res': '$const54.4'}), (56, {'lhs': '$slice_index52.3', 'rhs': '$const54.4', 'res': '$56binary_subtract.5'}), (58, {'res': '$const58.6'}), (60, {'items': ['$56binary_subtract.5', '$const58.6'], 'res': '$60build_tuple.7'}), (62, {'index': '$60build_tuple.7', 'target': '$precursor_slices50.2', 'res': '$62binary_subscr.8'}), (64, {'res': '$precursor_slices64.9'}), (66, {'res': '$slice_index66.10'}), (68, {'res': '$const68.11'}), (70, {'lhs': '$slice_index66.10', 'rhs': '$const68.11', 'res': '$70binary_subtract.12'}), (72, {'res': '$const72.13'}), (74, {'items': ['$70binary_subtract.12', '$const72.13'], 'res': '$74build_tuple.14'}), (76, {'index': '$74build_tuple.14', 'target': '$precursor_slices64.9', 'res': '$76binary_subscr.15'}), (78, {'res': '$precursor_slices78.16'}), (80, {'res': '$slice_index80.17'}), (82, {'res': '$const82.18'}), (84, {'lhs': '$slice_index80.17', 'rhs': '$const82.18', 'res': '$84binary_subtract.19'}), (86, {'res': '$const86.20'}), (88, {'items': ['$84binary_subtract.19', '$const86.20'], 'res': '$88build_tuple.21'}), (90, {'index': '$88build_tuple.21', 'target': '$precursor_slices78.16', 'res': '$90binary_subscr.22'}), (92, {'func': '$48load_global.1', 'args': ['$62binary_subscr.8', '$76binary_subscr.15', '$90binary_subscr.22'], 'res': '$92call_function.23'}), (94, {'lhs': '$precursor_index46.0', 'rhs': '$92call_function.23', 'res': '$94contains_op.24'}), (96, {'retval': '$94contains_op.24', 'castval': '$96return_value.25'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:12,790 - numba.core.interpreter - DEBUG - label 0:\n", - " precursor_index = arg(0, name=precursor_index) ['precursor_index']\n", - " precursor_slices = arg(1, name=precursor_slices) ['precursor_slices']\n", - " $2load_global.0 = global(np: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=searchsorted) ['$2load_global.0', '$4load_attr.1']\n", - " $const8.3 = const(NoneType, None) ['$const8.3']\n", - " $const10.4 = const(NoneType, None) ['$const10.4']\n", - " $12build_slice.5 = global(slice: ) ['$12build_slice.5']\n", - " $12build_slice.6 = call $12build_slice.5($const8.3, $const10.4, func=$12build_slice.5, args=(Var($const8.3, bruker.py:2947), Var($const10.4, bruker.py:2947)), kws=(), vararg=None, varkwarg=None, target=None) ['$12build_slice.5', '$12build_slice.6', '$const10.4', '$const8.3']\n", - " $const14.7 = const(int, 0) ['$const14.7']\n", - " $16build_tuple.8 = build_tuple(items=[Var($12build_slice.6, bruker.py:2947), Var($const14.7, bruker.py:2947)]) ['$12build_slice.6', '$16build_tuple.8', '$const14.7']\n", - " $18binary_subscr.9 = getitem(value=precursor_slices, index=$16build_tuple.8, fn=) ['$16build_tuple.8', '$18binary_subscr.9', 'precursor_slices']\n", - " $20load_method.10 = getattr(value=$18binary_subscr.9, attr=ravel) ['$18binary_subscr.9', '$20load_method.10']\n", - " $22call_method.11 = call $20load_method.10(func=$20load_method.10, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$20load_method.10', '$22call_method.11']\n", - " $const26.13 = const(str, right) ['$const26.13']\n", - " slice_index = call $4load_attr.1($22call_method.11, precursor_index, func=$4load_attr.1, args=[Var($22call_method.11, bruker.py:2947), Var(precursor_index, bruker.py:2924)], kws=[('side', Var($const26.13, bruker.py:2949))], vararg=None, varkwarg=None, target=None) ['$22call_method.11', '$4load_attr.1', '$const26.13', 'precursor_index', 'slice_index']\n", - " $const36.17 = const(int, 0) ['$const36.17']\n", - " $38compare_op.18 = slice_index == $const36.17 ['$38compare_op.18', '$const36.17', 'slice_index']\n", - " bool40 = global(bool: ) ['bool40']\n", - " $40pred = call bool40($38compare_op.18, func=bool40, args=(Var($38compare_op.18, bruker.py:2951),), kws=(), vararg=None, varkwarg=None, target=None) ['$38compare_op.18', '$40pred', 'bool40']\n", - " branch $40pred, 42, 46 ['$40pred']\n", - "label 42:\n", - " $const42.0 = const(bool, False) ['$const42.0']\n", - " $44return_value.1 = cast(value=$const42.0) ['$44return_value.1', '$const42.0']\n", - " return $44return_value.1 ['$44return_value.1']\n", - "label 46:\n", - " $48load_global.1 = global(range: ) ['$48load_global.1']\n", - " $const54.4 = const(int, 1) ['$const54.4']\n", - " $56binary_subtract.5 = slice_index - $const54.4 ['$56binary_subtract.5', '$const54.4', 'slice_index']\n", - " $const58.6 = const(int, 0) ['$const58.6']\n", - " $60build_tuple.7 = build_tuple(items=[Var($56binary_subtract.5, bruker.py:2954), Var($const58.6, bruker.py:2954)]) ['$56binary_subtract.5', '$60build_tuple.7', '$const58.6']\n", - " $62binary_subscr.8 = getitem(value=precursor_slices, index=$60build_tuple.7, fn=) ['$60build_tuple.7', '$62binary_subscr.8', 'precursor_slices']\n", - " $const68.11 = const(int, 1) ['$const68.11']\n", - " $70binary_subtract.12 = slice_index - $const68.11 ['$70binary_subtract.12', '$const68.11', 'slice_index']\n", - " $const72.13 = const(int, 1) ['$const72.13']\n", - " $74build_tuple.14 = build_tuple(items=[Var($70binary_subtract.12, bruker.py:2955), Var($const72.13, bruker.py:2955)]) ['$70binary_subtract.12', '$74build_tuple.14', '$const72.13']\n", - " $76binary_subscr.15 = getitem(value=precursor_slices, index=$74build_tuple.14, fn=) ['$74build_tuple.14', '$76binary_subscr.15', 'precursor_slices']\n", - " $const82.18 = const(int, 1) ['$const82.18']\n", - " $84binary_subtract.19 = slice_index - $const82.18 ['$84binary_subtract.19', '$const82.18', 'slice_index']\n", - " $const86.20 = const(int, 2) ['$const86.20']\n", - " $88build_tuple.21 = build_tuple(items=[Var($84binary_subtract.19, bruker.py:2956), Var($const86.20, bruker.py:2956)]) ['$84binary_subtract.19', '$88build_tuple.21', '$const86.20']\n", - " $90binary_subscr.22 = getitem(value=precursor_slices, index=$88build_tuple.21, fn=) ['$88build_tuple.21', '$90binary_subscr.22', 'precursor_slices']\n", - " $92call_function.23 = call $48load_global.1($62binary_subscr.8, $76binary_subscr.15, $90binary_subscr.22, func=$48load_global.1, args=[Var($62binary_subscr.8, bruker.py:2954), Var($76binary_subscr.15, bruker.py:2955), Var($90binary_subscr.22, bruker.py:2956)], kws=(), vararg=None, varkwarg=None, target=None) ['$48load_global.1', '$62binary_subscr.8', '$76binary_subscr.15', '$90binary_subscr.22', '$92call_function.23']\n", - " $94contains_op.24 = precursor_index in $92call_function.23 ['$92call_function.23', '$94contains_op.24', 'precursor_index']\n", - " $96return_value.25 = cast(value=$94contains_op.24) ['$94contains_op.24', '$96return_value.25']\n", - " return $96return_value.25 ['$96return_value.25']\n", - "\n", - "2024-10-16 10:11:12,803 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:12,804 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,804 - numba.core.ssa - DEBUG - on stmt: precursor_index = arg(0, name=precursor_index)\n", - "2024-10-16 10:11:12,805 - numba.core.ssa - DEBUG - on stmt: precursor_slices = arg(1, name=precursor_slices)\n", - "2024-10-16 10:11:12,805 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:12,805 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=searchsorted)\n", - "2024-10-16 10:11:12,806 - numba.core.ssa - DEBUG - on stmt: $const8.3 = const(NoneType, None)\n", - "2024-10-16 10:11:12,806 - numba.core.ssa - DEBUG - on stmt: $const10.4 = const(NoneType, None)\n", - "2024-10-16 10:11:12,807 - numba.core.ssa - DEBUG - on stmt: $12build_slice.5 = global(slice: )\n", - "2024-10-16 10:11:12,807 - numba.core.ssa - DEBUG - on stmt: $12build_slice.6 = call $12build_slice.5($const8.3, $const10.4, func=$12build_slice.5, args=(Var($const8.3, bruker.py:2947), Var($const10.4, bruker.py:2947)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,808 - numba.core.ssa - DEBUG - on stmt: $const14.7 = const(int, 0)\n", - "2024-10-16 10:11:12,808 - numba.core.ssa - DEBUG - on stmt: $16build_tuple.8 = build_tuple(items=[Var($12build_slice.6, bruker.py:2947), Var($const14.7, bruker.py:2947)])\n", - "2024-10-16 10:11:12,808 - numba.core.ssa - DEBUG - on stmt: $18binary_subscr.9 = static_getitem(value=precursor_slices, index=(slice(None, None, None), 0), index_var=$16build_tuple.8, fn=)\n", - "2024-10-16 10:11:12,809 - numba.core.ssa - DEBUG - on stmt: $20load_method.10 = getattr(value=$18binary_subscr.9, attr=ravel)\n", - "2024-10-16 10:11:12,809 - numba.core.ssa - DEBUG - on stmt: $22call_method.11 = call $20load_method.10(func=$20load_method.10, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,810 - numba.core.ssa - DEBUG - on stmt: $const26.13 = const(str, right)\n", - "2024-10-16 10:11:12,810 - numba.core.ssa - DEBUG - on stmt: slice_index = call $4load_attr.1($22call_method.11, precursor_index, func=$4load_attr.1, args=[Var($22call_method.11, bruker.py:2947), Var(precursor_index, bruker.py:2924)], kws=[('side', Var($const26.13, bruker.py:2949))], vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,810 - numba.core.ssa - DEBUG - on stmt: $const36.17 = const(int, 0)\n", - "2024-10-16 10:11:12,811 - numba.core.ssa - DEBUG - on stmt: $38compare_op.18 = slice_index == $const36.17\n", - "2024-10-16 10:11:12,811 - numba.core.ssa - DEBUG - on stmt: bool40 = global(bool: )\n", - "2024-10-16 10:11:12,812 - numba.core.ssa - DEBUG - on stmt: $40pred = call bool40($38compare_op.18, func=bool40, args=(Var($38compare_op.18, bruker.py:2951),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,812 - numba.core.ssa - DEBUG - on stmt: branch $40pred, 42, 46\n", - "2024-10-16 10:11:12,812 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 42\n", - "2024-10-16 10:11:12,813 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,813 - numba.core.ssa - DEBUG - on stmt: $const42.0 = const(bool, False)\n", - "2024-10-16 10:11:12,814 - numba.core.ssa - DEBUG - on stmt: $44return_value.1 = cast(value=$const42.0)\n", - "2024-10-16 10:11:12,814 - numba.core.ssa - DEBUG - on stmt: return $44return_value.1\n", - "2024-10-16 10:11:12,814 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-10-16 10:11:12,815 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,815 - numba.core.ssa - DEBUG - on stmt: $48load_global.1 = global(range: )\n", - "2024-10-16 10:11:12,816 - numba.core.ssa - DEBUG - on stmt: $const54.4 = const(int, 1)\n", - "2024-10-16 10:11:12,816 - numba.core.ssa - DEBUG - on stmt: $56binary_subtract.5 = slice_index - $const54.4\n", - "2024-10-16 10:11:12,816 - numba.core.ssa - DEBUG - on stmt: $const58.6 = const(int, 0)\n", - "2024-10-16 10:11:12,817 - numba.core.ssa - DEBUG - on stmt: $60build_tuple.7 = build_tuple(items=[Var($56binary_subtract.5, bruker.py:2954), Var($const58.6, bruker.py:2954)])\n", - "2024-10-16 10:11:12,817 - numba.core.ssa - DEBUG - on stmt: $62binary_subscr.8 = getitem(value=precursor_slices, index=$60build_tuple.7, fn=)\n", - "2024-10-16 10:11:12,818 - numba.core.ssa - DEBUG - on stmt: $const68.11 = const(int, 1)\n", - "2024-10-16 10:11:12,818 - numba.core.ssa - DEBUG - on stmt: $70binary_subtract.12 = slice_index - $const68.11\n", - "2024-10-16 10:11:12,818 - numba.core.ssa - DEBUG - on stmt: $const72.13 = const(int, 1)\n", - "2024-10-16 10:11:12,819 - numba.core.ssa - DEBUG - on stmt: $74build_tuple.14 = build_tuple(items=[Var($70binary_subtract.12, bruker.py:2955), Var($const72.13, bruker.py:2955)])\n", - "2024-10-16 10:11:12,819 - numba.core.ssa - DEBUG - on stmt: $76binary_subscr.15 = getitem(value=precursor_slices, index=$74build_tuple.14, fn=)\n", - "2024-10-16 10:11:12,820 - numba.core.ssa - DEBUG - on stmt: $const82.18 = const(int, 1)\n", - "2024-10-16 10:11:12,820 - numba.core.ssa - DEBUG - on stmt: $84binary_subtract.19 = slice_index - $const82.18\n", - "2024-10-16 10:11:12,820 - numba.core.ssa - DEBUG - on stmt: $const86.20 = const(int, 2)\n", - "2024-10-16 10:11:12,821 - numba.core.ssa - DEBUG - on stmt: $88build_tuple.21 = build_tuple(items=[Var($84binary_subtract.19, bruker.py:2956), Var($const86.20, bruker.py:2956)])\n", - "2024-10-16 10:11:12,821 - numba.core.ssa - DEBUG - on stmt: $90binary_subscr.22 = getitem(value=precursor_slices, index=$88build_tuple.21, fn=)\n", - "2024-10-16 10:11:12,822 - numba.core.ssa - DEBUG - on stmt: $92call_function.23 = call $48load_global.1($62binary_subscr.8, $76binary_subscr.15, $90binary_subscr.22, func=$48load_global.1, args=[Var($62binary_subscr.8, bruker.py:2954), Var($76binary_subscr.15, bruker.py:2955), Var($90binary_subscr.22, bruker.py:2956)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,822 - numba.core.ssa - DEBUG - on stmt: $94contains_op.24 = precursor_index in $92call_function.23\n", - "2024-10-16 10:11:12,822 - numba.core.ssa - DEBUG - on stmt: $96return_value.25 = cast(value=$94contains_op.24)\n", - "2024-10-16 10:11:12,823 - numba.core.ssa - DEBUG - on stmt: return $96return_value.25\n", - "2024-10-16 10:11:12,824 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12build_slice.5': [],\n", - " '$12build_slice.6': [],\n", - " '$16build_tuple.8': [],\n", - " '$18binary_subscr.9': [],\n", - " '$20load_method.10': [],\n", - " '$22call_method.11': [],\n", - " '$2load_global.0': [],\n", - " '$38compare_op.18': [],\n", - " '$40pred': [],\n", - " '$44return_value.1': [],\n", - " '$48load_global.1': [],\n", - " '$4load_attr.1': [],\n", - " '$56binary_subtract.5': [],\n", - " '$60build_tuple.7': [],\n", - " '$62binary_subscr.8': [],\n", - " '$70binary_subtract.12': [],\n", - " '$74build_tuple.14': [],\n", - " '$76binary_subscr.15': [],\n", - " '$84binary_subtract.19': [],\n", - " '$88build_tuple.21': [],\n", - " '$90binary_subscr.22': [],\n", - " '$92call_function.23': [],\n", - " '$94contains_op.24': [],\n", - " '$96return_value.25': [],\n", - " '$const10.4': [],\n", - " '$const14.7': [],\n", - " '$const26.13': [],\n", - " '$const36.17': [],\n", - " '$const42.0': [],\n", - " '$const54.4': [],\n", - " '$const58.6': [],\n", - " '$const68.11': [],\n", - " '$const72.13': [],\n", - " '$const8.3': [],\n", - " '$const82.18': [],\n", - " '$const86.20': [],\n", - " 'bool40': [],\n", - " 'precursor_index': [],\n", - " 'precursor_slices': [],\n", - " 'slice_index': []})\n", - "2024-10-16 10:11:12,824 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:12,830 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3773)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3774)\n", - " 4\tLOAD_FAST(arg=0, lineno=3774)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=3774)\n", - " 8\tSTORE_FAST(arg=3, lineno=3774)\n", - " 10\tLOAD_DEREF(arg=0, lineno=3775)\n", - " 12\tLOAD_FAST(arg=0, lineno=3775)\n", - " 14\tLOAD_FAST(arg=1, lineno=3775)\n", - " 16\tLOAD_FAST(arg=1, lineno=3775)\n", - " 18\tLOAD_CONST(arg=1, lineno=3775)\n", - " 20\tLOAD_FAST(arg=3, lineno=3775)\n", - " 22\tLOAD_FAST(arg=3, lineno=3775)\n", - " 24\tCALL_FUNCTION(arg=6, lineno=3775)\n", - " 26\tRETURN_VALUE(arg=None, lineno=3775)\n", - "2024-10-16 10:11:12,831 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:12,831 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,832 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:12,832 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3773)\n", - "2024-10-16 10:11:12,833 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,833 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3774)\n", - "2024-10-16 10:11:12,833 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,834 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=3774)\n", - "2024-10-16 10:11:12,834 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:11:12,835 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=3774)\n", - "2024-10-16 10:11:12,835 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$a4.1']\n", - "2024-10-16 10:11:12,835 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=3, lineno=3774)\n", - "2024-10-16 10:11:12,836 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-10-16 10:11:12,836 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_DEREF(arg=0, lineno=3775)\n", - "2024-10-16 10:11:12,837 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,837 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=0, lineno=3775)\n", - "2024-10-16 10:11:12,837 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3']\n", - "2024-10-16 10:11:12,838 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-10-16 10:11:12,838 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4']\n", - "2024-10-16 10:11:12,839 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-10-16 10:11:12,839 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5']\n", - "2024-10-16 10:11:12,839 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=1, lineno=3775)\n", - "2024-10-16 10:11:12,840 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6']\n", - "2024-10-16 10:11:12,840 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-10-16 10:11:12,841 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7']\n", - "2024-10-16 10:11:12,841 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-10-16 10:11:12,841 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8']\n", - "2024-10-16 10:11:12,842 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=CALL_FUNCTION(arg=6, lineno=3775)\n", - "2024-10-16 10:11:12,842 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9']\n", - "2024-10-16 10:11:12,843 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=RETURN_VALUE(arg=None, lineno=3775)\n", - "2024-10-16 10:11:12,843 - numba.core.byteflow - DEBUG - stack ['$24call_function.10']\n", - "2024-10-16 10:11:12,843 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:12,844 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:12,844 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:12,845 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:12,845 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,845 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:12,846 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:12,846 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:12,847 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:12,847 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$a4.1'}), (6, {'func': '$2load_global.0', 'args': ['$a4.1'], 'res': '$6call_function.2'}), (8, {'value': '$6call_function.2'}), (10, {'res': '$10load_deref.3'}), (12, {'res': '$a12.4'}), (14, {'res': '$v14.5'}), (16, {'res': '$v16.6'}), (18, {'res': '$const18.7'}), (20, {'res': '$n20.8'}), (22, {'res': '$n22.9'}), (24, {'func': '$10load_deref.3', 'args': ['$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9'], 'res': '$24call_function.10'}), (26, {'retval': '$24call_function.10', 'castval': '$26return_value.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:12,850 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " side = arg(2, name=side) ['side']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'a', 'n']\n", - " $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f33dd9a25f0>) ['$10load_deref.3']\n", - " $const18.7 = const(int, 0) ['$const18.7']\n", - " $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_deref.3', '$24call_function.10', '$const18.7', 'a', 'n', 'n', 'v', 'v']\n", - " $26return_value.11 = cast(value=$24call_function.10) ['$24call_function.10', '$26return_value.11']\n", - " return $26return_value.11 ['$26return_value.11']\n", - "\n", - "2024-10-16 10:11:12,857 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:12,858 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:12,858 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:12,859 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:12,859 - numba.core.ssa - DEBUG - on stmt: side = arg(2, name=side)\n", - "2024-10-16 10:11:12,859 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-10-16 10:11:12,860 - numba.core.ssa - DEBUG - on stmt: n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,860 - numba.core.ssa - DEBUG - on stmt: $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f33dd9a25f0>)\n", - "2024-10-16 10:11:12,861 - numba.core.ssa - DEBUG - on stmt: $const18.7 = const(int, 0)\n", - "2024-10-16 10:11:12,861 - numba.core.ssa - DEBUG - on stmt: $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:12,862 - numba.core.ssa - DEBUG - on stmt: $26return_value.11 = cast(value=$24call_function.10)\n", - "2024-10-16 10:11:12,862 - numba.core.ssa - DEBUG - on stmt: return $26return_value.11\n", - "2024-10-16 10:11:12,862 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_deref.3': [],\n", - " '$24call_function.10': [],\n", - " '$26return_value.11': [],\n", - " '$2load_global.0': [],\n", - " '$const18.7': [],\n", - " 'a': [],\n", - " 'n': [],\n", - " 'side': [],\n", - " 'v': []})\n", - "2024-10-16 10:11:12,863 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:12,867 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3678)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3701)\n", - " 4\tLOAD_METHOD(arg=1, lineno=3701)\n", - " 6\tLOAD_FAST(arg=1, lineno=3701)\n", - " 8\tCALL_METHOD(arg=1, lineno=3701)\n", - " 10\tPOP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - " 12\tLOAD_GLOBAL(arg=2, lineno=3704)\n", - " 14\tLOAD_FAST(arg=5, lineno=3704)\n", - " 16\tLOAD_CONST(arg=1, lineno=3704)\n", - " 18\tLOAD_CONST(arg=2, lineno=3704)\n", - " 20\tCALL_FUNCTION(arg=3, lineno=3704)\n", - " 22\tGET_ITER(arg=None, lineno=3704)\n", - "> 24\tFOR_ITER(arg=15, lineno=3704)\n", - " 26\tSTORE_FAST(arg=6, lineno=3704)\n", - " 28\tLOAD_GLOBAL(arg=0, lineno=3705)\n", - " 30\tLOAD_METHOD(arg=1, lineno=3705)\n", - " 32\tLOAD_FAST(arg=0, lineno=3705)\n", - " 34\tLOAD_FAST(arg=6, lineno=3705)\n", - " 36\tLOAD_CONST(arg=3, lineno=3705)\n", - " 38\tBINARY_SUBTRACT(arg=None, lineno=3705)\n", - " 40\tBINARY_SUBSCR(arg=None, lineno=3705)\n", - " 42\tCALL_METHOD(arg=1, lineno=3705)\n", - " 44\tPOP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - " 46\tLOAD_FAST(arg=6, lineno=3706)\n", - " 48\tROT_TWO(arg=None, lineno=3706)\n", - " 50\tPOP_TOP(arg=None, lineno=3706)\n", - " 52\tRETURN_VALUE(arg=None, lineno=3706)\n", - "> 54\tJUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "> 56\tLOAD_CONST(arg=1, lineno=3707)\n", - " 58\tRETURN_VALUE(arg=None, lineno=3707)\n", - "> 60\tLOAD_FAST(arg=2, lineno=3709)\n", - " 62\tLOAD_FAST(arg=1, lineno=3709)\n", - " 64\tCOMPARE_OP(arg=0, lineno=3709)\n", - " 66\tPOP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - " 68\tLOAD_FAST(arg=5, lineno=3710)\n", - " 70\tSTORE_FAST(arg=4, lineno=3710)\n", - " 72\tJUMP_FORWARD(arg=12, lineno=3710)\n", - "> 74\tLOAD_CONST(arg=1, lineno=3712)\n", - " 76\tSTORE_FAST(arg=3, lineno=3712)\n", - " 78\tLOAD_FAST(arg=4, lineno=3713)\n", - " 80\tLOAD_FAST(arg=5, lineno=3713)\n", - " 82\tCOMPARE_OP(arg=0, lineno=3713)\n", - " 84\tPOP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - " 86\tLOAD_FAST(arg=4, lineno=3713)\n", - " 88\tLOAD_CONST(arg=3, lineno=3713)\n", - " 90\tBINARY_ADD(arg=None, lineno=3713)\n", - " 92\tJUMP_FORWARD(arg=1, lineno=3713)\n", - "> 94\tLOAD_FAST(arg=5, lineno=3713)\n", - "> 96\tSTORE_FAST(arg=4, lineno=3713)\n", - "> 98\tLOAD_FAST(arg=4, lineno=3715)\n", - " 100\tLOAD_FAST(arg=3, lineno=3715)\n", - " 102\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 104\tPOP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "> 106\tLOAD_FAST(arg=3, lineno=3716)\n", - " 108\tLOAD_FAST(arg=4, lineno=3716)\n", - " 110\tBINARY_ADD(arg=None, lineno=3716)\n", - " 112\tLOAD_CONST(arg=3, lineno=3716)\n", - " 114\tBINARY_RSHIFT(arg=None, lineno=3716)\n", - " 116\tSTORE_FAST(arg=7, lineno=3716)\n", - " 118\tLOAD_DEREF(arg=0, lineno=3717)\n", - " 120\tLOAD_FAST(arg=0, lineno=3717)\n", - " 122\tLOAD_FAST(arg=7, lineno=3717)\n", - " 124\tBINARY_SUBSCR(arg=None, lineno=3717)\n", - " 126\tLOAD_FAST(arg=1, lineno=3717)\n", - " 128\tCALL_FUNCTION(arg=2, lineno=3717)\n", - " 130\tPOP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - " 132\tLOAD_FAST(arg=7, lineno=3719)\n", - " 134\tLOAD_CONST(arg=3, lineno=3719)\n", - " 136\tBINARY_ADD(arg=None, lineno=3719)\n", - " 138\tSTORE_FAST(arg=3, lineno=3719)\n", - " 140\tJUMP_FORWARD(arg=2, lineno=3719)\n", - "> 142\tLOAD_FAST(arg=7, lineno=3722)\n", - " 144\tSTORE_FAST(arg=4, lineno=3722)\n", - "> 146\tLOAD_FAST(arg=4, lineno=3715)\n", - " 148\tLOAD_FAST(arg=3, lineno=3715)\n", - " 150\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 152\tPOP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "> 154\tLOAD_FAST(arg=3, lineno=3723)\n", - " 156\tRETURN_VALUE(arg=None, lineno=3723)\n", - "2024-10-16 10:11:12,868 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:12,868 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,869 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:12,869 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3678)\n", - "2024-10-16 10:11:12,869 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,870 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3701)\n", - "2024-10-16 10:11:12,870 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,871 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=1, lineno=3701)\n", - "2024-10-16 10:11:12,871 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:11:12,872 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=3701)\n", - "2024-10-16 10:11:12,872 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:11:12,872 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_METHOD(arg=1, lineno=3701)\n", - "2024-10-16 10:11:12,873 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$v6.2']\n", - "2024-10-16 10:11:12,873 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=POP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - "2024-10-16 10:11:12,874 - numba.core.byteflow - DEBUG - stack ['$8call_method.3']\n", - "2024-10-16 10:11:12,874 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=12, stack=(), blockstack=(), npush=0), Edge(pc=60, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,875 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=12 nstack_initial=0), State(pc_initial=60 nstack_initial=0)])\n", - "2024-10-16 10:11:12,875 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,875 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=12 nstack_initial=0)\n", - "2024-10-16 10:11:12,876 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_GLOBAL(arg=2, lineno=3704)\n", - "2024-10-16 10:11:12,888 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,888 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=5, lineno=3704)\n", - "2024-10-16 10:11:12,888 - numba.core.byteflow - DEBUG - stack ['$12load_global.0']\n", - "2024-10-16 10:11:12,889 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_CONST(arg=1, lineno=3704)\n", - "2024-10-16 10:11:12,889 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1']\n", - "2024-10-16 10:11:12,890 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=2, lineno=3704)\n", - "2024-10-16 10:11:12,890 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2']\n", - "2024-10-16 10:11:12,890 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=CALL_FUNCTION(arg=3, lineno=3704)\n", - "2024-10-16 10:11:12,891 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2', '$const18.3']\n", - "2024-10-16 10:11:12,891 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=GET_ITER(arg=None, lineno=3704)\n", - "2024-10-16 10:11:12,893 - numba.core.byteflow - DEBUG - stack ['$20call_function.4']\n", - "2024-10-16 10:11:12,893 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$22get_iter.5',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,893 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=0), State(pc_initial=24 nstack_initial=1)])\n", - "2024-10-16 10:11:12,894 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,894 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=60 nstack_initial=0)\n", - "2024-10-16 10:11:12,895 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_FAST(arg=2, lineno=3709)\n", - "2024-10-16 10:11:12,895 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,896 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_FAST(arg=1, lineno=3709)\n", - "2024-10-16 10:11:12,896 - numba.core.byteflow - DEBUG - stack ['$v_last60.0']\n", - "2024-10-16 10:11:12,896 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=COMPARE_OP(arg=0, lineno=3709)\n", - "2024-10-16 10:11:12,897 - numba.core.byteflow - DEBUG - stack ['$v_last60.0', '$v62.1']\n", - "2024-10-16 10:11:12,897 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=POP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - "2024-10-16 10:11:12,898 - numba.core.byteflow - DEBUG - stack ['$64compare_op.2']\n", - "2024-10-16 10:11:12,898 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=68, stack=(), blockstack=(), npush=0), Edge(pc=74, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,898 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0)])\n", - "2024-10-16 10:11:12,899 - numba.core.byteflow - DEBUG - stack: ['$phi24.0']\n", - "2024-10-16 10:11:12,899 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=24 nstack_initial=1)\n", - "2024-10-16 10:11:12,900 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=FOR_ITER(arg=15, lineno=3704)\n", - "2024-10-16 10:11:12,900 - numba.core.byteflow - DEBUG - stack ['$phi24.0']\n", - "2024-10-16 10:11:12,900 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=56, stack=(), blockstack=(), npush=0), Edge(pc=26, stack=('$phi24.0', '$24for_iter.2'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,901 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2)])\n", - "2024-10-16 10:11:12,901 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,902 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=68 nstack_initial=0)\n", - "2024-10-16 10:11:12,902 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_FAST(arg=5, lineno=3710)\n", - "2024-10-16 10:11:12,903 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,903 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=STORE_FAST(arg=4, lineno=3710)\n", - "2024-10-16 10:11:12,903 - numba.core.byteflow - DEBUG - stack ['$n68.0']\n", - "2024-10-16 10:11:12,904 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=JUMP_FORWARD(arg=12, lineno=3710)\n", - "2024-10-16 10:11:12,904 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,905 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,905 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:12,905 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,906 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=0)\n", - "2024-10-16 10:11:12,906 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=1, lineno=3712)\n", - "2024-10-16 10:11:12,907 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,907 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=STORE_FAST(arg=3, lineno=3712)\n", - "2024-10-16 10:11:12,907 - numba.core.byteflow - DEBUG - stack ['$const74.0']\n", - "2024-10-16 10:11:12,908 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-10-16 10:11:12,908 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,909 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-10-16 10:11:12,909 - numba.core.byteflow - DEBUG - stack ['$hi78.1']\n", - "2024-10-16 10:11:12,910 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=COMPARE_OP(arg=0, lineno=3713)\n", - "2024-10-16 10:11:12,910 - numba.core.byteflow - DEBUG - stack ['$hi78.1', '$n80.2']\n", - "2024-10-16 10:11:12,910 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=POP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - "2024-10-16 10:11:12,911 - numba.core.byteflow - DEBUG - stack ['$82compare_op.3']\n", - "2024-10-16 10:11:12,911 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=86, stack=(), blockstack=(), npush=0), Edge(pc=94, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,912 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-10-16 10:11:12,912 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,912 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=0)\n", - "2024-10-16 10:11:12,913 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_CONST(arg=1, lineno=3707)\n", - "2024-10-16 10:11:12,913 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,914 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=RETURN_VALUE(arg=None, lineno=3707)\n", - "2024-10-16 10:11:12,914 - numba.core.byteflow - DEBUG - stack ['$const56.0']\n", - "2024-10-16 10:11:12,914 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:12,915 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-10-16 10:11:12,915 - numba.core.byteflow - DEBUG - stack: ['$phi26.0', '$phi26.1']\n", - "2024-10-16 10:11:12,916 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=26 nstack_initial=2)\n", - "2024-10-16 10:11:12,916 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=STORE_FAST(arg=6, lineno=3704)\n", - "2024-10-16 10:11:12,916 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$phi26.1']\n", - "2024-10-16 10:11:12,917 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_GLOBAL(arg=0, lineno=3705)\n", - "2024-10-16 10:11:12,917 - numba.core.byteflow - DEBUG - stack ['$phi26.0']\n", - "2024-10-16 10:11:12,918 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_METHOD(arg=1, lineno=3705)\n", - "2024-10-16 10:11:12,918 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$28load_global.2']\n", - "2024-10-16 10:11:12,918 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_FAST(arg=0, lineno=3705)\n", - "2024-10-16 10:11:12,919 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3']\n", - "2024-10-16 10:11:12,919 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=6, lineno=3705)\n", - "2024-10-16 10:11:12,920 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4']\n", - "2024-10-16 10:11:12,920 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_CONST(arg=3, lineno=3705)\n", - "2024-10-16 10:11:12,921 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5']\n", - "2024-10-16 10:11:12,921 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=BINARY_SUBTRACT(arg=None, lineno=3705)\n", - "2024-10-16 10:11:12,921 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5', '$const36.6']\n", - "2024-10-16 10:11:12,922 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=BINARY_SUBSCR(arg=None, lineno=3705)\n", - "2024-10-16 10:11:12,922 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$38binary_subtract.7']\n", - "2024-10-16 10:11:12,923 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=CALL_METHOD(arg=1, lineno=3705)\n", - "2024-10-16 10:11:12,923 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$40binary_subscr.8']\n", - "2024-10-16 10:11:12,923 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - "2024-10-16 10:11:12,924 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$42call_method.9']\n", - "2024-10-16 10:11:12,924 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=('$phi26.0',), blockstack=(), npush=0), Edge(pc=54, stack=('$phi26.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,925 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1)])\n", - "2024-10-16 10:11:12,925 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,926 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=98 nstack_initial=0)\n", - "2024-10-16 10:11:12,926 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-10-16 10:11:12,926 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,927 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-10-16 10:11:12,927 - numba.core.byteflow - DEBUG - stack ['$hi98.0']\n", - "2024-10-16 10:11:12,928 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-10-16 10:11:12,928 - numba.core.byteflow - DEBUG - stack ['$hi98.0', '$lo100.1']\n", - "2024-10-16 10:11:12,928 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=POP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "2024-10-16 10:11:12,929 - numba.core.byteflow - DEBUG - stack ['$102compare_op.2']\n", - "2024-10-16 10:11:12,929 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=106, stack=(), blockstack=(), npush=0), Edge(pc=154, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,930 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0)])\n", - "2024-10-16 10:11:12,930 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,930 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=86 nstack_initial=0)\n", - "2024-10-16 10:11:12,931 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-10-16 10:11:12,940 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,941 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_CONST(arg=3, lineno=3713)\n", - "2024-10-16 10:11:12,941 - numba.core.byteflow - DEBUG - stack ['$hi86.0']\n", - "2024-10-16 10:11:12,942 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=BINARY_ADD(arg=None, lineno=3713)\n", - "2024-10-16 10:11:12,943 - numba.core.byteflow - DEBUG - stack ['$hi86.0', '$const88.1']\n", - "2024-10-16 10:11:12,943 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=JUMP_FORWARD(arg=1, lineno=3713)\n", - "2024-10-16 10:11:12,944 - numba.core.byteflow - DEBUG - stack ['$90binary_add.2']\n", - "2024-10-16 10:11:12,944 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$90binary_add.2',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,945 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1)])\n", - "2024-10-16 10:11:12,945 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,946 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=94 nstack_initial=0)\n", - "2024-10-16 10:11:12,946 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-10-16 10:11:12,947 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,947 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$n94.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,948 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-10-16 10:11:12,949 - numba.core.byteflow - DEBUG - stack: ['$phi46.0']\n", - "2024-10-16 10:11:12,950 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=1)\n", - "2024-10-16 10:11:12,950 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=6, lineno=3706)\n", - "2024-10-16 10:11:12,951 - numba.core.byteflow - DEBUG - stack ['$phi46.0']\n", - "2024-10-16 10:11:12,951 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=ROT_TWO(arg=None, lineno=3706)\n", - "2024-10-16 10:11:12,952 - numba.core.byteflow - DEBUG - stack ['$phi46.0', '$i46.1']\n", - "2024-10-16 10:11:12,952 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=POP_TOP(arg=None, lineno=3706)\n", - "2024-10-16 10:11:12,954 - numba.core.byteflow - DEBUG - stack ['$i46.1', '$phi46.0']\n", - "2024-10-16 10:11:12,954 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=RETURN_VALUE(arg=None, lineno=3706)\n", - "2024-10-16 10:11:12,955 - numba.core.byteflow - DEBUG - stack ['$i46.1']\n", - "2024-10-16 10:11:12,955 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:12,956 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-10-16 10:11:12,957 - numba.core.byteflow - DEBUG - stack: ['$phi54.0']\n", - "2024-10-16 10:11:12,957 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=1)\n", - "2024-10-16 10:11:12,958 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=JUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "2024-10-16 10:11:12,959 - numba.core.byteflow - DEBUG - stack ['$phi54.0']\n", - "2024-10-16 10:11:12,959 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$phi54.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,960 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1)])\n", - "2024-10-16 10:11:12,960 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,961 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=106 nstack_initial=0)\n", - "2024-10-16 10:11:12,962 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_FAST(arg=3, lineno=3716)\n", - "2024-10-16 10:11:12,962 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,963 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_FAST(arg=4, lineno=3716)\n", - "2024-10-16 10:11:12,964 - numba.core.byteflow - DEBUG - stack ['$lo106.0']\n", - "2024-10-16 10:11:12,964 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=BINARY_ADD(arg=None, lineno=3716)\n", - "2024-10-16 10:11:12,965 - numba.core.byteflow - DEBUG - stack ['$lo106.0', '$hi108.1']\n", - "2024-10-16 10:11:12,966 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=3, lineno=3716)\n", - "2024-10-16 10:11:12,966 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2']\n", - "2024-10-16 10:11:12,967 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BINARY_RSHIFT(arg=None, lineno=3716)\n", - "2024-10-16 10:11:12,968 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2', '$const112.3']\n", - "2024-10-16 10:11:12,968 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=STORE_FAST(arg=7, lineno=3716)\n", - "2024-10-16 10:11:12,969 - numba.core.byteflow - DEBUG - stack ['$114binary_rshift.4']\n", - "2024-10-16 10:11:12,969 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_DEREF(arg=0, lineno=3717)\n", - "2024-10-16 10:11:12,970 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,971 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=0, lineno=3717)\n", - "2024-10-16 10:11:12,971 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5']\n", - "2024-10-16 10:11:12,972 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_FAST(arg=7, lineno=3717)\n", - "2024-10-16 10:11:12,973 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6']\n", - "2024-10-16 10:11:12,973 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=BINARY_SUBSCR(arg=None, lineno=3717)\n", - "2024-10-16 10:11:12,974 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6', '$mid122.7']\n", - "2024-10-16 10:11:12,975 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_FAST(arg=1, lineno=3717)\n", - "2024-10-16 10:11:12,975 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8']\n", - "2024-10-16 10:11:12,976 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=CALL_FUNCTION(arg=2, lineno=3717)\n", - "2024-10-16 10:11:12,976 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8', '$v126.9']\n", - "2024-10-16 10:11:12,977 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=POP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - "2024-10-16 10:11:12,977 - numba.core.byteflow - DEBUG - stack ['$128call_function.10']\n", - "2024-10-16 10:11:12,978 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=132, stack=(), blockstack=(), npush=0), Edge(pc=142, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,979 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-10-16 10:11:12,980 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,980 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=154 nstack_initial=0)\n", - "2024-10-16 10:11:12,981 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_FAST(arg=3, lineno=3723)\n", - "2024-10-16 10:11:12,981 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,982 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=RETURN_VALUE(arg=None, lineno=3723)\n", - "2024-10-16 10:11:12,982 - numba.core.byteflow - DEBUG - stack ['$lo154.0']\n", - "2024-10-16 10:11:12,983 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:12,983 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-10-16 10:11:12,983 - numba.core.byteflow - DEBUG - stack: ['$phi96.0']\n", - "2024-10-16 10:11:12,985 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=96 nstack_initial=1)\n", - "2024-10-16 10:11:12,986 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=STORE_FAST(arg=4, lineno=3713)\n", - "2024-10-16 10:11:12,986 - numba.core.byteflow - DEBUG - stack ['$phi96.0']\n", - "2024-10-16 10:11:12,986 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,987 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:12,987 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:12,988 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:12,989 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,989 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=132 nstack_initial=0)\n", - "2024-10-16 10:11:12,990 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_FAST(arg=7, lineno=3719)\n", - "2024-10-16 10:11:12,990 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,991 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_CONST(arg=3, lineno=3719)\n", - "2024-10-16 10:11:12,991 - numba.core.byteflow - DEBUG - stack ['$mid132.0']\n", - "2024-10-16 10:11:12,992 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BINARY_ADD(arg=None, lineno=3719)\n", - "2024-10-16 10:11:12,992 - numba.core.byteflow - DEBUG - stack ['$mid132.0', '$const134.1']\n", - "2024-10-16 10:11:12,993 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=STORE_FAST(arg=3, lineno=3719)\n", - "2024-10-16 10:11:12,993 - numba.core.byteflow - DEBUG - stack ['$136binary_add.2']\n", - "2024-10-16 10:11:12,994 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=JUMP_FORWARD(arg=2, lineno=3719)\n", - "2024-10-16 10:11:12,994 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,995 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,995 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-10-16 10:11:12,996 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:12,996 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=142 nstack_initial=0)\n", - "2024-10-16 10:11:12,996 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=7, lineno=3722)\n", - "2024-10-16 10:11:12,997 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:12,997 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=STORE_FAST(arg=4, lineno=3722)\n", - "2024-10-16 10:11:12,998 - numba.core.byteflow - DEBUG - stack ['$mid142.0']\n", - "2024-10-16 10:11:12,999 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:12,999 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-10-16 10:11:13,000 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-10-16 10:11:13,000 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,001 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=146 nstack_initial=0)\n", - "2024-10-16 10:11:13,001 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-10-16 10:11:13,005 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,005 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-10-16 10:11:13,006 - numba.core.byteflow - DEBUG - stack ['$hi146.0']\n", - "2024-10-16 10:11:13,007 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-10-16 10:11:13,007 - numba.core.byteflow - DEBUG - stack ['$hi146.0', '$lo148.1']\n", - "2024-10-16 10:11:13,008 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=POP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "2024-10-16 10:11:13,009 - numba.core.byteflow - DEBUG - stack ['$150compare_op.2']\n", - "2024-10-16 10:11:13,009 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=154, stack=(), blockstack=(), npush=0), Edge(pc=106, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:13,010 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-10-16 10:11:13,010 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-10-16 10:11:13,011 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0)])\n", - "2024-10-16 10:11:13,011 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:13,012 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=12 nstack_initial=0): set(),\n", - " State(pc_initial=24 nstack_initial=1): {'$phi24.0'},\n", - " State(pc_initial=26 nstack_initial=2): {'$phi26.1'},\n", - " State(pc_initial=46 nstack_initial=1): set(),\n", - " State(pc_initial=54 nstack_initial=1): set(),\n", - " State(pc_initial=56 nstack_initial=0): set(),\n", - " State(pc_initial=60 nstack_initial=0): set(),\n", - " State(pc_initial=68 nstack_initial=0): set(),\n", - " State(pc_initial=74 nstack_initial=0): set(),\n", - " State(pc_initial=86 nstack_initial=0): set(),\n", - " State(pc_initial=94 nstack_initial=0): set(),\n", - " State(pc_initial=96 nstack_initial=1): {'$phi96.0'},\n", - " State(pc_initial=98 nstack_initial=0): set(),\n", - " State(pc_initial=106 nstack_initial=0): set(),\n", - " State(pc_initial=132 nstack_initial=0): set(),\n", - " State(pc_initial=142 nstack_initial=0): set(),\n", - " State(pc_initial=146 nstack_initial=0): set(),\n", - " State(pc_initial=154 nstack_initial=0): set()})\n", - "2024-10-16 10:11:13,013 - numba.core.byteflow - DEBUG - defmap: {'$phi24.0': State(pc_initial=12 nstack_initial=0),\n", - " '$phi26.1': State(pc_initial=24 nstack_initial=1),\n", - " '$phi96.0': State(pc_initial=86 nstack_initial=0)}\n", - "2024-10-16 10:11:13,014 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi54.0', State(pc_initial=54 nstack_initial=1))},\n", - " '$phi26.0': {('$phi24.0', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi54.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:13,015 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:13,016 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:13,018 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:13,019 - numba.core.byteflow - DEBUG - keep phismap: {'$phi24.0': {('$22get_iter.5', State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi96.0': {('$90binary_add.2', State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}}\n", - "2024-10-16 10:11:13,020 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=12 nstack_initial=0): {'$phi24.0': '$22get_iter.5'},\n", - " State(pc_initial=24 nstack_initial=1): {'$phi26.1': '$24for_iter.2'},\n", - " State(pc_initial=86 nstack_initial=0): {'$phi96.0': '$90binary_add.2'},\n", - " State(pc_initial=94 nstack_initial=0): {'$phi96.0': '$n94.0'}})\n", - "2024-10-16 10:11:13,021 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:13,021 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_method.1'}), (6, {'res': '$v6.2'}), (8, {'func': '$4load_method.1', 'args': ['$v6.2'], 'res': '$8call_method.3'}), (10, {'pred': '$8call_method.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={12: (), 60: ()})\n", - "2024-10-16 10:11:13,022 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=12 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((12, {'res': '$12load_global.0'}), (14, {'res': '$n14.1'}), (16, {'res': '$const16.2'}), (18, {'res': '$const18.3'}), (20, {'func': '$12load_global.0', 'args': ['$n14.1', '$const16.2', '$const18.3'], 'res': '$20call_function.4'}), (22, {'value': '$20call_function.4', 'res': '$22get_iter.5'})), outgoing_phis={'$phi24.0': '$22get_iter.5'}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$22get_iter.5',)})\n", - "2024-10-16 10:11:13,022 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=24 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((24, {'iterator': '$phi24.0', 'pair': '$24for_iter.1', 'indval': '$24for_iter.2', 'pred': '$24for_iter.3'}),), outgoing_phis={'$phi26.1': '$24for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={56: (), 26: ('$phi24.0', '$24for_iter.2')})\n", - "2024-10-16 10:11:13,023 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=26 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((26, {'value': '$phi26.1'}), (28, {'res': '$28load_global.2'}), (30, {'item': '$28load_global.2', 'res': '$30load_method.3'}), (32, {'res': '$a32.4'}), (34, {'res': '$i34.5'}), (36, {'res': '$const36.6'}), (38, {'lhs': '$i34.5', 'rhs': '$const36.6', 'res': '$38binary_subtract.7'}), (40, {'index': '$38binary_subtract.7', 'target': '$a32.4', 'res': '$40binary_subscr.8'}), (42, {'func': '$30load_method.3', 'args': ['$40binary_subscr.8'], 'res': '$42call_method.9'}), (44, {'pred': '$42call_method.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: ('$phi26.0',), 54: ('$phi26.0',)})\n", - "2024-10-16 10:11:13,024 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((46, {'res': '$i46.1'}), (52, {'retval': '$i46.1', 'castval': '$52return_value.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:13,025 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((54, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$phi54.0',)})\n", - "2024-10-16 10:11:13,025 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((56, {'res': '$const56.0'}), (58, {'retval': '$const56.0', 'castval': '$58return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:13,026 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=60 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((60, {'res': '$v_last60.0'}), (62, {'res': '$v62.1'}), (64, {'lhs': '$v_last60.0', 'rhs': '$v62.1', 'res': '$64compare_op.2'}), (66, {'pred': '$64compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={68: (), 74: ()})\n", - "2024-10-16 10:11:13,027 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=68 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((68, {'res': '$n68.0'}), (70, {'value': '$n68.0'}), (72, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-10-16 10:11:13,027 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((74, {'res': '$const74.0'}), (76, {'value': '$const74.0'}), (78, {'res': '$hi78.1'}), (80, {'res': '$n80.2'}), (82, {'lhs': '$hi78.1', 'rhs': '$n80.2', 'res': '$82compare_op.3'}), (84, {'pred': '$82compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={86: (), 94: ()})\n", - "2024-10-16 10:11:13,028 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=86 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((86, {'res': '$hi86.0'}), (88, {'res': '$const88.1'}), (90, {'lhs': '$hi86.0', 'rhs': '$const88.1', 'res': '$90binary_add.2'}), (92, {})), outgoing_phis={'$phi96.0': '$90binary_add.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$90binary_add.2',)})\n", - "2024-10-16 10:11:13,029 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=94 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((94, {'res': '$n94.0'}),), outgoing_phis={'$phi96.0': '$n94.0'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$n94.0',)})\n", - "2024-10-16 10:11:13,029 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=96 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((96, {'value': '$phi96.0'}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-10-16 10:11:13,030 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=98 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((98, {'res': '$hi98.0'}), (100, {'res': '$lo100.1'}), (102, {'lhs': '$hi98.0', 'rhs': '$lo100.1', 'res': '$102compare_op.2'}), (104, {'pred': '$102compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={106: (), 154: ()})\n", - "2024-10-16 10:11:13,030 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=106 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((106, {'res': '$lo106.0'}), (108, {'res': '$hi108.1'}), (110, {'lhs': '$lo106.0', 'rhs': '$hi108.1', 'res': '$110binary_add.2'}), (112, {'res': '$const112.3'}), (114, {'lhs': '$110binary_add.2', 'rhs': '$const112.3', 'res': '$114binary_rshift.4'}), (116, {'value': '$114binary_rshift.4'}), (118, {'res': '$118load_deref.5'}), (120, {'res': '$a120.6'}), (122, {'res': '$mid122.7'}), (124, {'index': '$mid122.7', 'target': '$a120.6', 'res': '$124binary_subscr.8'}), (126, {'res': '$v126.9'}), (128, {'func': '$118load_deref.5', 'args': ['$124binary_subscr.8', '$v126.9'], 'res': '$128call_function.10'}), (130, {'pred': '$128call_function.10'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={132: (), 142: ()})\n", - "2024-10-16 10:11:13,031 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=132 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((132, {'res': '$mid132.0'}), (134, {'res': '$const134.1'}), (136, {'lhs': '$mid132.0', 'rhs': '$const134.1', 'res': '$136binary_add.2'}), (138, {'value': '$136binary_add.2'}), (140, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-10-16 10:11:13,032 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=142 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((142, {'res': '$mid142.0'}), (144, {'value': '$mid142.0'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-10-16 10:11:13,033 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=146 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((146, {'res': '$hi146.0'}), (148, {'res': '$lo148.1'}), (150, {'lhs': '$hi146.0', 'rhs': '$lo148.1', 'res': '$150compare_op.2'}), (152, {'pred': '$150compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={154: (), 106: ()})\n", - "2024-10-16 10:11:13,033 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=154 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((154, {'res': '$lo154.0'}), (156, {'retval': '$lo154.0', 'castval': '$156return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:13,040 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " v_last = arg(2, name=v_last) ['v_last']\n", - " lo = arg(3, name=lo) ['lo']\n", - " hi = arg(4, name=hi) ['hi']\n", - " n = arg(5, name=n) ['n']\n", - " $2load_global.0 = global(np: ) ['$2load_global.0']\n", - " $4load_method.1 = getattr(value=$2load_global.0, attr=isnan) ['$2load_global.0', '$4load_method.1']\n", - " $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$8call_method.3', 'v']\n", - " bool10 = global(bool: ) ['bool10']\n", - " $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None) ['$10pred', '$8call_method.3', 'bool10']\n", - " branch $10pred, 12, 60 ['$10pred']\n", - "label 12:\n", - " $12load_global.0 = global(range: ) ['$12load_global.0']\n", - " $const16.2 = const(int, 0) ['$const16.2']\n", - " $const18.3 = const(int, -1) ['$const18.3']\n", - " $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_global.0', '$20call_function.4', '$const16.2', '$const18.3', 'n']\n", - " $22get_iter.5 = getiter(value=$20call_function.4) ['$20call_function.4', '$22get_iter.5']\n", - " $phi24.0 = $22get_iter.5 ['$22get_iter.5', '$phi24.0']\n", - " jump 24 []\n", - "label 24:\n", - " $24for_iter.1 = iternext(value=$phi24.0) ['$24for_iter.1', '$phi24.0']\n", - " $24for_iter.2 = pair_first(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.2']\n", - " $24for_iter.3 = pair_second(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.3']\n", - " $phi26.1 = $24for_iter.2 ['$24for_iter.2', '$phi26.1']\n", - " branch $24for_iter.3, 26, 56 ['$24for_iter.3']\n", - "label 26:\n", - " i = $phi26.1 ['$phi26.1', 'i']\n", - " $28load_global.2 = global(np: ) ['$28load_global.2']\n", - " $30load_method.3 = getattr(value=$28load_global.2, attr=isnan) ['$28load_global.2', '$30load_method.3']\n", - " $const36.6 = const(int, 1) ['$const36.6']\n", - " $38binary_subtract.7 = i - $const36.6 ['$38binary_subtract.7', '$const36.6', 'i']\n", - " $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=) ['$38binary_subtract.7', '$40binary_subscr.8', 'a']\n", - " $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None) ['$30load_method.3', '$40binary_subscr.8', '$42call_method.9']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None) ['$42call_method.9', '$44pred', 'bool44']\n", - " branch $44pred, 54, 46 ['$44pred']\n", - "label 46:\n", - " $52return_value.2 = cast(value=i) ['$52return_value.2', 'i']\n", - " return $52return_value.2 ['$52return_value.2']\n", - "label 54:\n", - " jump 24 []\n", - "label 56:\n", - " $const56.0 = const(int, 0) ['$const56.0']\n", - " $58return_value.1 = cast(value=$const56.0) ['$58return_value.1', '$const56.0']\n", - " return $58return_value.1 ['$58return_value.1']\n", - "label 60:\n", - " $64compare_op.2 = v_last < v ['$64compare_op.2', 'v', 'v_last']\n", - " bool66 = global(bool: ) ['bool66']\n", - " $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None) ['$64compare_op.2', '$66pred', 'bool66']\n", - " branch $66pred, 68, 74 ['$66pred']\n", - "label 68:\n", - " hi = n ['hi', 'n']\n", - " jump 98 []\n", - "label 74:\n", - " lo = const(int, 0) ['lo']\n", - " $82compare_op.3 = hi < n ['$82compare_op.3', 'hi', 'n']\n", - " bool84 = global(bool: ) ['bool84']\n", - " $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None) ['$82compare_op.3', '$84pred', 'bool84']\n", - " branch $84pred, 86, 94 ['$84pred']\n", - "label 86:\n", - " $const88.1 = const(int, 1) ['$const88.1']\n", - " $90binary_add.2 = hi + $const88.1 ['$90binary_add.2', '$const88.1', 'hi']\n", - " $phi96.0 = $90binary_add.2 ['$90binary_add.2', '$phi96.0']\n", - " jump 96 []\n", - "label 94:\n", - " $phi96.0 = n ['$phi96.0', 'n']\n", - " jump 96 []\n", - "label 96:\n", - " hi = $phi96.0 ['$phi96.0', 'hi']\n", - " jump 98 []\n", - "label 98:\n", - " $102compare_op.2 = hi > lo ['$102compare_op.2', 'hi', 'lo']\n", - " bool104 = global(bool: ) ['bool104']\n", - " $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$102compare_op.2', '$104pred', 'bool104']\n", - " branch $104pred, 106, 154 ['$104pred']\n", - "label 106:\n", - " $110binary_add.2 = lo + hi ['$110binary_add.2', 'hi', 'lo']\n", - " $const112.3 = const(int, 1) ['$const112.3']\n", - " mid = $110binary_add.2 >> $const112.3 ['$110binary_add.2', '$const112.3', 'mid']\n", - " $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>) ['$118load_deref.5']\n", - " $124binary_subscr.8 = getitem(value=a, index=mid, fn=) ['$124binary_subscr.8', 'a', 'mid']\n", - " $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$118load_deref.5', '$124binary_subscr.8', '$128call_function.10', 'v']\n", - " bool130 = global(bool: ) ['bool130']\n", - " $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None) ['$128call_function.10', '$130pred', 'bool130']\n", - " branch $130pred, 132, 142 ['$130pred']\n", - "label 132:\n", - " $const134.1 = const(int, 1) ['$const134.1']\n", - " lo = mid + $const134.1 ['$const134.1', 'lo', 'mid']\n", - " jump 146 []\n", - "label 142:\n", - " hi = mid ['hi', 'mid']\n", - " jump 146 []\n", - "label 146:\n", - " $150compare_op.2 = hi > lo ['$150compare_op.2', 'hi', 'lo']\n", - " bool152 = global(bool: ) ['bool152']\n", - " $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$150compare_op.2', '$152pred', 'bool152']\n", - " branch $152pred, 106, 154 ['$152pred']\n", - "label 154:\n", - " $156return_value.1 = cast(value=lo) ['$156return_value.1', 'lo']\n", - " return $156return_value.1 ['$156return_value.1']\n", - "\n", - "2024-10-16 10:11:13,074 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:13,074 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,075 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:13,075 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:13,076 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:13,077 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:13,077 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:13,078 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:13,078 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:13,079 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:13,079 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,080 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:13,080 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,081 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:13,081 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 12\n", - "2024-10-16 10:11:13,083 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,083 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:13,084 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:13,084 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:13,085 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,085 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:13,086 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:13,086 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,087 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 24\n", - "2024-10-16 10:11:13,087 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,088 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:13,088 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,089 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,089 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:13,089 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:13,090 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 26\n", - "2024-10-16 10:11:13,090 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,091 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:13,091 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:13,092 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:13,092 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:13,092 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:13,093 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:13,093 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,094 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:13,094 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,095 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:13,095 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-10-16 10:11:13,096 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,096 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:13,100 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:13,100 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-10-16 10:11:13,101 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,101 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,102 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-10-16 10:11:13,102 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,102 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:13,103 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:13,103 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:13,104 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 60\n", - "2024-10-16 10:11:13,104 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,104 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:13,105 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:13,105 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,106 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:13,106 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 68\n", - "2024-10-16 10:11:13,107 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,107 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:13,107 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,108 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-10-16 10:11:13,108 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,109 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-10-16 10:11:13,109 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:13,110 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:13,110 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,110 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:13,111 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 86\n", - "2024-10-16 10:11:13,111 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,112 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:13,112 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:13,112 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:13,117 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,117 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 94\n", - "2024-10-16 10:11:13,118 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,118 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:13,119 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,119 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 96\n", - "2024-10-16 10:11:13,120 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,120 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:13,120 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,121 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 98\n", - "2024-10-16 10:11:13,121 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,122 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:13,122 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:13,123 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,123 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:13,123 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 106\n", - "2024-10-16 10:11:13,124 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,124 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:13,125 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:13,125 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:13,126 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:13,126 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:13,129 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,130 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:13,130 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,131 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:13,132 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 132\n", - "2024-10-16 10:11:13,132 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,133 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:13,133 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-10-16 10:11:13,134 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,135 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 142\n", - "2024-10-16 10:11:13,135 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,136 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:13,136 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,137 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 146\n", - "2024-10-16 10:11:13,137 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,138 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:13,138 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:13,139 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,139 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:13,140 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 154\n", - "2024-10-16 10:11:13,140 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,141 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:13,141 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:13,145 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102compare_op.2': [],\n", - " '$104pred': [],\n", - " '$10pred': [],\n", - " '$110binary_add.2': [],\n", - " '$118load_deref.5': [],\n", - " '$124binary_subscr.8': [],\n", - " '$128call_function.10': [],\n", - " '$12load_global.0': [],\n", - " '$130pred': [],\n", - " '$150compare_op.2': [],\n", - " '$152pred': [],\n", - " '$156return_value.1': [],\n", - " '$20call_function.4': [],\n", - " '$22get_iter.5': [],\n", - " '$24for_iter.1': [],\n", - " '$24for_iter.2': [],\n", - " '$24for_iter.3': [],\n", - " '$28load_global.2': [],\n", - " '$2load_global.0': [],\n", - " '$30load_method.3': [],\n", - " '$38binary_subtract.7': [],\n", - " '$40binary_subscr.8': [],\n", - " '$42call_method.9': [],\n", - " '$44pred': [],\n", - " '$4load_method.1': [],\n", - " '$52return_value.2': [],\n", - " '$58return_value.1': [],\n", - " '$64compare_op.2': [],\n", - " '$66pred': [],\n", - " '$82compare_op.3': [],\n", - " '$84pred': [],\n", - " '$8call_method.3': [],\n", - " '$90binary_add.2': [],\n", - " '$const112.3': [],\n", - " '$const134.1': [],\n", - " '$const16.2': [],\n", - " '$const18.3': [],\n", - " '$const36.6': [],\n", - " '$const56.0': [],\n", - " '$const88.1': [],\n", - " '$phi24.0': [],\n", - " '$phi26.1': [],\n", - " '$phi96.0': [,\n", - " ],\n", - " 'a': [],\n", - " 'bool10': [],\n", - " 'bool104': [],\n", - " 'bool130': [],\n", - " 'bool152': [],\n", - " 'bool44': [],\n", - " 'bool66': [],\n", - " 'bool84': [],\n", - " 'hi': [,\n", - " ,\n", - " ,\n", - " ],\n", - " 'i': [],\n", - " 'lo': [,\n", - " ,\n", - " ],\n", - " 'mid': [],\n", - " 'n': [],\n", - " 'v': [],\n", - " 'v_last': []})\n", - "2024-10-16 10:11:13,146 - numba.core.ssa - DEBUG - SSA violators {'lo', 'hi', '$phi96.0'}\n", - "2024-10-16 10:11:13,146 - numba.core.ssa - DEBUG - Fix SSA violator on var lo\n", - "2024-10-16 10:11:13,147 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:13,147 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,147 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:13,148 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:13,150 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:13,150 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:13,151 - numba.core.ssa - DEBUG - first assign: lo\n", - "2024-10-16 10:11:13,151 - numba.core.ssa - DEBUG - replaced with: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:13,152 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:13,153 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:13,153 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:13,154 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:13,154 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,155 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:13,155 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,156 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:13,157 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:13,158 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,158 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:13,159 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:13,160 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:13,160 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,161 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:13,162 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:13,162 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,163 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:13,164 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,164 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:13,165 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,165 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,166 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:13,167 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:13,167 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:13,168 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,168 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:13,169 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:13,170 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:13,171 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:13,171 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:13,172 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:13,173 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,173 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:13,174 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,174 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:13,175 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:13,175 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,176 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:13,177 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:13,177 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:13,178 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,179 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,179 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:13,180 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,180 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:13,181 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:13,181 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:13,183 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:13,183 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,184 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:13,184 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:13,185 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,185 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:13,186 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:13,187 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,188 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:13,188 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,189 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:13,189 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,190 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-10-16 10:11:13,190 - numba.core.ssa - DEBUG - replaced with: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:13,191 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:13,191 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:13,192 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,194 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:13,194 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:13,195 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,195 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:13,196 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:13,197 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:13,197 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,198 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:13,199 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,199 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:13,200 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,200 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:13,201 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,202 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:13,202 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,203 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:13,203 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,204 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:13,205 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:13,205 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,206 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:13,207 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:13,208 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,208 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:13,209 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:13,209 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:13,210 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:13,210 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:13,211 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,212 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:13,213 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,213 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:13,214 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:13,214 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,215 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:13,215 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-10-16 10:11:13,216 - numba.core.ssa - DEBUG - replaced with: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:13,217 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,217 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:13,218 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,218 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:13,219 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,219 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:13,220 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,220 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:13,221 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:13,221 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,222 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:13,222 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:13,223 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,223 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:13,224 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:13,224 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 74: [],\n", - " 132: []})\n", - "2024-10-16 10:11:13,225 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:13,225 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,226 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:13,226 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:13,227 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:13,227 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:13,228 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:13,228 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:13,229 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:13,229 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:13,229 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,230 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:13,231 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,231 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:13,232 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:13,232 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,236 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:13,237 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:13,237 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:13,238 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,239 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:13,239 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:13,240 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,240 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:13,241 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,242 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:13,242 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,243 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,244 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:13,244 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:13,245 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:13,245 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,246 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:13,247 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:13,247 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:13,248 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:13,248 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:13,249 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:13,249 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,250 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:13,250 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,251 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:13,252 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:13,252 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,253 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:13,253 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:13,254 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:13,254 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,255 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,255 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:13,256 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,256 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:13,257 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:13,257 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:13,258 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:13,258 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,259 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:13,259 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:13,260 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,265 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:13,266 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:13,266 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,267 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:13,268 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,269 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:13,269 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,269 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:13,270 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:13,271 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:13,271 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,272 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:13,272 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:13,273 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,273 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:13,274 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:13,275 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:13,276 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,276 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:13,277 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,278 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:13,278 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,279 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:13,279 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,280 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:13,281 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,281 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:13,282 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,282 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:13,283 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:13,283 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-10-16 10:11:13,284 - numba.core.ssa - DEBUG - insert phi node lo.3 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-10-16 10:11:13,284 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-10-16 10:11:13,285 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-10-16 10:11:13,285 - numba.core.ssa - DEBUG - idom 74 from label 96\n", - "2024-10-16 10:11:13,286 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-10-16 10:11:13,286 - numba.core.ssa - DEBUG - incoming_def lo.1 = const(int, 0)\n", - "2024-10-16 10:11:13,287 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:13,287 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-10-16 10:11:13,288 - numba.core.ssa - DEBUG - idom 60 from label 68\n", - "2024-10-16 10:11:13,288 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-10-16 10:11:13,289 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-10-16 10:11:13,289 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-10-16 10:11:13,289 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:13,290 - numba.core.ssa - DEBUG - incoming_def lo = arg(3, name=lo)\n", - "2024-10-16 10:11:13,291 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:13,291 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:13,292 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,292 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:13,293 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:13,293 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,293 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:13,294 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:13,294 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-10-16 10:11:13,295 - numba.core.ssa - DEBUG - insert phi node lo.4 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-10-16 10:11:13,299 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-10-16 10:11:13,299 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:13,300 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-10-16 10:11:13,300 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-10-16 10:11:13,301 - numba.core.ssa - DEBUG - insert phi node lo.5 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-10-16 10:11:13,302 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-10-16 10:11:13,302 - numba.core.ssa - DEBUG - incoming_def lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:13,303 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-10-16 10:11:13,303 - numba.core.ssa - DEBUG - find_def_from_top label 142\n", - "2024-10-16 10:11:13,305 - numba.core.ssa - DEBUG - idom 106 from label 142\n", - "2024-10-16 10:11:13,305 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-10-16 10:11:13,306 - numba.core.ssa - DEBUG - incoming_def lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-10-16 10:11:13,306 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:13,307 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:13,307 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:13,308 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:13,308 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:13,309 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:13,310 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,311 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:13,312 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,312 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:13,313 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:13,314 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,314 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:13,315 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:13,315 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,316 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:13,316 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,317 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:13,317 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,318 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:13,318 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,319 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:13,319 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:13,320 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:13,320 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:13,322 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,323 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:13,323 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:13,324 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,324 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:13,325 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:13,325 - numba.core.ssa - DEBUG - find_def_from_top label 154\n", - "2024-10-16 10:11:13,327 - numba.core.ssa - DEBUG - insert phi node lo.6 = phi(incoming_values=[], incoming_blocks=[]) at 154\n", - "2024-10-16 10:11:13,327 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-10-16 10:11:13,328 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:13,328 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-10-16 10:11:13,329 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:13,329 - numba.core.ssa - DEBUG - replaced with: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:13,330 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:13,330 - numba.core.ssa - DEBUG - Fix SSA violator on var hi\n", - "2024-10-16 10:11:13,331 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:13,331 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,332 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:13,333 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:13,334 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:13,334 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:13,335 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:13,335 - numba.core.ssa - DEBUG - first assign: hi\n", - "2024-10-16 10:11:13,336 - numba.core.ssa - DEBUG - replaced with: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:13,336 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:13,337 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:13,337 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:13,338 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,338 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:13,339 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,339 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:13,341 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:13,342 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,342 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:13,343 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:13,343 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:13,344 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,344 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:13,345 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:13,346 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,346 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:13,347 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,347 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:13,348 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,348 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,348 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:13,349 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:13,349 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:13,350 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,350 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:13,351 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:13,351 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:13,352 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:13,352 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:13,353 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:13,353 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,354 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:13,357 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,357 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:13,358 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:13,358 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,359 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:13,359 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:13,359 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:13,360 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,360 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,361 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:13,361 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,362 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:13,362 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:13,363 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:13,363 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:13,364 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,364 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:13,365 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:13,365 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,366 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:13,366 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:13,367 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,367 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:13,368 - numba.core.ssa - DEBUG - replaced with: hi.1 = n\n", - "2024-10-16 10:11:13,368 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,369 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:13,369 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,369 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:13,370 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:13,370 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:13,371 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,371 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:13,372 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:13,372 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,373 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:13,373 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:13,374 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:13,378 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,379 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:13,379 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,380 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:13,380 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,381 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:13,381 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,382 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:13,382 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0\n", - "2024-10-16 10:11:13,383 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,383 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:13,384 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,384 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:13,385 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:13,385 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:13,386 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,386 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:13,387 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:13,387 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,389 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,390 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:13,390 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:13,391 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:13,391 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:13,392 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:13,392 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,394 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:13,394 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,395 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:13,395 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:13,396 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,396 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:13,397 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:13,398 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,398 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:13,399 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,399 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:13,400 - numba.core.ssa - DEBUG - replaced with: hi.3 = mid\n", - "2024-10-16 10:11:13,400 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,401 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:13,402 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,403 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:13,403 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:13,404 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:13,404 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,405 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:13,405 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:13,406 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,407 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,407 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:13,408 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:13,409 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 68: [],\n", - " 96: [],\n", - " 142: []})\n", - "2024-10-16 10:11:13,409 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:13,410 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,411 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:13,411 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:13,412 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:13,413 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:13,413 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:13,414 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:13,414 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:13,414 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:13,415 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,416 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:13,416 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,417 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:13,417 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:13,417 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,418 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:13,419 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:13,419 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:13,420 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,420 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:13,420 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:13,421 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,421 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:13,422 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,422 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:13,423 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,423 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,424 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:13,424 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:13,425 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:13,428 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,429 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:13,429 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:13,430 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:13,431 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:13,431 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:13,432 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:13,432 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,433 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:13,434 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,434 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:13,435 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:13,435 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,436 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:13,436 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:13,437 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:13,437 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,438 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,438 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:13,440 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,440 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:13,441 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:13,441 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:13,442 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:13,442 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,443 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:13,444 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:13,445 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,445 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:13,446 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:13,446 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,447 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-10-16 10:11:13,447 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,447 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:13,448 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,448 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:13,449 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:13,449 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$82compare_op.3 = hi < n\n", - "2024-10-16 10:11:13,450 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-10-16 10:11:13,450 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-10-16 10:11:13,451 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-10-16 10:11:13,451 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-10-16 10:11:13,454 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-10-16 10:11:13,454 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:13,455 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:13,455 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,456 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:13,457 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:13,457 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,458 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:13,458 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:13,459 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:13,460 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-10-16 10:11:13,460 - numba.core.ssa - DEBUG - idom 74 from label 86\n", - "2024-10-16 10:11:13,460 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-10-16 10:11:13,461 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-10-16 10:11:13,462 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-10-16 10:11:13,463 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-10-16 10:11:13,463 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-10-16 10:11:13,464 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-10-16 10:11:13,464 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:13,465 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:13,465 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,466 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:13,466 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,467 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:13,467 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,468 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:13,468 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,469 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-10-16 10:11:13,469 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,469 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:13,470 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,470 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:13,471 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:13,471 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:13,472 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-10-16 10:11:13,472 - numba.core.ssa - DEBUG - insert phi node hi.4 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-10-16 10:11:13,475 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-10-16 10:11:13,476 - numba.core.ssa - DEBUG - incoming_def hi.2 = $phi96.0\n", - "2024-10-16 10:11:13,476 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:13,477 - numba.core.ssa - DEBUG - incoming_def hi.1 = n\n", - "2024-10-16 10:11:13,477 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi.4 > lo.3\n", - "2024-10-16 10:11:13,478 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:13,478 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,479 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:13,479 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:13,480 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,481 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,482 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:13,482 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:13,483 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-10-16 10:11:13,484 - numba.core.ssa - DEBUG - insert phi node hi.5 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-10-16 10:11:13,484 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-10-16 10:11:13,485 - numba.core.ssa - DEBUG - incoming_def hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:13,485 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-10-16 10:11:13,485 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-10-16 10:11:13,486 - numba.core.ssa - DEBUG - insert phi node hi.6 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-10-16 10:11:13,488 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-10-16 10:11:13,488 - numba.core.ssa - DEBUG - find_def_from_top label 132\n", - "2024-10-16 10:11:13,488 - numba.core.ssa - DEBUG - idom 106 from label 132\n", - "2024-10-16 10:11:13,489 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-10-16 10:11:13,489 - numba.core.ssa - DEBUG - incoming_def hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-10-16 10:11:13,490 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-10-16 10:11:13,490 - numba.core.ssa - DEBUG - incoming_def hi.3 = mid\n", - "2024-10-16 10:11:13,491 - numba.core.ssa - DEBUG - incoming_def hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:13,491 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi.5\n", - "2024-10-16 10:11:13,493 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:13,494 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:13,494 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:13,495 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:13,495 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,495 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:13,496 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,496 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:13,497 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:13,497 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,499 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:13,500 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:13,500 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,501 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:13,501 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,502 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-10-16 10:11:13,503 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,503 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:13,504 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,504 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:13,505 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:13,505 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:13,506 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi.6 > lo.5\n", - "2024-10-16 10:11:13,506 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:13,507 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,508 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:13,509 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:13,510 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,510 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,511 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:13,511 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:13,512 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi96.0\n", - "2024-10-16 10:11:13,512 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:13,513 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,514 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:13,514 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:13,515 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:13,515 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:13,516 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:13,516 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:13,518 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:13,518 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:13,519 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,519 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:13,520 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,520 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:13,521 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:13,521 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,522 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:13,522 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:13,523 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:13,523 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,524 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:13,524 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:13,525 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,525 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:13,526 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,526 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:13,526 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,527 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,527 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:13,528 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:13,528 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:13,529 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,529 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:13,530 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:13,530 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:13,531 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:13,531 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:13,532 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:13,532 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,536 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:13,537 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,537 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:13,538 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:13,538 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,538 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:13,539 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:13,539 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:13,540 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,540 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,541 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:13,541 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,542 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:13,542 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:13,543 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:13,543 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:13,546 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,546 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:13,547 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:13,547 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,548 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:13,548 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:13,549 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,549 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-10-16 10:11:13,549 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,550 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:13,550 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,551 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:13,551 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:13,553 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:13,554 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,554 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:13,555 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:13,555 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,556 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:13,556 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:13,557 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:13,557 - numba.core.ssa - DEBUG - first assign: $phi96.0\n", - "2024-10-16 10:11:13,558 - numba.core.ssa - DEBUG - replaced with: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:13,559 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,560 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:13,560 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,561 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:13,561 - numba.core.ssa - DEBUG - replaced with: $phi96.0.1 = n\n", - "2024-10-16 10:11:13,562 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,562 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:13,563 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,564 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-10-16 10:11:13,564 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,565 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:13,565 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,566 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:13,566 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:13,568 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-10-16 10:11:13,568 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:13,568 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,569 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:13,569 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:13,570 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,570 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,572 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,572 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-10-16 10:11:13,573 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:13,573 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:13,574 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:13,575 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:13,575 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,576 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:13,576 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,577 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:13,578 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:13,578 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,579 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:13,579 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:13,580 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,580 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:13,581 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,581 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-10-16 10:11:13,581 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,582 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:13,584 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,584 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:13,585 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:13,585 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-10-16 10:11:13,586 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:13,586 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,587 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:13,588 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:13,589 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,589 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,590 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:13,590 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:13,591 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {86: [],\n", - " 94: []})\n", - "2024-10-16 10:11:13,591 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:13,592 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,592 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:13,593 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:13,593 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:13,594 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:13,596 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:13,596 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:13,597 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:13,597 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:13,597 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,598 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:13,598 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,599 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:13,600 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:13,600 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,602 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:13,602 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:13,603 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:13,603 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,604 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:13,604 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:13,605 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,606 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:13,606 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,607 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:13,608 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,608 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:13,609 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:13,610 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:13,610 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:13,611 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,611 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:13,612 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:13,612 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:13,613 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:13,613 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:13,614 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:13,614 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,615 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:13,615 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,616 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:13,618 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:13,618 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,619 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:13,619 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:13,620 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:13,620 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,621 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:13,621 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:13,621 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,622 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:13,622 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:13,623 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:13,623 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:13,624 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,624 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:13,625 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:13,627 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,628 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:13,628 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:13,629 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,629 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-10-16 10:11:13,629 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,630 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:13,631 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,632 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:13,632 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:13,633 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:13,633 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,634 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:13,634 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:13,635 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,635 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:13,636 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:13,637 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:13,638 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,638 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:13,639 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,639 - numba.core.ssa - DEBUG - on stmt: $phi96.0.1 = n\n", - "2024-10-16 10:11:13,640 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:13,640 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:13,642 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,642 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-10-16 10:11:13,643 - numba.core.ssa - DEBUG - find_def var='$phi96.0' stmt=hi.2 = $phi96.0\n", - "2024-10-16 10:11:13,643 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-10-16 10:11:13,644 - numba.core.ssa - DEBUG - insert phi node $phi96.0.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-10-16 10:11:13,644 - numba.core.ssa - DEBUG - find_def_from_bottom label 94\n", - "2024-10-16 10:11:13,645 - numba.core.ssa - DEBUG - incoming_def $phi96.0.1 = n\n", - "2024-10-16 10:11:13,645 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-10-16 10:11:13,645 - numba.core.ssa - DEBUG - incoming_def $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:13,646 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0.2\n", - "2024-10-16 10:11:13,648 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:13,648 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:13,649 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,649 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:13,650 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:13,650 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-10-16 10:11:13,651 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:13,652 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,653 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:13,653 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:13,653 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,654 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,654 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,655 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-10-16 10:11:13,655 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:13,656 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:13,656 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f33dd9a24d0>)\n", - "2024-10-16 10:11:13,658 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:13,659 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,659 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:13,660 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,660 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:13,661 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:13,661 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,662 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:13,663 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:13,663 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,664 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:13,664 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,665 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-10-16 10:11:13,665 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:13,666 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:13,666 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,667 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:13,667 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:13,668 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-10-16 10:11:13,670 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:13,670 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:13,671 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:13,671 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:13,672 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,672 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:13,673 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:13,673 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:13,711 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3728)\n", - " 2\tLOAD_FAST(arg=0, lineno=3728)\n", - " 4\tLOAD_FAST(arg=1, lineno=3728)\n", - " 6\tCOMPARE_OP(arg=1, lineno=3728)\n", - " 8\tRETURN_VALUE(arg=None, lineno=3728)\n", - "2024-10-16 10:11:13,711 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:13,712 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,713 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:13,713 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3728)\n", - "2024-10-16 10:11:13,714 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,714 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=3728)\n", - "2024-10-16 10:11:13,715 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,715 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=1, lineno=3728)\n", - "2024-10-16 10:11:13,716 - numba.core.byteflow - DEBUG - stack ['$x2.0']\n", - "2024-10-16 10:11:13,716 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=COMPARE_OP(arg=1, lineno=3728)\n", - "2024-10-16 10:11:13,717 - numba.core.byteflow - DEBUG - stack ['$x2.0', '$y4.1']\n", - "2024-10-16 10:11:13,717 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=3728)\n", - "2024-10-16 10:11:13,718 - numba.core.byteflow - DEBUG - stack ['$6compare_op.2']\n", - "2024-10-16 10:11:13,718 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:13,719 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:13,719 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:13,720 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:13,720 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:13,723 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:13,723 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:13,724 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:13,724 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:13,725 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$x2.0'}), (4, {'res': '$y4.1'}), (6, {'lhs': '$x2.0', 'rhs': '$y4.1', 'res': '$6compare_op.2'}), (8, {'retval': '$6compare_op.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:13,726 - numba.core.interpreter - DEBUG - label 0:\n", - " x = arg(0, name=x) ['x']\n", - " y = arg(1, name=y) ['y']\n", - " $6compare_op.2 = x <= y ['$6compare_op.2', 'x', 'y']\n", - " $8return_value.3 = cast(value=$6compare_op.2) ['$6compare_op.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:11:13,739 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:13,739 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:13,740 - numba.core.ssa - DEBUG - on stmt: x = arg(0, name=x)\n", - "2024-10-16 10:11:13,741 - numba.core.ssa - DEBUG - on stmt: y = arg(1, name=y)\n", - "2024-10-16 10:11:13,741 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = x <= y\n", - "2024-10-16 10:11:13,742 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6compare_op.2)\n", - "2024-10-16 10:11:13,742 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:11:13,743 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$6compare_op.2': [],\n", - " '$8return_value.3': [],\n", - " 'x': [],\n", - " 'y': []})\n", - "2024-10-16 10:11:13,744 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:13,929 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=255)\n", - " 2\tLOAD_FAST(arg=0, lineno=257)\n", - " 4\tLOAD_ATTR(arg=0, lineno=257)\n", - " 6\tLOAD_CONST(arg=1, lineno=257)\n", - " 8\tCOMPARE_OP(arg=4, lineno=257)\n", - " 10\tPOP_JUMP_IF_FALSE(arg=19, lineno=257)\n", - " 12\tLOAD_FAST(arg=1, lineno=257)\n", - " 14\tLOAD_FAST(arg=0, lineno=257)\n", - " 16\tLOAD_ATTR(arg=1, lineno=257)\n", - " 18\tCOMPARE_OP(arg=0, lineno=257)\n", - " 20\tPOP_JUMP_IF_TRUE(arg=17, lineno=257)\n", - " 22\tLOAD_FAST(arg=1, lineno=257)\n", - " 24\tLOAD_FAST(arg=0, lineno=257)\n", - " 26\tLOAD_ATTR(arg=2, lineno=257)\n", - " 28\tCOMPARE_OP(arg=5, lineno=257)\n", - " 30\tPOP_JUMP_IF_FALSE(arg=19, lineno=257)\n", - "> 32\tLOAD_CONST(arg=2, lineno=258)\n", - " 34\tRETURN_VALUE(arg=None, lineno=258)\n", - "> 36\tLOAD_FAST(arg=0, lineno=259)\n", - " 38\tLOAD_ATTR(arg=0, lineno=259)\n", - " 40\tLOAD_CONST(arg=1, lineno=259)\n", - " 42\tCOMPARE_OP(arg=0, lineno=259)\n", - " 44\tPOP_JUMP_IF_FALSE(arg=36, lineno=259)\n", - " 46\tLOAD_FAST(arg=1, lineno=259)\n", - " 48\tLOAD_FAST(arg=0, lineno=259)\n", - " 50\tLOAD_ATTR(arg=2, lineno=259)\n", - " 52\tCOMPARE_OP(arg=1, lineno=259)\n", - " 54\tPOP_JUMP_IF_TRUE(arg=34, lineno=259)\n", - " 56\tLOAD_FAST(arg=1, lineno=259)\n", - " 58\tLOAD_FAST(arg=0, lineno=259)\n", - " 60\tLOAD_ATTR(arg=1, lineno=259)\n", - " 62\tCOMPARE_OP(arg=4, lineno=259)\n", - " 64\tPOP_JUMP_IF_FALSE(arg=36, lineno=259)\n", - "> 66\tLOAD_CONST(arg=2, lineno=260)\n", - " 68\tRETURN_VALUE(arg=None, lineno=260)\n", - "> 70\tLOAD_FAST(arg=1, lineno=262)\n", - " 72\tLOAD_FAST(arg=0, lineno=262)\n", - " 74\tLOAD_ATTR(arg=1, lineno=262)\n", - " 76\tBINARY_SUBTRACT(arg=None, lineno=262)\n", - " 78\tLOAD_FAST(arg=0, lineno=262)\n", - " 80\tLOAD_ATTR(arg=0, lineno=262)\n", - " 82\tBINARY_MODULO(arg=None, lineno=262)\n", - " 84\tLOAD_CONST(arg=1, lineno=262)\n", - " 86\tCOMPARE_OP(arg=2, lineno=262)\n", - " 88\tRETURN_VALUE(arg=None, lineno=262)\n", - "2024-10-16 10:11:13,930 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:13,930 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,930 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:13,931 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=255)\n", - "2024-10-16 10:11:13,931 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,932 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=257)\n", - "2024-10-16 10:11:13,932 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,933 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=0, lineno=257)\n", - "2024-10-16 10:11:13,933 - numba.core.byteflow - DEBUG - stack ['$robj2.0']\n", - "2024-10-16 10:11:13,933 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_CONST(arg=1, lineno=257)\n", - "2024-10-16 10:11:13,934 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-10-16 10:11:13,934 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=COMPARE_OP(arg=4, lineno=257)\n", - "2024-10-16 10:11:13,935 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$const6.2']\n", - "2024-10-16 10:11:13,935 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=POP_JUMP_IF_FALSE(arg=19, lineno=257)\n", - "2024-10-16 10:11:13,935 - numba.core.byteflow - DEBUG - stack ['$8compare_op.3']\n", - "2024-10-16 10:11:13,936 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=12, stack=(), blockstack=(), npush=0), Edge(pc=36, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:13,936 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=12 nstack_initial=0), State(pc_initial=36 nstack_initial=0)])\n", - "2024-10-16 10:11:13,937 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,937 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=12 nstack_initial=0)\n", - "2024-10-16 10:11:13,937 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=1, lineno=257)\n", - "2024-10-16 10:11:13,938 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,940 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=0, lineno=257)\n", - "2024-10-16 10:11:13,941 - numba.core.byteflow - DEBUG - stack ['$val12.0']\n", - "2024-10-16 10:11:13,941 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_ATTR(arg=1, lineno=257)\n", - "2024-10-16 10:11:13,941 - numba.core.byteflow - DEBUG - stack ['$val12.0', '$robj14.1']\n", - "2024-10-16 10:11:13,942 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=COMPARE_OP(arg=0, lineno=257)\n", - "2024-10-16 10:11:13,942 - numba.core.byteflow - DEBUG - stack ['$val12.0', '$16load_attr.2']\n", - "2024-10-16 10:11:13,943 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=POP_JUMP_IF_TRUE(arg=17, lineno=257)\n", - "2024-10-16 10:11:13,943 - numba.core.byteflow - DEBUG - stack ['$18compare_op.3']\n", - "2024-10-16 10:11:13,943 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=22, stack=(), blockstack=(), npush=0), Edge(pc=32, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:13,944 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=36 nstack_initial=0), State(pc_initial=22 nstack_initial=0), State(pc_initial=32 nstack_initial=0)])\n", - "2024-10-16 10:11:13,944 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,945 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=36 nstack_initial=0)\n", - "2024-10-16 10:11:13,945 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_FAST(arg=0, lineno=259)\n", - "2024-10-16 10:11:13,945 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,946 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_ATTR(arg=0, lineno=259)\n", - "2024-10-16 10:11:13,946 - numba.core.byteflow - DEBUG - stack ['$robj36.0']\n", - "2024-10-16 10:11:13,947 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_CONST(arg=1, lineno=259)\n", - "2024-10-16 10:11:13,947 - numba.core.byteflow - DEBUG - stack ['$38load_attr.1']\n", - "2024-10-16 10:11:13,947 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=COMPARE_OP(arg=0, lineno=259)\n", - "2024-10-16 10:11:13,948 - numba.core.byteflow - DEBUG - stack ['$38load_attr.1', '$const40.2']\n", - "2024-10-16 10:11:13,948 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_FALSE(arg=36, lineno=259)\n", - "2024-10-16 10:11:13,949 - numba.core.byteflow - DEBUG - stack ['$42compare_op.3']\n", - "2024-10-16 10:11:13,949 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=(), blockstack=(), npush=0), Edge(pc=70, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:13,952 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=22 nstack_initial=0), State(pc_initial=32 nstack_initial=0), State(pc_initial=46 nstack_initial=0), State(pc_initial=70 nstack_initial=0)])\n", - "2024-10-16 10:11:13,952 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,952 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=22 nstack_initial=0)\n", - "2024-10-16 10:11:13,953 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=1, lineno=257)\n", - "2024-10-16 10:11:13,953 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,953 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_FAST(arg=0, lineno=257)\n", - "2024-10-16 10:11:13,954 - numba.core.byteflow - DEBUG - stack ['$val22.0']\n", - "2024-10-16 10:11:13,954 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_ATTR(arg=2, lineno=257)\n", - "2024-10-16 10:11:13,955 - numba.core.byteflow - DEBUG - stack ['$val22.0', '$robj24.1']\n", - "2024-10-16 10:11:13,955 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=COMPARE_OP(arg=5, lineno=257)\n", - "2024-10-16 10:11:13,955 - numba.core.byteflow - DEBUG - stack ['$val22.0', '$26load_attr.2']\n", - "2024-10-16 10:11:13,956 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=POP_JUMP_IF_FALSE(arg=19, lineno=257)\n", - "2024-10-16 10:11:13,956 - numba.core.byteflow - DEBUG - stack ['$28compare_op.3']\n", - "2024-10-16 10:11:13,957 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=32, stack=(), blockstack=(), npush=0), Edge(pc=36, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:13,957 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=0), State(pc_initial=46 nstack_initial=0), State(pc_initial=70 nstack_initial=0), State(pc_initial=32 nstack_initial=0), State(pc_initial=36 nstack_initial=0)])\n", - "2024-10-16 10:11:13,959 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,959 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=32 nstack_initial=0)\n", - "2024-10-16 10:11:13,960 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_CONST(arg=2, lineno=258)\n", - "2024-10-16 10:11:13,960 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,961 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=RETURN_VALUE(arg=None, lineno=258)\n", - "2024-10-16 10:11:13,961 - numba.core.byteflow - DEBUG - stack ['$const32.0']\n", - "2024-10-16 10:11:13,961 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:13,962 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=0), State(pc_initial=70 nstack_initial=0), State(pc_initial=32 nstack_initial=0), State(pc_initial=36 nstack_initial=0)])\n", - "2024-10-16 10:11:13,962 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,962 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=0)\n", - "2024-10-16 10:11:13,963 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=1, lineno=259)\n", - "2024-10-16 10:11:13,963 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,964 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_FAST(arg=0, lineno=259)\n", - "2024-10-16 10:11:13,964 - numba.core.byteflow - DEBUG - stack ['$val46.0']\n", - "2024-10-16 10:11:13,964 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_ATTR(arg=2, lineno=259)\n", - "2024-10-16 10:11:13,965 - numba.core.byteflow - DEBUG - stack ['$val46.0', '$robj48.1']\n", - "2024-10-16 10:11:13,965 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=COMPARE_OP(arg=1, lineno=259)\n", - "2024-10-16 10:11:13,966 - numba.core.byteflow - DEBUG - stack ['$val46.0', '$50load_attr.2']\n", - "2024-10-16 10:11:13,966 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=POP_JUMP_IF_TRUE(arg=34, lineno=259)\n", - "2024-10-16 10:11:13,966 - numba.core.byteflow - DEBUG - stack ['$52compare_op.3']\n", - "2024-10-16 10:11:13,967 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=56, stack=(), blockstack=(), npush=0), Edge(pc=66, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:13,967 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=70 nstack_initial=0), State(pc_initial=32 nstack_initial=0), State(pc_initial=36 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=66 nstack_initial=0)])\n", - "2024-10-16 10:11:13,968 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,968 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=70 nstack_initial=0)\n", - "2024-10-16 10:11:13,968 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=LOAD_FAST(arg=1, lineno=262)\n", - "2024-10-16 10:11:13,969 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,969 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=LOAD_FAST(arg=0, lineno=262)\n", - "2024-10-16 10:11:13,970 - numba.core.byteflow - DEBUG - stack ['$val70.0']\n", - "2024-10-16 10:11:13,970 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_ATTR(arg=1, lineno=262)\n", - "2024-10-16 10:11:13,970 - numba.core.byteflow - DEBUG - stack ['$val70.0', '$robj72.1']\n", - "2024-10-16 10:11:13,971 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=BINARY_SUBTRACT(arg=None, lineno=262)\n", - "2024-10-16 10:11:13,971 - numba.core.byteflow - DEBUG - stack ['$val70.0', '$74load_attr.2']\n", - "2024-10-16 10:11:13,972 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=0, lineno=262)\n", - "2024-10-16 10:11:13,972 - numba.core.byteflow - DEBUG - stack ['$76binary_subtract.3']\n", - "2024-10-16 10:11:13,972 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_ATTR(arg=0, lineno=262)\n", - "2024-10-16 10:11:13,973 - numba.core.byteflow - DEBUG - stack ['$76binary_subtract.3', '$robj78.4']\n", - "2024-10-16 10:11:13,973 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=BINARY_MODULO(arg=None, lineno=262)\n", - "2024-10-16 10:11:13,974 - numba.core.byteflow - DEBUG - stack ['$76binary_subtract.3', '$80load_attr.5']\n", - "2024-10-16 10:11:13,974 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=LOAD_CONST(arg=1, lineno=262)\n", - "2024-10-16 10:11:13,977 - numba.core.byteflow - DEBUG - stack ['$82binary_modulo.6']\n", - "2024-10-16 10:11:13,978 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=COMPARE_OP(arg=2, lineno=262)\n", - "2024-10-16 10:11:13,978 - numba.core.byteflow - DEBUG - stack ['$82binary_modulo.6', '$const84.7']\n", - "2024-10-16 10:11:13,979 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=RETURN_VALUE(arg=None, lineno=262)\n", - "2024-10-16 10:11:13,979 - numba.core.byteflow - DEBUG - stack ['$86compare_op.8']\n", - "2024-10-16 10:11:13,979 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:13,980 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=0), State(pc_initial=36 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=66 nstack_initial=0)])\n", - "2024-10-16 10:11:13,980 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=36 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=66 nstack_initial=0)])\n", - "2024-10-16 10:11:13,981 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=0), State(pc_initial=66 nstack_initial=0)])\n", - "2024-10-16 10:11:13,981 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,981 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=0)\n", - "2024-10-16 10:11:13,982 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_FAST(arg=1, lineno=259)\n", - "2024-10-16 10:11:13,982 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,983 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_FAST(arg=0, lineno=259)\n", - "2024-10-16 10:11:13,983 - numba.core.byteflow - DEBUG - stack ['$val56.0']\n", - "2024-10-16 10:11:13,983 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_ATTR(arg=1, lineno=259)\n", - "2024-10-16 10:11:13,984 - numba.core.byteflow - DEBUG - stack ['$val56.0', '$robj58.1']\n", - "2024-10-16 10:11:13,984 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=COMPARE_OP(arg=4, lineno=259)\n", - "2024-10-16 10:11:13,985 - numba.core.byteflow - DEBUG - stack ['$val56.0', '$60load_attr.2']\n", - "2024-10-16 10:11:13,985 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=POP_JUMP_IF_FALSE(arg=36, lineno=259)\n", - "2024-10-16 10:11:13,986 - numba.core.byteflow - DEBUG - stack ['$62compare_op.3']\n", - "2024-10-16 10:11:13,986 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=66, stack=(), blockstack=(), npush=0), Edge(pc=70, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:13,986 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=66 nstack_initial=0), State(pc_initial=66 nstack_initial=0), State(pc_initial=70 nstack_initial=0)])\n", - "2024-10-16 10:11:13,987 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:13,987 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=66 nstack_initial=0)\n", - "2024-10-16 10:11:13,988 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_CONST(arg=2, lineno=260)\n", - "2024-10-16 10:11:13,988 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:13,988 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=RETURN_VALUE(arg=None, lineno=260)\n", - "2024-10-16 10:11:13,989 - numba.core.byteflow - DEBUG - stack ['$const66.0']\n", - "2024-10-16 10:11:13,989 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:13,990 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=66 nstack_initial=0), State(pc_initial=70 nstack_initial=0)])\n", - "2024-10-16 10:11:13,990 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=70 nstack_initial=0)])\n", - "2024-10-16 10:11:13,990 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:13,991 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=12 nstack_initial=0): set(),\n", - " State(pc_initial=22 nstack_initial=0): set(),\n", - " State(pc_initial=32 nstack_initial=0): set(),\n", - " State(pc_initial=36 nstack_initial=0): set(),\n", - " State(pc_initial=46 nstack_initial=0): set(),\n", - " State(pc_initial=56 nstack_initial=0): set(),\n", - " State(pc_initial=66 nstack_initial=0): set(),\n", - " State(pc_initial=70 nstack_initial=0): set()})\n", - "2024-10-16 10:11:13,991 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:13,992 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:13,992 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:13,993 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:13,993 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:13,993 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:13,994 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$robj2.0'}), (4, {'item': '$robj2.0', 'res': '$4load_attr.1'}), (6, {'res': '$const6.2'}), (8, {'lhs': '$4load_attr.1', 'rhs': '$const6.2', 'res': '$8compare_op.3'}), (10, {'pred': '$8compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={12: (), 36: ()})\n", - "2024-10-16 10:11:13,994 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=12 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((12, {'res': '$val12.0'}), (14, {'res': '$robj14.1'}), (16, {'item': '$robj14.1', 'res': '$16load_attr.2'}), (18, {'lhs': '$val12.0', 'rhs': '$16load_attr.2', 'res': '$18compare_op.3'}), (20, {'pred': '$18compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={22: (), 32: ()})\n", - "2024-10-16 10:11:13,995 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=22 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((22, {'res': '$val22.0'}), (24, {'res': '$robj24.1'}), (26, {'item': '$robj24.1', 'res': '$26load_attr.2'}), (28, {'lhs': '$val22.0', 'rhs': '$26load_attr.2', 'res': '$28compare_op.3'}), (30, {'pred': '$28compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={32: (), 36: ()})\n", - "2024-10-16 10:11:13,995 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=32 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((32, {'res': '$const32.0'}), (34, {'retval': '$const32.0', 'castval': '$34return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:13,996 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=36 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((36, {'res': '$robj36.0'}), (38, {'item': '$robj36.0', 'res': '$38load_attr.1'}), (40, {'res': '$const40.2'}), (42, {'lhs': '$38load_attr.1', 'rhs': '$const40.2', 'res': '$42compare_op.3'}), (44, {'pred': '$42compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: (), 70: ()})\n", - "2024-10-16 10:11:13,996 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((46, {'res': '$val46.0'}), (48, {'res': '$robj48.1'}), (50, {'item': '$robj48.1', 'res': '$50load_attr.2'}), (52, {'lhs': '$val46.0', 'rhs': '$50load_attr.2', 'res': '$52compare_op.3'}), (54, {'pred': '$52compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={56: (), 66: ()})\n", - "2024-10-16 10:11:13,996 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((56, {'res': '$val56.0'}), (58, {'res': '$robj58.1'}), (60, {'item': '$robj58.1', 'res': '$60load_attr.2'}), (62, {'lhs': '$val56.0', 'rhs': '$60load_attr.2', 'res': '$62compare_op.3'}), (64, {'pred': '$62compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={66: (), 70: ()})\n", - "2024-10-16 10:11:13,997 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=66 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((66, {'res': '$const66.0'}), (68, {'retval': '$const66.0', 'castval': '$68return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:13,997 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=70 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((70, {'res': '$val70.0'}), (72, {'res': '$robj72.1'}), (74, {'item': '$robj72.1', 'res': '$74load_attr.2'}), (76, {'lhs': '$val70.0', 'rhs': '$74load_attr.2', 'res': '$76binary_subtract.3'}), (78, {'res': '$robj78.4'}), (80, {'item': '$robj78.4', 'res': '$80load_attr.5'}), (82, {'lhs': '$76binary_subtract.3', 'rhs': '$80load_attr.5', 'res': '$82binary_modulo.6'}), (84, {'res': '$const84.7'}), (86, {'lhs': '$82binary_modulo.6', 'rhs': '$const84.7', 'res': '$86compare_op.8'}), (88, {'retval': '$86compare_op.8', 'castval': '$88return_value.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:13,999 - numba.core.interpreter - DEBUG - label 0:\n", - " robj = arg(0, name=robj) ['robj']\n", - " val = arg(1, name=val) ['val']\n", - " $4load_attr.1 = getattr(value=robj, attr=step) ['$4load_attr.1', 'robj']\n", - " $const6.2 = const(int, 0) ['$const6.2']\n", - " $8compare_op.3 = $4load_attr.1 > $const6.2 ['$4load_attr.1', '$8compare_op.3', '$const6.2']\n", - " bool10 = global(bool: ) ['bool10']\n", - " $10pred = call bool10($8compare_op.3, func=bool10, args=(Var($8compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None) ['$10pred', '$8compare_op.3', 'bool10']\n", - " branch $10pred, 12, 36 ['$10pred']\n", - "label 12:\n", - " $16load_attr.2 = getattr(value=robj, attr=start) ['$16load_attr.2', 'robj']\n", - " $18compare_op.3 = val < $16load_attr.2 ['$16load_attr.2', '$18compare_op.3', 'val']\n", - " bool20 = global(bool: ) ['bool20']\n", - " $20pred = call bool20($18compare_op.3, func=bool20, args=(Var($18compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None) ['$18compare_op.3', '$20pred', 'bool20']\n", - " branch $20pred, 32, 22 ['$20pred']\n", - "label 22:\n", - " $26load_attr.2 = getattr(value=robj, attr=stop) ['$26load_attr.2', 'robj']\n", - " $28compare_op.3 = val >= $26load_attr.2 ['$26load_attr.2', '$28compare_op.3', 'val']\n", - " bool30 = global(bool: ) ['bool30']\n", - " $30pred = call bool30($28compare_op.3, func=bool30, args=(Var($28compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None) ['$28compare_op.3', '$30pred', 'bool30']\n", - " branch $30pred, 32, 36 ['$30pred']\n", - "label 32:\n", - " $const32.0 = const(bool, False) ['$const32.0']\n", - " $34return_value.1 = cast(value=$const32.0) ['$34return_value.1', '$const32.0']\n", - " return $34return_value.1 ['$34return_value.1']\n", - "label 36:\n", - " $38load_attr.1 = getattr(value=robj, attr=step) ['$38load_attr.1', 'robj']\n", - " $const40.2 = const(int, 0) ['$const40.2']\n", - " $42compare_op.3 = $38load_attr.1 < $const40.2 ['$38load_attr.1', '$42compare_op.3', '$const40.2']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42compare_op.3, func=bool44, args=(Var($42compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None) ['$42compare_op.3', '$44pred', 'bool44']\n", - " branch $44pred, 46, 70 ['$44pred']\n", - "label 46:\n", - " $50load_attr.2 = getattr(value=robj, attr=stop) ['$50load_attr.2', 'robj']\n", - " $52compare_op.3 = val <= $50load_attr.2 ['$50load_attr.2', '$52compare_op.3', 'val']\n", - " bool54 = global(bool: ) ['bool54']\n", - " $54pred = call bool54($52compare_op.3, func=bool54, args=(Var($52compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None) ['$52compare_op.3', '$54pred', 'bool54']\n", - " branch $54pred, 66, 56 ['$54pred']\n", - "label 56:\n", - " $60load_attr.2 = getattr(value=robj, attr=start) ['$60load_attr.2', 'robj']\n", - " $62compare_op.3 = val > $60load_attr.2 ['$60load_attr.2', '$62compare_op.3', 'val']\n", - " bool64 = global(bool: ) ['bool64']\n", - " $64pred = call bool64($62compare_op.3, func=bool64, args=(Var($62compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None) ['$62compare_op.3', '$64pred', 'bool64']\n", - " branch $64pred, 66, 70 ['$64pred']\n", - "label 66:\n", - " $const66.0 = const(bool, False) ['$const66.0']\n", - " $68return_value.1 = cast(value=$const66.0) ['$68return_value.1', '$const66.0']\n", - " return $68return_value.1 ['$68return_value.1']\n", - "label 70:\n", - " $74load_attr.2 = getattr(value=robj, attr=start) ['$74load_attr.2', 'robj']\n", - " $76binary_subtract.3 = val - $74load_attr.2 ['$74load_attr.2', '$76binary_subtract.3', 'val']\n", - " $80load_attr.5 = getattr(value=robj, attr=step) ['$80load_attr.5', 'robj']\n", - " $82binary_modulo.6 = $76binary_subtract.3 % $80load_attr.5 ['$76binary_subtract.3', '$80load_attr.5', '$82binary_modulo.6']\n", - " $const84.7 = const(int, 0) ['$const84.7']\n", - " $86compare_op.8 = $82binary_modulo.6 == $const84.7 ['$82binary_modulo.6', '$86compare_op.8', '$const84.7']\n", - " $88return_value.9 = cast(value=$86compare_op.8) ['$86compare_op.8', '$88return_value.9']\n", - " return $88return_value.9 ['$88return_value.9']\n", - "\n", - "2024-10-16 10:11:14,009 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:14,015 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,015 - numba.core.ssa - DEBUG - on stmt: robj = arg(0, name=robj)\n", - "2024-10-16 10:11:14,016 - numba.core.ssa - DEBUG - on stmt: val = arg(1, name=val)\n", - "2024-10-16 10:11:14,016 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=robj, attr=step)\n", - "2024-10-16 10:11:14,017 - numba.core.ssa - DEBUG - on stmt: $const6.2 = const(int, 0)\n", - "2024-10-16 10:11:14,017 - numba.core.ssa - DEBUG - on stmt: $8compare_op.3 = $4load_attr.1 > $const6.2\n", - "2024-10-16 10:11:14,017 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:14,018 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8compare_op.3, func=bool10, args=(Var($8compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,018 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 36\n", - "2024-10-16 10:11:14,019 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 12\n", - "2024-10-16 10:11:14,019 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,019 - numba.core.ssa - DEBUG - on stmt: $16load_attr.2 = getattr(value=robj, attr=start)\n", - "2024-10-16 10:11:14,020 - numba.core.ssa - DEBUG - on stmt: $18compare_op.3 = val < $16load_attr.2\n", - "2024-10-16 10:11:14,020 - numba.core.ssa - DEBUG - on stmt: bool20 = global(bool: )\n", - "2024-10-16 10:11:14,021 - numba.core.ssa - DEBUG - on stmt: $20pred = call bool20($18compare_op.3, func=bool20, args=(Var($18compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,021 - numba.core.ssa - DEBUG - on stmt: branch $20pred, 32, 22\n", - "2024-10-16 10:11:14,021 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 22\n", - "2024-10-16 10:11:14,022 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,022 - numba.core.ssa - DEBUG - on stmt: $26load_attr.2 = getattr(value=robj, attr=stop)\n", - "2024-10-16 10:11:14,023 - numba.core.ssa - DEBUG - on stmt: $28compare_op.3 = val >= $26load_attr.2\n", - "2024-10-16 10:11:14,023 - numba.core.ssa - DEBUG - on stmt: bool30 = global(bool: )\n", - "2024-10-16 10:11:14,023 - numba.core.ssa - DEBUG - on stmt: $30pred = call bool30($28compare_op.3, func=bool30, args=(Var($28compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,024 - numba.core.ssa - DEBUG - on stmt: branch $30pred, 32, 36\n", - "2024-10-16 10:11:14,024 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 32\n", - "2024-10-16 10:11:14,025 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,025 - numba.core.ssa - DEBUG - on stmt: $const32.0 = const(bool, False)\n", - "2024-10-16 10:11:14,025 - numba.core.ssa - DEBUG - on stmt: $34return_value.1 = cast(value=$const32.0)\n", - "2024-10-16 10:11:14,026 - numba.core.ssa - DEBUG - on stmt: return $34return_value.1\n", - "2024-10-16 10:11:14,026 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 36\n", - "2024-10-16 10:11:14,027 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,027 - numba.core.ssa - DEBUG - on stmt: $38load_attr.1 = getattr(value=robj, attr=step)\n", - "2024-10-16 10:11:14,027 - numba.core.ssa - DEBUG - on stmt: $const40.2 = const(int, 0)\n", - "2024-10-16 10:11:14,028 - numba.core.ssa - DEBUG - on stmt: $42compare_op.3 = $38load_attr.1 < $const40.2\n", - "2024-10-16 10:11:14,028 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:14,029 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42compare_op.3, func=bool44, args=(Var($42compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,029 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 46, 70\n", - "2024-10-16 10:11:14,029 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-10-16 10:11:14,030 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,030 - numba.core.ssa - DEBUG - on stmt: $50load_attr.2 = getattr(value=robj, attr=stop)\n", - "2024-10-16 10:11:14,031 - numba.core.ssa - DEBUG - on stmt: $52compare_op.3 = val <= $50load_attr.2\n", - "2024-10-16 10:11:14,031 - numba.core.ssa - DEBUG - on stmt: bool54 = global(bool: )\n", - "2024-10-16 10:11:14,031 - numba.core.ssa - DEBUG - on stmt: $54pred = call bool54($52compare_op.3, func=bool54, args=(Var($52compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,032 - numba.core.ssa - DEBUG - on stmt: branch $54pred, 66, 56\n", - "2024-10-16 10:11:14,032 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-10-16 10:11:14,033 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,033 - numba.core.ssa - DEBUG - on stmt: $60load_attr.2 = getattr(value=robj, attr=start)\n", - "2024-10-16 10:11:14,033 - numba.core.ssa - DEBUG - on stmt: $62compare_op.3 = val > $60load_attr.2\n", - "2024-10-16 10:11:14,034 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:11:14,034 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.3, func=bool64, args=(Var($62compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,035 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 70\n", - "2024-10-16 10:11:14,035 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 66\n", - "2024-10-16 10:11:14,035 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,036 - numba.core.ssa - DEBUG - on stmt: $const66.0 = const(bool, False)\n", - "2024-10-16 10:11:14,036 - numba.core.ssa - DEBUG - on stmt: $68return_value.1 = cast(value=$const66.0)\n", - "2024-10-16 10:11:14,037 - numba.core.ssa - DEBUG - on stmt: return $68return_value.1\n", - "2024-10-16 10:11:14,037 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 70\n", - "2024-10-16 10:11:14,037 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,038 - numba.core.ssa - DEBUG - on stmt: $74load_attr.2 = getattr(value=robj, attr=start)\n", - "2024-10-16 10:11:14,038 - numba.core.ssa - DEBUG - on stmt: $76binary_subtract.3 = val - $74load_attr.2\n", - "2024-10-16 10:11:14,039 - numba.core.ssa - DEBUG - on stmt: $80load_attr.5 = getattr(value=robj, attr=step)\n", - "2024-10-16 10:11:14,039 - numba.core.ssa - DEBUG - on stmt: $82binary_modulo.6 = $76binary_subtract.3 % $80load_attr.5\n", - "2024-10-16 10:11:14,039 - numba.core.ssa - DEBUG - on stmt: $const84.7 = const(int, 0)\n", - "2024-10-16 10:11:14,040 - numba.core.ssa - DEBUG - on stmt: $86compare_op.8 = $82binary_modulo.6 == $const84.7\n", - "2024-10-16 10:11:14,040 - numba.core.ssa - DEBUG - on stmt: $88return_value.9 = cast(value=$86compare_op.8)\n", - "2024-10-16 10:11:14,041 - numba.core.ssa - DEBUG - on stmt: return $88return_value.9\n", - "2024-10-16 10:11:14,041 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10pred': [],\n", - " '$16load_attr.2': [],\n", - " '$18compare_op.3': [],\n", - " '$20pred': [],\n", - " '$26load_attr.2': [],\n", - " '$28compare_op.3': [],\n", - " '$30pred': [],\n", - " '$34return_value.1': [],\n", - " '$38load_attr.1': [],\n", - " '$42compare_op.3': [],\n", - " '$44pred': [],\n", - " '$4load_attr.1': [],\n", - " '$50load_attr.2': [],\n", - " '$52compare_op.3': [],\n", - " '$54pred': [],\n", - " '$60load_attr.2': [],\n", - " '$62compare_op.3': [],\n", - " '$64pred': [],\n", - " '$68return_value.1': [],\n", - " '$74load_attr.2': [],\n", - " '$76binary_subtract.3': [],\n", - " '$80load_attr.5': [],\n", - " '$82binary_modulo.6': [],\n", - " '$86compare_op.8': [],\n", - " '$88return_value.9': [],\n", - " '$8compare_op.3': [],\n", - " '$const32.0': [],\n", - " '$const40.2': [],\n", - " '$const6.2': [],\n", - " '$const66.0': [],\n", - " '$const84.7': [],\n", - " 'bool10': [],\n", - " 'bool20': [],\n", - " 'bool30': [],\n", - " 'bool44': [],\n", - " 'bool54': [],\n", - " 'bool64': [],\n", - " 'robj': [],\n", - " 'val': []})\n", - "2024-10-16 10:11:14,048 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:14,053 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=250)\n", - " 2\tLOAD_DEREF(arg=0, lineno=251)\n", - " 4\tLOAD_FAST(arg=0, lineno=251)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=251)\n", - " 8\tRETURN_VALUE(arg=None, lineno=251)\n", - "2024-10-16 10:11:14,053 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:14,054 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,054 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:14,055 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=250)\n", - "2024-10-16 10:11:14,055 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,055 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_DEREF(arg=0, lineno=251)\n", - "2024-10-16 10:11:14,056 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,056 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=251)\n", - "2024-10-16 10:11:14,057 - numba.core.byteflow - DEBUG - stack ['$2load_deref.0']\n", - "2024-10-16 10:11:14,057 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=251)\n", - "2024-10-16 10:11:14,057 - numba.core.byteflow - DEBUG - stack ['$2load_deref.0', '$rnge4.1']\n", - "2024-10-16 10:11:14,058 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=251)\n", - "2024-10-16 10:11:14,058 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-10-16 10:11:14,059 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:14,059 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:14,059 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:14,060 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:14,060 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,061 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,061 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:14,061 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:14,062 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:14,062 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_deref.0'}), (4, {'res': '$rnge4.1'}), (6, {'func': '$2load_deref.0', 'args': ['$rnge4.1'], 'res': '$6call_function.2'}), (8, {'retval': '$6call_function.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:14,063 - numba.core.interpreter - DEBUG - label 0:\n", - " rnge = arg(0, name=rnge) ['rnge']\n", - " $2load_deref.0 = freevar(rangetype_attr_getter: ) ['$2load_deref.0']\n", - " $6call_function.2 = call $2load_deref.0(rnge, func=$2load_deref.0, args=[Var(rnge, rangeobj.py:250)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_deref.0', '$6call_function.2', 'rnge']\n", - " $8return_value.3 = cast(value=$6call_function.2) ['$6call_function.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:11:14,068 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:14,069 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,069 - numba.core.ssa - DEBUG - on stmt: rnge = arg(0, name=rnge)\n", - "2024-10-16 10:11:14,070 - numba.core.ssa - DEBUG - on stmt: $2load_deref.0 = freevar(rangetype_attr_getter: )\n", - "2024-10-16 10:11:14,070 - numba.core.ssa - DEBUG - on stmt: $6call_function.2 = call $2load_deref.0(rnge, func=$2load_deref.0, args=[Var(rnge, rangeobj.py:250)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,070 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6call_function.2)\n", - "2024-10-16 10:11:14,071 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:11:14,071 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$2load_deref.0': [],\n", - " '$6call_function.2': [],\n", - " '$8return_value.3': [],\n", - " 'rnge': []})\n", - "2024-10-16 10:11:14,072 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:14,100 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=250)\n", - " 2\tLOAD_DEREF(arg=0, lineno=251)\n", - " 4\tLOAD_FAST(arg=0, lineno=251)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=251)\n", - " 8\tRETURN_VALUE(arg=None, lineno=251)\n", - "2024-10-16 10:11:14,100 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:14,101 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,101 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:14,102 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=250)\n", - "2024-10-16 10:11:14,102 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,103 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_DEREF(arg=0, lineno=251)\n", - "2024-10-16 10:11:14,103 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,103 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=251)\n", - "2024-10-16 10:11:14,104 - numba.core.byteflow - DEBUG - stack ['$2load_deref.0']\n", - "2024-10-16 10:11:14,104 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=251)\n", - "2024-10-16 10:11:14,105 - numba.core.byteflow - DEBUG - stack ['$2load_deref.0', '$rnge4.1']\n", - "2024-10-16 10:11:14,105 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=251)\n", - "2024-10-16 10:11:14,105 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-10-16 10:11:14,106 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:14,106 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:14,107 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:14,107 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:14,107 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,108 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,108 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:14,109 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:14,109 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:14,109 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_deref.0'}), (4, {'res': '$rnge4.1'}), (6, {'func': '$2load_deref.0', 'args': ['$rnge4.1'], 'res': '$6call_function.2'}), (8, {'retval': '$6call_function.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:14,110 - numba.core.interpreter - DEBUG - label 0:\n", - " rnge = arg(0, name=rnge) ['rnge']\n", - " $2load_deref.0 = freevar(rangetype_attr_getter: ) ['$2load_deref.0']\n", - " $6call_function.2 = call $2load_deref.0(rnge, func=$2load_deref.0, args=[Var(rnge, rangeobj.py:250)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_deref.0', '$6call_function.2', 'rnge']\n", - " $8return_value.3 = cast(value=$6call_function.2) ['$6call_function.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:11:14,118 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:14,118 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,119 - numba.core.ssa - DEBUG - on stmt: rnge = arg(0, name=rnge)\n", - "2024-10-16 10:11:14,119 - numba.core.ssa - DEBUG - on stmt: $2load_deref.0 = freevar(rangetype_attr_getter: )\n", - "2024-10-16 10:11:14,119 - numba.core.ssa - DEBUG - on stmt: $6call_function.2 = call $2load_deref.0(rnge, func=$2load_deref.0, args=[Var(rnge, rangeobj.py:250)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,120 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6call_function.2)\n", - "2024-10-16 10:11:14,120 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:11:14,121 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$2load_deref.0': [],\n", - " '$6call_function.2': [],\n", - " '$8return_value.3': [],\n", - " 'rnge': []})\n", - "2024-10-16 10:11:14,121 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:14,145 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=250)\n", - " 2\tLOAD_DEREF(arg=0, lineno=251)\n", - " 4\tLOAD_FAST(arg=0, lineno=251)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=251)\n", - " 8\tRETURN_VALUE(arg=None, lineno=251)\n", - "2024-10-16 10:11:14,146 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:14,146 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,147 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:14,147 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=250)\n", - "2024-10-16 10:11:14,148 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,148 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_DEREF(arg=0, lineno=251)\n", - "2024-10-16 10:11:14,149 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,149 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=251)\n", - "2024-10-16 10:11:14,149 - numba.core.byteflow - DEBUG - stack ['$2load_deref.0']\n", - "2024-10-16 10:11:14,150 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=251)\n", - "2024-10-16 10:11:14,150 - numba.core.byteflow - DEBUG - stack ['$2load_deref.0', '$rnge4.1']\n", - "2024-10-16 10:11:14,151 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=251)\n", - "2024-10-16 10:11:14,152 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-10-16 10:11:14,152 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:14,153 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:14,153 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:14,154 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:14,154 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,155 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,155 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:14,155 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:14,156 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:14,156 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_deref.0'}), (4, {'res': '$rnge4.1'}), (6, {'func': '$2load_deref.0', 'args': ['$rnge4.1'], 'res': '$6call_function.2'}), (8, {'retval': '$6call_function.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:14,157 - numba.core.interpreter - DEBUG - label 0:\n", - " rnge = arg(0, name=rnge) ['rnge']\n", - " $2load_deref.0 = freevar(rangetype_attr_getter: ) ['$2load_deref.0']\n", - " $6call_function.2 = call $2load_deref.0(rnge, func=$2load_deref.0, args=[Var(rnge, rangeobj.py:250)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_deref.0', '$6call_function.2', 'rnge']\n", - " $8return_value.3 = cast(value=$6call_function.2) ['$6call_function.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:11:14,163 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:14,163 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,164 - numba.core.ssa - DEBUG - on stmt: rnge = arg(0, name=rnge)\n", - "2024-10-16 10:11:14,164 - numba.core.ssa - DEBUG - on stmt: $2load_deref.0 = freevar(rangetype_attr_getter: )\n", - "2024-10-16 10:11:14,165 - numba.core.ssa - DEBUG - on stmt: $6call_function.2 = call $2load_deref.0(rnge, func=$2load_deref.0, args=[Var(rnge, rangeobj.py:250)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,165 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6call_function.2)\n", - "2024-10-16 10:11:14,166 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:11:14,166 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$2load_deref.0': [],\n", - " '$6call_function.2': [],\n", - " '$8return_value.3': [],\n", - " 'rnge': []})\n", - "2024-10-16 10:11:14,167 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:14,305 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=2232)\n", - " 2\tLOAD_FAST(arg=0, lineno=2234)\n", - " 4\tLOAD_METHOD(arg=0, lineno=2234)\n", - " 6\tCALL_METHOD(arg=0, lineno=2234)\n", - " 8\tRETURN_VALUE(arg=None, lineno=2234)\n", - "2024-10-16 10:11:14,306 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:14,306 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,307 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:14,307 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=2232)\n", - "2024-10-16 10:11:14,307 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,308 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=2234)\n", - "2024-10-16 10:11:14,308 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,308 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=0, lineno=2234)\n", - "2024-10-16 10:11:14,309 - numba.core.byteflow - DEBUG - stack ['$ary2.0']\n", - "2024-10-16 10:11:14,309 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_METHOD(arg=0, lineno=2234)\n", - "2024-10-16 10:11:14,310 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:11:14,310 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=2234)\n", - "2024-10-16 10:11:14,310 - numba.core.byteflow - DEBUG - stack ['$6call_method.2']\n", - "2024-10-16 10:11:14,311 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:14,311 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:14,312 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:14,312 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:14,312 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,313 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,313 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:14,314 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:14,314 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:14,314 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$ary2.0'}), (4, {'item': '$ary2.0', 'res': '$4load_method.1'}), (6, {'func': '$4load_method.1', 'args': [], 'res': '$6call_method.2'}), (8, {'retval': '$6call_method.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:14,315 - numba.core.interpreter - DEBUG - label 0:\n", - " ary = arg(0, name=ary) ['ary']\n", - " $4load_method.1 = getattr(value=ary, attr=flatten) ['$4load_method.1', 'ary']\n", - " $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$6call_method.2']\n", - " $8return_value.3 = cast(value=$6call_method.2) ['$6call_method.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:11:14,324 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:14,324 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,324 - numba.core.ssa - DEBUG - on stmt: ary = arg(0, name=ary)\n", - "2024-10-16 10:11:14,325 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=ary, attr=flatten)\n", - "2024-10-16 10:11:14,325 - numba.core.ssa - DEBUG - on stmt: $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,326 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6call_method.2)\n", - "2024-10-16 10:11:14,326 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:11:14,327 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$4load_method.1': [],\n", - " '$6call_method.2': [],\n", - " '$8return_value.3': [],\n", - " 'ary': []})\n", - "2024-10-16 10:11:14,327 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:14,336 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=2259)\n", - " 2\tLOAD_FAST(arg=0, lineno=2260)\n", - " 4\tLOAD_METHOD(arg=0, lineno=2260)\n", - " 6\tCALL_METHOD(arg=0, lineno=2260)\n", - " 8\tLOAD_METHOD(arg=1, lineno=2260)\n", - " 10\tLOAD_FAST(arg=0, lineno=2260)\n", - " 12\tLOAD_ATTR(arg=2, lineno=2260)\n", - " 14\tCALL_METHOD(arg=1, lineno=2260)\n", - " 16\tRETURN_VALUE(arg=None, lineno=2260)\n", - "2024-10-16 10:11:14,336 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:14,337 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,337 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:14,338 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=2259)\n", - "2024-10-16 10:11:14,338 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,338 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=2260)\n", - "2024-10-16 10:11:14,339 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,339 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=0, lineno=2260)\n", - "2024-10-16 10:11:14,340 - numba.core.byteflow - DEBUG - stack ['$ary2.0']\n", - "2024-10-16 10:11:14,340 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_METHOD(arg=0, lineno=2260)\n", - "2024-10-16 10:11:14,340 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:11:14,341 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=1, lineno=2260)\n", - "2024-10-16 10:11:14,341 - numba.core.byteflow - DEBUG - stack ['$6call_method.2']\n", - "2024-10-16 10:11:14,342 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_FAST(arg=0, lineno=2260)\n", - "2024-10-16 10:11:14,342 - numba.core.byteflow - DEBUG - stack ['$8load_method.3']\n", - "2024-10-16 10:11:14,342 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=2, lineno=2260)\n", - "2024-10-16 10:11:14,343 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$ary10.4']\n", - "2024-10-16 10:11:14,343 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=CALL_METHOD(arg=1, lineno=2260)\n", - "2024-10-16 10:11:14,344 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$12load_attr.5']\n", - "2024-10-16 10:11:14,344 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=RETURN_VALUE(arg=None, lineno=2260)\n", - "2024-10-16 10:11:14,344 - numba.core.byteflow - DEBUG - stack ['$14call_method.6']\n", - "2024-10-16 10:11:14,345 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:14,345 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:14,346 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:14,346 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:14,347 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,347 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,347 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:14,348 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:14,348 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:14,349 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$ary2.0'}), (4, {'item': '$ary2.0', 'res': '$4load_method.1'}), (6, {'func': '$4load_method.1', 'args': [], 'res': '$6call_method.2'}), (8, {'item': '$6call_method.2', 'res': '$8load_method.3'}), (10, {'res': '$ary10.4'}), (12, {'item': '$ary10.4', 'res': '$12load_attr.5'}), (14, {'func': '$8load_method.3', 'args': ['$12load_attr.5'], 'res': '$14call_method.6'}), (16, {'retval': '$14call_method.6', 'castval': '$16return_value.7'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:14,349 - numba.core.interpreter - DEBUG - label 0:\n", - " ary = arg(0, name=ary) ['ary']\n", - " $4load_method.1 = getattr(value=ary, attr=copy) ['$4load_method.1', 'ary']\n", - " $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$6call_method.2']\n", - " $8load_method.3 = getattr(value=$6call_method.2, attr=reshape) ['$6call_method.2', '$8load_method.3']\n", - " $12load_attr.5 = getattr(value=ary, attr=size) ['$12load_attr.5', 'ary']\n", - " $14call_method.6 = call $8load_method.3($12load_attr.5, func=$8load_method.3, args=[Var($12load_attr.5, arrayobj.py:2260)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_attr.5', '$14call_method.6', '$8load_method.3']\n", - " $16return_value.7 = cast(value=$14call_method.6) ['$14call_method.6', '$16return_value.7']\n", - " return $16return_value.7 ['$16return_value.7']\n", - "\n", - "2024-10-16 10:11:14,357 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:14,360 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,360 - numba.core.ssa - DEBUG - on stmt: ary = arg(0, name=ary)\n", - "2024-10-16 10:11:14,361 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=ary, attr=copy)\n", - "2024-10-16 10:11:14,361 - numba.core.ssa - DEBUG - on stmt: $6call_method.2 = call $4load_method.1(func=$4load_method.1, args=[], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,362 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6call_method.2, attr=reshape)\n", - "2024-10-16 10:11:14,362 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=ary, attr=size)\n", - "2024-10-16 10:11:14,362 - numba.core.ssa - DEBUG - on stmt: $14call_method.6 = call $8load_method.3($12load_attr.5, func=$8load_method.3, args=[Var($12load_attr.5, arrayobj.py:2260)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,363 - numba.core.ssa - DEBUG - on stmt: $16return_value.7 = cast(value=$14call_method.6)\n", - "2024-10-16 10:11:14,363 - numba.core.ssa - DEBUG - on stmt: return $16return_value.7\n", - "2024-10-16 10:11:14,364 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12load_attr.5': [],\n", - " '$14call_method.6': [],\n", - " '$16return_value.7': [],\n", - " '$4load_method.1': [],\n", - " '$6call_method.2': [],\n", - " '$8load_method.3': [],\n", - " 'ary': []})\n", - "2024-10-16 10:11:14,364 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:14,626 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3773)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3774)\n", - " 4\tLOAD_FAST(arg=0, lineno=3774)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=3774)\n", - " 8\tSTORE_FAST(arg=3, lineno=3774)\n", - " 10\tLOAD_DEREF(arg=0, lineno=3775)\n", - " 12\tLOAD_FAST(arg=0, lineno=3775)\n", - " 14\tLOAD_FAST(arg=1, lineno=3775)\n", - " 16\tLOAD_FAST(arg=1, lineno=3775)\n", - " 18\tLOAD_CONST(arg=1, lineno=3775)\n", - " 20\tLOAD_FAST(arg=3, lineno=3775)\n", - " 22\tLOAD_FAST(arg=3, lineno=3775)\n", - " 24\tCALL_FUNCTION(arg=6, lineno=3775)\n", - " 26\tRETURN_VALUE(arg=None, lineno=3775)\n", - "2024-10-16 10:11:14,627 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:14,627 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,627 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:14,628 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3773)\n", - "2024-10-16 10:11:14,628 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,629 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3774)\n", - "2024-10-16 10:11:14,629 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,629 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=3774)\n", - "2024-10-16 10:11:14,630 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:11:14,630 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=3774)\n", - "2024-10-16 10:11:14,631 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$a4.1']\n", - "2024-10-16 10:11:14,631 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=3, lineno=3774)\n", - "2024-10-16 10:11:14,632 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-10-16 10:11:14,632 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_DEREF(arg=0, lineno=3775)\n", - "2024-10-16 10:11:14,632 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,633 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=0, lineno=3775)\n", - "2024-10-16 10:11:14,633 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3']\n", - "2024-10-16 10:11:14,634 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-10-16 10:11:14,634 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4']\n", - "2024-10-16 10:11:14,634 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-10-16 10:11:14,635 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5']\n", - "2024-10-16 10:11:14,635 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=1, lineno=3775)\n", - "2024-10-16 10:11:14,636 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6']\n", - "2024-10-16 10:11:14,636 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-10-16 10:11:14,636 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7']\n", - "2024-10-16 10:11:14,637 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-10-16 10:11:14,637 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8']\n", - "2024-10-16 10:11:14,638 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=CALL_FUNCTION(arg=6, lineno=3775)\n", - "2024-10-16 10:11:14,638 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9']\n", - "2024-10-16 10:11:14,638 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=RETURN_VALUE(arg=None, lineno=3775)\n", - "2024-10-16 10:11:14,639 - numba.core.byteflow - DEBUG - stack ['$24call_function.10']\n", - "2024-10-16 10:11:14,639 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:14,640 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:14,640 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:14,640 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:14,641 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,641 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:14,642 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:14,642 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:14,642 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:14,643 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$a4.1'}), (6, {'func': '$2load_global.0', 'args': ['$a4.1'], 'res': '$6call_function.2'}), (8, {'value': '$6call_function.2'}), (10, {'res': '$10load_deref.3'}), (12, {'res': '$a12.4'}), (14, {'res': '$v14.5'}), (16, {'res': '$v16.6'}), (18, {'res': '$const18.7'}), (20, {'res': '$n20.8'}), (22, {'res': '$n22.9'}), (24, {'func': '$10load_deref.3', 'args': ['$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9'], 'res': '$24call_function.10'}), (26, {'retval': '$24call_function.10', 'castval': '$26return_value.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:14,644 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " side = arg(2, name=side) ['side']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'a', 'n']\n", - " $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f33dd9a2560>) ['$10load_deref.3']\n", - " $const18.7 = const(int, 0) ['$const18.7']\n", - " $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_deref.3', '$24call_function.10', '$const18.7', 'a', 'n', 'n', 'v', 'v']\n", - " $26return_value.11 = cast(value=$24call_function.10) ['$24call_function.10', '$26return_value.11']\n", - " return $26return_value.11 ['$26return_value.11']\n", - "\n", - "2024-10-16 10:11:14,650 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:14,650 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,651 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:14,651 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:14,651 - numba.core.ssa - DEBUG - on stmt: side = arg(2, name=side)\n", - "2024-10-16 10:11:14,652 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-10-16 10:11:14,652 - numba.core.ssa - DEBUG - on stmt: n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,653 - numba.core.ssa - DEBUG - on stmt: $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f33dd9a2560>)\n", - "2024-10-16 10:11:14,653 - numba.core.ssa - DEBUG - on stmt: $const18.7 = const(int, 0)\n", - "2024-10-16 10:11:14,653 - numba.core.ssa - DEBUG - on stmt: $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,654 - numba.core.ssa - DEBUG - on stmt: $26return_value.11 = cast(value=$24call_function.10)\n", - "2024-10-16 10:11:14,654 - numba.core.ssa - DEBUG - on stmt: return $26return_value.11\n", - "2024-10-16 10:11:14,655 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_deref.3': [],\n", - " '$24call_function.10': [],\n", - " '$26return_value.11': [],\n", - " '$2load_global.0': [],\n", - " '$const18.7': [],\n", - " 'a': [],\n", - " 'n': [],\n", - " 'side': [],\n", - " 'v': []})\n", - "2024-10-16 10:11:14,655 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:14,664 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3678)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3701)\n", - " 4\tLOAD_METHOD(arg=1, lineno=3701)\n", - " 6\tLOAD_FAST(arg=1, lineno=3701)\n", - " 8\tCALL_METHOD(arg=1, lineno=3701)\n", - " 10\tPOP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - " 12\tLOAD_GLOBAL(arg=2, lineno=3704)\n", - " 14\tLOAD_FAST(arg=5, lineno=3704)\n", - " 16\tLOAD_CONST(arg=1, lineno=3704)\n", - " 18\tLOAD_CONST(arg=2, lineno=3704)\n", - " 20\tCALL_FUNCTION(arg=3, lineno=3704)\n", - " 22\tGET_ITER(arg=None, lineno=3704)\n", - "> 24\tFOR_ITER(arg=15, lineno=3704)\n", - " 26\tSTORE_FAST(arg=6, lineno=3704)\n", - " 28\tLOAD_GLOBAL(arg=0, lineno=3705)\n", - " 30\tLOAD_METHOD(arg=1, lineno=3705)\n", - " 32\tLOAD_FAST(arg=0, lineno=3705)\n", - " 34\tLOAD_FAST(arg=6, lineno=3705)\n", - " 36\tLOAD_CONST(arg=3, lineno=3705)\n", - " 38\tBINARY_SUBTRACT(arg=None, lineno=3705)\n", - " 40\tBINARY_SUBSCR(arg=None, lineno=3705)\n", - " 42\tCALL_METHOD(arg=1, lineno=3705)\n", - " 44\tPOP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - " 46\tLOAD_FAST(arg=6, lineno=3706)\n", - " 48\tROT_TWO(arg=None, lineno=3706)\n", - " 50\tPOP_TOP(arg=None, lineno=3706)\n", - " 52\tRETURN_VALUE(arg=None, lineno=3706)\n", - "> 54\tJUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "> 56\tLOAD_CONST(arg=1, lineno=3707)\n", - " 58\tRETURN_VALUE(arg=None, lineno=3707)\n", - "> 60\tLOAD_FAST(arg=2, lineno=3709)\n", - " 62\tLOAD_FAST(arg=1, lineno=3709)\n", - " 64\tCOMPARE_OP(arg=0, lineno=3709)\n", - " 66\tPOP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - " 68\tLOAD_FAST(arg=5, lineno=3710)\n", - " 70\tSTORE_FAST(arg=4, lineno=3710)\n", - " 72\tJUMP_FORWARD(arg=12, lineno=3710)\n", - "> 74\tLOAD_CONST(arg=1, lineno=3712)\n", - " 76\tSTORE_FAST(arg=3, lineno=3712)\n", - " 78\tLOAD_FAST(arg=4, lineno=3713)\n", - " 80\tLOAD_FAST(arg=5, lineno=3713)\n", - " 82\tCOMPARE_OP(arg=0, lineno=3713)\n", - " 84\tPOP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - " 86\tLOAD_FAST(arg=4, lineno=3713)\n", - " 88\tLOAD_CONST(arg=3, lineno=3713)\n", - " 90\tBINARY_ADD(arg=None, lineno=3713)\n", - " 92\tJUMP_FORWARD(arg=1, lineno=3713)\n", - "> 94\tLOAD_FAST(arg=5, lineno=3713)\n", - "> 96\tSTORE_FAST(arg=4, lineno=3713)\n", - "> 98\tLOAD_FAST(arg=4, lineno=3715)\n", - " 100\tLOAD_FAST(arg=3, lineno=3715)\n", - " 102\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 104\tPOP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "> 106\tLOAD_FAST(arg=3, lineno=3716)\n", - " 108\tLOAD_FAST(arg=4, lineno=3716)\n", - " 110\tBINARY_ADD(arg=None, lineno=3716)\n", - " 112\tLOAD_CONST(arg=3, lineno=3716)\n", - " 114\tBINARY_RSHIFT(arg=None, lineno=3716)\n", - " 116\tSTORE_FAST(arg=7, lineno=3716)\n", - " 118\tLOAD_DEREF(arg=0, lineno=3717)\n", - " 120\tLOAD_FAST(arg=0, lineno=3717)\n", - " 122\tLOAD_FAST(arg=7, lineno=3717)\n", - " 124\tBINARY_SUBSCR(arg=None, lineno=3717)\n", - " 126\tLOAD_FAST(arg=1, lineno=3717)\n", - " 128\tCALL_FUNCTION(arg=2, lineno=3717)\n", - " 130\tPOP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - " 132\tLOAD_FAST(arg=7, lineno=3719)\n", - " 134\tLOAD_CONST(arg=3, lineno=3719)\n", - " 136\tBINARY_ADD(arg=None, lineno=3719)\n", - " 138\tSTORE_FAST(arg=3, lineno=3719)\n", - " 140\tJUMP_FORWARD(arg=2, lineno=3719)\n", - "> 142\tLOAD_FAST(arg=7, lineno=3722)\n", - " 144\tSTORE_FAST(arg=4, lineno=3722)\n", - "> 146\tLOAD_FAST(arg=4, lineno=3715)\n", - " 148\tLOAD_FAST(arg=3, lineno=3715)\n", - " 150\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 152\tPOP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "> 154\tLOAD_FAST(arg=3, lineno=3723)\n", - " 156\tRETURN_VALUE(arg=None, lineno=3723)\n", - "2024-10-16 10:11:14,664 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:14,665 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,665 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:14,666 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3678)\n", - "2024-10-16 10:11:14,666 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,666 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3701)\n", - "2024-10-16 10:11:14,667 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,667 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=1, lineno=3701)\n", - "2024-10-16 10:11:14,668 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:11:14,668 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=3701)\n", - "2024-10-16 10:11:14,668 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-10-16 10:11:14,669 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_METHOD(arg=1, lineno=3701)\n", - "2024-10-16 10:11:14,669 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$v6.2']\n", - "2024-10-16 10:11:14,670 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=POP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - "2024-10-16 10:11:14,670 - numba.core.byteflow - DEBUG - stack ['$8call_method.3']\n", - "2024-10-16 10:11:14,670 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=12, stack=(), blockstack=(), npush=0), Edge(pc=60, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,671 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=12 nstack_initial=0), State(pc_initial=60 nstack_initial=0)])\n", - "2024-10-16 10:11:14,671 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,672 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=12 nstack_initial=0)\n", - "2024-10-16 10:11:14,672 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_GLOBAL(arg=2, lineno=3704)\n", - "2024-10-16 10:11:14,672 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,673 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=5, lineno=3704)\n", - "2024-10-16 10:11:14,673 - numba.core.byteflow - DEBUG - stack ['$12load_global.0']\n", - "2024-10-16 10:11:14,674 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_CONST(arg=1, lineno=3704)\n", - "2024-10-16 10:11:14,674 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1']\n", - "2024-10-16 10:11:14,674 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=2, lineno=3704)\n", - "2024-10-16 10:11:14,675 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2']\n", - "2024-10-16 10:11:14,675 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=CALL_FUNCTION(arg=3, lineno=3704)\n", - "2024-10-16 10:11:14,676 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2', '$const18.3']\n", - "2024-10-16 10:11:14,676 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=GET_ITER(arg=None, lineno=3704)\n", - "2024-10-16 10:11:14,676 - numba.core.byteflow - DEBUG - stack ['$20call_function.4']\n", - "2024-10-16 10:11:14,677 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$22get_iter.5',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,677 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=0), State(pc_initial=24 nstack_initial=1)])\n", - "2024-10-16 10:11:14,678 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,678 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=60 nstack_initial=0)\n", - "2024-10-16 10:11:14,678 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_FAST(arg=2, lineno=3709)\n", - "2024-10-16 10:11:14,679 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,679 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_FAST(arg=1, lineno=3709)\n", - "2024-10-16 10:11:14,680 - numba.core.byteflow - DEBUG - stack ['$v_last60.0']\n", - "2024-10-16 10:11:14,680 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=COMPARE_OP(arg=0, lineno=3709)\n", - "2024-10-16 10:11:14,680 - numba.core.byteflow - DEBUG - stack ['$v_last60.0', '$v62.1']\n", - "2024-10-16 10:11:14,681 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=POP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - "2024-10-16 10:11:14,681 - numba.core.byteflow - DEBUG - stack ['$64compare_op.2']\n", - "2024-10-16 10:11:14,682 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=68, stack=(), blockstack=(), npush=0), Edge(pc=74, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,682 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0)])\n", - "2024-10-16 10:11:14,686 - numba.core.byteflow - DEBUG - stack: ['$phi24.0']\n", - "2024-10-16 10:11:14,687 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=24 nstack_initial=1)\n", - "2024-10-16 10:11:14,687 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=FOR_ITER(arg=15, lineno=3704)\n", - "2024-10-16 10:11:14,688 - numba.core.byteflow - DEBUG - stack ['$phi24.0']\n", - "2024-10-16 10:11:14,688 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=56, stack=(), blockstack=(), npush=0), Edge(pc=26, stack=('$phi24.0', '$24for_iter.2'), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,688 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2)])\n", - "2024-10-16 10:11:14,689 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,689 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=68 nstack_initial=0)\n", - "2024-10-16 10:11:14,690 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_FAST(arg=5, lineno=3710)\n", - "2024-10-16 10:11:14,690 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,690 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=STORE_FAST(arg=4, lineno=3710)\n", - "2024-10-16 10:11:14,691 - numba.core.byteflow - DEBUG - stack ['$n68.0']\n", - "2024-10-16 10:11:14,691 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=JUMP_FORWARD(arg=12, lineno=3710)\n", - "2024-10-16 10:11:14,692 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,692 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,692 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:14,693 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,693 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=0)\n", - "2024-10-16 10:11:14,694 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=1, lineno=3712)\n", - "2024-10-16 10:11:14,694 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,694 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=STORE_FAST(arg=3, lineno=3712)\n", - "2024-10-16 10:11:14,695 - numba.core.byteflow - DEBUG - stack ['$const74.0']\n", - "2024-10-16 10:11:14,695 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-10-16 10:11:14,696 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,696 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-10-16 10:11:14,696 - numba.core.byteflow - DEBUG - stack ['$hi78.1']\n", - "2024-10-16 10:11:14,697 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=COMPARE_OP(arg=0, lineno=3713)\n", - "2024-10-16 10:11:14,697 - numba.core.byteflow - DEBUG - stack ['$hi78.1', '$n80.2']\n", - "2024-10-16 10:11:14,698 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=POP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - "2024-10-16 10:11:14,698 - numba.core.byteflow - DEBUG - stack ['$82compare_op.3']\n", - "2024-10-16 10:11:14,698 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=86, stack=(), blockstack=(), npush=0), Edge(pc=94, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,699 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-10-16 10:11:14,699 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,700 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=0)\n", - "2024-10-16 10:11:14,700 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_CONST(arg=1, lineno=3707)\n", - "2024-10-16 10:11:14,700 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,701 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=RETURN_VALUE(arg=None, lineno=3707)\n", - "2024-10-16 10:11:14,701 - numba.core.byteflow - DEBUG - stack ['$const56.0']\n", - "2024-10-16 10:11:14,702 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:14,702 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-10-16 10:11:14,702 - numba.core.byteflow - DEBUG - stack: ['$phi26.0', '$phi26.1']\n", - "2024-10-16 10:11:14,703 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=26 nstack_initial=2)\n", - "2024-10-16 10:11:14,703 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=STORE_FAST(arg=6, lineno=3704)\n", - "2024-10-16 10:11:14,704 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$phi26.1']\n", - "2024-10-16 10:11:14,704 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_GLOBAL(arg=0, lineno=3705)\n", - "2024-10-16 10:11:14,704 - numba.core.byteflow - DEBUG - stack ['$phi26.0']\n", - "2024-10-16 10:11:14,705 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_METHOD(arg=1, lineno=3705)\n", - "2024-10-16 10:11:14,705 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$28load_global.2']\n", - "2024-10-16 10:11:14,706 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_FAST(arg=0, lineno=3705)\n", - "2024-10-16 10:11:14,706 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3']\n", - "2024-10-16 10:11:14,706 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=6, lineno=3705)\n", - "2024-10-16 10:11:14,707 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4']\n", - "2024-10-16 10:11:14,707 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_CONST(arg=3, lineno=3705)\n", - "2024-10-16 10:11:14,708 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5']\n", - "2024-10-16 10:11:14,708 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=BINARY_SUBTRACT(arg=None, lineno=3705)\n", - "2024-10-16 10:11:14,708 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5', '$const36.6']\n", - "2024-10-16 10:11:14,709 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=BINARY_SUBSCR(arg=None, lineno=3705)\n", - "2024-10-16 10:11:14,709 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$38binary_subtract.7']\n", - "2024-10-16 10:11:14,710 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=CALL_METHOD(arg=1, lineno=3705)\n", - "2024-10-16 10:11:14,710 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$40binary_subscr.8']\n", - "2024-10-16 10:11:14,710 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - "2024-10-16 10:11:14,711 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$42call_method.9']\n", - "2024-10-16 10:11:14,711 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=('$phi26.0',), blockstack=(), npush=0), Edge(pc=54, stack=('$phi26.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,712 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1)])\n", - "2024-10-16 10:11:14,712 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,712 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=98 nstack_initial=0)\n", - "2024-10-16 10:11:14,713 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-10-16 10:11:14,713 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,714 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-10-16 10:11:14,714 - numba.core.byteflow - DEBUG - stack ['$hi98.0']\n", - "2024-10-16 10:11:14,714 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-10-16 10:11:14,715 - numba.core.byteflow - DEBUG - stack ['$hi98.0', '$lo100.1']\n", - "2024-10-16 10:11:14,715 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=POP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "2024-10-16 10:11:14,716 - numba.core.byteflow - DEBUG - stack ['$102compare_op.2']\n", - "2024-10-16 10:11:14,716 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=106, stack=(), blockstack=(), npush=0), Edge(pc=154, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,716 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0)])\n", - "2024-10-16 10:11:14,717 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,717 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=86 nstack_initial=0)\n", - "2024-10-16 10:11:14,718 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-10-16 10:11:14,718 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,718 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_CONST(arg=3, lineno=3713)\n", - "2024-10-16 10:11:14,719 - numba.core.byteflow - DEBUG - stack ['$hi86.0']\n", - "2024-10-16 10:11:14,719 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=BINARY_ADD(arg=None, lineno=3713)\n", - "2024-10-16 10:11:14,720 - numba.core.byteflow - DEBUG - stack ['$hi86.0', '$const88.1']\n", - "2024-10-16 10:11:14,720 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=JUMP_FORWARD(arg=1, lineno=3713)\n", - "2024-10-16 10:11:14,720 - numba.core.byteflow - DEBUG - stack ['$90binary_add.2']\n", - "2024-10-16 10:11:14,721 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$90binary_add.2',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,721 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1)])\n", - "2024-10-16 10:11:14,722 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,722 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=94 nstack_initial=0)\n", - "2024-10-16 10:11:14,722 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-10-16 10:11:14,723 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,723 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$n94.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,724 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-10-16 10:11:14,724 - numba.core.byteflow - DEBUG - stack: ['$phi46.0']\n", - "2024-10-16 10:11:14,724 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=1)\n", - "2024-10-16 10:11:14,725 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=6, lineno=3706)\n", - "2024-10-16 10:11:14,725 - numba.core.byteflow - DEBUG - stack ['$phi46.0']\n", - "2024-10-16 10:11:14,726 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=ROT_TWO(arg=None, lineno=3706)\n", - "2024-10-16 10:11:14,726 - numba.core.byteflow - DEBUG - stack ['$phi46.0', '$i46.1']\n", - "2024-10-16 10:11:14,726 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=POP_TOP(arg=None, lineno=3706)\n", - "2024-10-16 10:11:14,727 - numba.core.byteflow - DEBUG - stack ['$i46.1', '$phi46.0']\n", - "2024-10-16 10:11:14,727 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=RETURN_VALUE(arg=None, lineno=3706)\n", - "2024-10-16 10:11:14,728 - numba.core.byteflow - DEBUG - stack ['$i46.1']\n", - "2024-10-16 10:11:14,728 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:14,728 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-10-16 10:11:14,729 - numba.core.byteflow - DEBUG - stack: ['$phi54.0']\n", - "2024-10-16 10:11:14,729 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=1)\n", - "2024-10-16 10:11:14,730 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=JUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "2024-10-16 10:11:14,730 - numba.core.byteflow - DEBUG - stack ['$phi54.0']\n", - "2024-10-16 10:11:14,730 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$phi54.0',), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,731 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1)])\n", - "2024-10-16 10:11:14,731 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,732 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=106 nstack_initial=0)\n", - "2024-10-16 10:11:14,732 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_FAST(arg=3, lineno=3716)\n", - "2024-10-16 10:11:14,732 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,733 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_FAST(arg=4, lineno=3716)\n", - "2024-10-16 10:11:14,733 - numba.core.byteflow - DEBUG - stack ['$lo106.0']\n", - "2024-10-16 10:11:14,734 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=BINARY_ADD(arg=None, lineno=3716)\n", - "2024-10-16 10:11:14,734 - numba.core.byteflow - DEBUG - stack ['$lo106.0', '$hi108.1']\n", - "2024-10-16 10:11:14,734 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=3, lineno=3716)\n", - "2024-10-16 10:11:14,735 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2']\n", - "2024-10-16 10:11:14,735 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BINARY_RSHIFT(arg=None, lineno=3716)\n", - "2024-10-16 10:11:14,736 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2', '$const112.3']\n", - "2024-10-16 10:11:14,736 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=STORE_FAST(arg=7, lineno=3716)\n", - "2024-10-16 10:11:14,736 - numba.core.byteflow - DEBUG - stack ['$114binary_rshift.4']\n", - "2024-10-16 10:11:14,737 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_DEREF(arg=0, lineno=3717)\n", - "2024-10-16 10:11:14,737 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,738 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=0, lineno=3717)\n", - "2024-10-16 10:11:14,738 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5']\n", - "2024-10-16 10:11:14,738 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_FAST(arg=7, lineno=3717)\n", - "2024-10-16 10:11:14,739 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6']\n", - "2024-10-16 10:11:14,739 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=BINARY_SUBSCR(arg=None, lineno=3717)\n", - "2024-10-16 10:11:14,740 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6', '$mid122.7']\n", - "2024-10-16 10:11:14,740 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_FAST(arg=1, lineno=3717)\n", - "2024-10-16 10:11:14,740 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8']\n", - "2024-10-16 10:11:14,741 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=CALL_FUNCTION(arg=2, lineno=3717)\n", - "2024-10-16 10:11:14,741 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8', '$v126.9']\n", - "2024-10-16 10:11:14,742 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=POP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - "2024-10-16 10:11:14,742 - numba.core.byteflow - DEBUG - stack ['$128call_function.10']\n", - "2024-10-16 10:11:14,742 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=132, stack=(), blockstack=(), npush=0), Edge(pc=142, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,743 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-10-16 10:11:14,743 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,744 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=154 nstack_initial=0)\n", - "2024-10-16 10:11:14,744 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_FAST(arg=3, lineno=3723)\n", - "2024-10-16 10:11:14,744 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,745 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=RETURN_VALUE(arg=None, lineno=3723)\n", - "2024-10-16 10:11:14,745 - numba.core.byteflow - DEBUG - stack ['$lo154.0']\n", - "2024-10-16 10:11:14,745 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:14,746 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-10-16 10:11:14,746 - numba.core.byteflow - DEBUG - stack: ['$phi96.0']\n", - "2024-10-16 10:11:14,747 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=96 nstack_initial=1)\n", - "2024-10-16 10:11:14,747 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=STORE_FAST(arg=4, lineno=3713)\n", - "2024-10-16 10:11:14,748 - numba.core.byteflow - DEBUG - stack ['$phi96.0']\n", - "2024-10-16 10:11:14,748 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,748 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:14,749 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:14,749 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-10-16 10:11:14,750 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,750 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=132 nstack_initial=0)\n", - "2024-10-16 10:11:14,750 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_FAST(arg=7, lineno=3719)\n", - "2024-10-16 10:11:14,751 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,751 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_CONST(arg=3, lineno=3719)\n", - "2024-10-16 10:11:14,752 - numba.core.byteflow - DEBUG - stack ['$mid132.0']\n", - "2024-10-16 10:11:14,752 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BINARY_ADD(arg=None, lineno=3719)\n", - "2024-10-16 10:11:14,752 - numba.core.byteflow - DEBUG - stack ['$mid132.0', '$const134.1']\n", - "2024-10-16 10:11:14,753 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=STORE_FAST(arg=3, lineno=3719)\n", - "2024-10-16 10:11:14,753 - numba.core.byteflow - DEBUG - stack ['$136binary_add.2']\n", - "2024-10-16 10:11:14,754 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=JUMP_FORWARD(arg=2, lineno=3719)\n", - "2024-10-16 10:11:14,754 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,754 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,755 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-10-16 10:11:14,755 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,756 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=142 nstack_initial=0)\n", - "2024-10-16 10:11:14,756 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=7, lineno=3722)\n", - "2024-10-16 10:11:14,756 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,757 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=STORE_FAST(arg=4, lineno=3722)\n", - "2024-10-16 10:11:14,757 - numba.core.byteflow - DEBUG - stack ['$mid142.0']\n", - "2024-10-16 10:11:14,758 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,758 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-10-16 10:11:14,758 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-10-16 10:11:14,759 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:14,759 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=146 nstack_initial=0)\n", - "2024-10-16 10:11:14,760 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-10-16 10:11:14,760 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:14,760 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-10-16 10:11:14,761 - numba.core.byteflow - DEBUG - stack ['$hi146.0']\n", - "2024-10-16 10:11:14,761 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-10-16 10:11:14,762 - numba.core.byteflow - DEBUG - stack ['$hi146.0', '$lo148.1']\n", - "2024-10-16 10:11:14,762 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=POP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "2024-10-16 10:11:14,762 - numba.core.byteflow - DEBUG - stack ['$150compare_op.2']\n", - "2024-10-16 10:11:14,763 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=154, stack=(), blockstack=(), npush=0), Edge(pc=106, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:14,763 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-10-16 10:11:14,764 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-10-16 10:11:14,764 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0)])\n", - "2024-10-16 10:11:14,764 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:14,765 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=12 nstack_initial=0): set(),\n", - " State(pc_initial=24 nstack_initial=1): {'$phi24.0'},\n", - " State(pc_initial=26 nstack_initial=2): {'$phi26.1'},\n", - " State(pc_initial=46 nstack_initial=1): set(),\n", - " State(pc_initial=54 nstack_initial=1): set(),\n", - " State(pc_initial=56 nstack_initial=0): set(),\n", - " State(pc_initial=60 nstack_initial=0): set(),\n", - " State(pc_initial=68 nstack_initial=0): set(),\n", - " State(pc_initial=74 nstack_initial=0): set(),\n", - " State(pc_initial=86 nstack_initial=0): set(),\n", - " State(pc_initial=94 nstack_initial=0): set(),\n", - " State(pc_initial=96 nstack_initial=1): {'$phi96.0'},\n", - " State(pc_initial=98 nstack_initial=0): set(),\n", - " State(pc_initial=106 nstack_initial=0): set(),\n", - " State(pc_initial=132 nstack_initial=0): set(),\n", - " State(pc_initial=142 nstack_initial=0): set(),\n", - " State(pc_initial=146 nstack_initial=0): set(),\n", - " State(pc_initial=154 nstack_initial=0): set()})\n", - "2024-10-16 10:11:14,765 - numba.core.byteflow - DEBUG - defmap: {'$phi24.0': State(pc_initial=12 nstack_initial=0),\n", - " '$phi26.1': State(pc_initial=24 nstack_initial=1),\n", - " '$phi96.0': State(pc_initial=86 nstack_initial=0)}\n", - "2024-10-16 10:11:14,766 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi54.0', State(pc_initial=54 nstack_initial=1))},\n", - " '$phi26.0': {('$phi24.0', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi54.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:14,767 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:14,767 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:14,768 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-10-16 10:11:14,768 - numba.core.byteflow - DEBUG - keep phismap: {'$phi24.0': {('$22get_iter.5', State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi96.0': {('$90binary_add.2', State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}}\n", - "2024-10-16 10:11:14,769 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=12 nstack_initial=0): {'$phi24.0': '$22get_iter.5'},\n", - " State(pc_initial=24 nstack_initial=1): {'$phi26.1': '$24for_iter.2'},\n", - " State(pc_initial=86 nstack_initial=0): {'$phi96.0': '$90binary_add.2'},\n", - " State(pc_initial=94 nstack_initial=0): {'$phi96.0': '$n94.0'}})\n", - "2024-10-16 10:11:14,769 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:14,770 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_method.1'}), (6, {'res': '$v6.2'}), (8, {'func': '$4load_method.1', 'args': ['$v6.2'], 'res': '$8call_method.3'}), (10, {'pred': '$8call_method.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={12: (), 60: ()})\n", - "2024-10-16 10:11:14,770 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=12 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((12, {'res': '$12load_global.0'}), (14, {'res': '$n14.1'}), (16, {'res': '$const16.2'}), (18, {'res': '$const18.3'}), (20, {'func': '$12load_global.0', 'args': ['$n14.1', '$const16.2', '$const18.3'], 'res': '$20call_function.4'}), (22, {'value': '$20call_function.4', 'res': '$22get_iter.5'})), outgoing_phis={'$phi24.0': '$22get_iter.5'}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$22get_iter.5',)})\n", - "2024-10-16 10:11:14,771 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=24 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((24, {'iterator': '$phi24.0', 'pair': '$24for_iter.1', 'indval': '$24for_iter.2', 'pred': '$24for_iter.3'}),), outgoing_phis={'$phi26.1': '$24for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={56: (), 26: ('$phi24.0', '$24for_iter.2')})\n", - "2024-10-16 10:11:14,771 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=26 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((26, {'value': '$phi26.1'}), (28, {'res': '$28load_global.2'}), (30, {'item': '$28load_global.2', 'res': '$30load_method.3'}), (32, {'res': '$a32.4'}), (34, {'res': '$i34.5'}), (36, {'res': '$const36.6'}), (38, {'lhs': '$i34.5', 'rhs': '$const36.6', 'res': '$38binary_subtract.7'}), (40, {'index': '$38binary_subtract.7', 'target': '$a32.4', 'res': '$40binary_subscr.8'}), (42, {'func': '$30load_method.3', 'args': ['$40binary_subscr.8'], 'res': '$42call_method.9'}), (44, {'pred': '$42call_method.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: ('$phi26.0',), 54: ('$phi26.0',)})\n", - "2024-10-16 10:11:14,772 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((46, {'res': '$i46.1'}), (52, {'retval': '$i46.1', 'castval': '$52return_value.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:14,772 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((54, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$phi54.0',)})\n", - "2024-10-16 10:11:14,772 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((56, {'res': '$const56.0'}), (58, {'retval': '$const56.0', 'castval': '$58return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:14,773 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=60 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((60, {'res': '$v_last60.0'}), (62, {'res': '$v62.1'}), (64, {'lhs': '$v_last60.0', 'rhs': '$v62.1', 'res': '$64compare_op.2'}), (66, {'pred': '$64compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={68: (), 74: ()})\n", - "2024-10-16 10:11:14,773 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=68 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((68, {'res': '$n68.0'}), (70, {'value': '$n68.0'}), (72, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-10-16 10:11:14,774 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((74, {'res': '$const74.0'}), (76, {'value': '$const74.0'}), (78, {'res': '$hi78.1'}), (80, {'res': '$n80.2'}), (82, {'lhs': '$hi78.1', 'rhs': '$n80.2', 'res': '$82compare_op.3'}), (84, {'pred': '$82compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={86: (), 94: ()})\n", - "2024-10-16 10:11:14,774 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=86 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((86, {'res': '$hi86.0'}), (88, {'res': '$const88.1'}), (90, {'lhs': '$hi86.0', 'rhs': '$const88.1', 'res': '$90binary_add.2'}), (92, {})), outgoing_phis={'$phi96.0': '$90binary_add.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$90binary_add.2',)})\n", - "2024-10-16 10:11:14,775 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=94 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((94, {'res': '$n94.0'}),), outgoing_phis={'$phi96.0': '$n94.0'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$n94.0',)})\n", - "2024-10-16 10:11:14,775 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=96 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((96, {'value': '$phi96.0'}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-10-16 10:11:14,775 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=98 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((98, {'res': '$hi98.0'}), (100, {'res': '$lo100.1'}), (102, {'lhs': '$hi98.0', 'rhs': '$lo100.1', 'res': '$102compare_op.2'}), (104, {'pred': '$102compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={106: (), 154: ()})\n", - "2024-10-16 10:11:14,776 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=106 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((106, {'res': '$lo106.0'}), (108, {'res': '$hi108.1'}), (110, {'lhs': '$lo106.0', 'rhs': '$hi108.1', 'res': '$110binary_add.2'}), (112, {'res': '$const112.3'}), (114, {'lhs': '$110binary_add.2', 'rhs': '$const112.3', 'res': '$114binary_rshift.4'}), (116, {'value': '$114binary_rshift.4'}), (118, {'res': '$118load_deref.5'}), (120, {'res': '$a120.6'}), (122, {'res': '$mid122.7'}), (124, {'index': '$mid122.7', 'target': '$a120.6', 'res': '$124binary_subscr.8'}), (126, {'res': '$v126.9'}), (128, {'func': '$118load_deref.5', 'args': ['$124binary_subscr.8', '$v126.9'], 'res': '$128call_function.10'}), (130, {'pred': '$128call_function.10'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={132: (), 142: ()})\n", - "2024-10-16 10:11:14,776 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=132 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((132, {'res': '$mid132.0'}), (134, {'res': '$const134.1'}), (136, {'lhs': '$mid132.0', 'rhs': '$const134.1', 'res': '$136binary_add.2'}), (138, {'value': '$136binary_add.2'}), (140, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-10-16 10:11:14,777 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=142 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((142, {'res': '$mid142.0'}), (144, {'value': '$mid142.0'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-10-16 10:11:14,777 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=146 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((146, {'res': '$hi146.0'}), (148, {'res': '$lo148.1'}), (150, {'lhs': '$hi146.0', 'rhs': '$lo148.1', 'res': '$150compare_op.2'}), (152, {'pred': '$150compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={154: (), 106: ()})\n", - "2024-10-16 10:11:14,777 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=154 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((154, {'res': '$lo154.0'}), (156, {'retval': '$lo154.0', 'castval': '$156return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:14,782 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " v_last = arg(2, name=v_last) ['v_last']\n", - " lo = arg(3, name=lo) ['lo']\n", - " hi = arg(4, name=hi) ['hi']\n", - " n = arg(5, name=n) ['n']\n", - " $2load_global.0 = global(np: ) ['$2load_global.0']\n", - " $4load_method.1 = getattr(value=$2load_global.0, attr=isnan) ['$2load_global.0', '$4load_method.1']\n", - " $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$8call_method.3', 'v']\n", - " bool10 = global(bool: ) ['bool10']\n", - " $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None) ['$10pred', '$8call_method.3', 'bool10']\n", - " branch $10pred, 12, 60 ['$10pred']\n", - "label 12:\n", - " $12load_global.0 = global(range: ) ['$12load_global.0']\n", - " $const16.2 = const(int, 0) ['$const16.2']\n", - " $const18.3 = const(int, -1) ['$const18.3']\n", - " $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_global.0', '$20call_function.4', '$const16.2', '$const18.3', 'n']\n", - " $22get_iter.5 = getiter(value=$20call_function.4) ['$20call_function.4', '$22get_iter.5']\n", - " $phi24.0 = $22get_iter.5 ['$22get_iter.5', '$phi24.0']\n", - " jump 24 []\n", - "label 24:\n", - " $24for_iter.1 = iternext(value=$phi24.0) ['$24for_iter.1', '$phi24.0']\n", - " $24for_iter.2 = pair_first(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.2']\n", - " $24for_iter.3 = pair_second(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.3']\n", - " $phi26.1 = $24for_iter.2 ['$24for_iter.2', '$phi26.1']\n", - " branch $24for_iter.3, 26, 56 ['$24for_iter.3']\n", - "label 26:\n", - " i = $phi26.1 ['$phi26.1', 'i']\n", - " $28load_global.2 = global(np: ) ['$28load_global.2']\n", - " $30load_method.3 = getattr(value=$28load_global.2, attr=isnan) ['$28load_global.2', '$30load_method.3']\n", - " $const36.6 = const(int, 1) ['$const36.6']\n", - " $38binary_subtract.7 = i - $const36.6 ['$38binary_subtract.7', '$const36.6', 'i']\n", - " $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=) ['$38binary_subtract.7', '$40binary_subscr.8', 'a']\n", - " $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None) ['$30load_method.3', '$40binary_subscr.8', '$42call_method.9']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None) ['$42call_method.9', '$44pred', 'bool44']\n", - " branch $44pred, 54, 46 ['$44pred']\n", - "label 46:\n", - " $52return_value.2 = cast(value=i) ['$52return_value.2', 'i']\n", - " return $52return_value.2 ['$52return_value.2']\n", - "label 54:\n", - " jump 24 []\n", - "label 56:\n", - " $const56.0 = const(int, 0) ['$const56.0']\n", - " $58return_value.1 = cast(value=$const56.0) ['$58return_value.1', '$const56.0']\n", - " return $58return_value.1 ['$58return_value.1']\n", - "label 60:\n", - " $64compare_op.2 = v_last < v ['$64compare_op.2', 'v', 'v_last']\n", - " bool66 = global(bool: ) ['bool66']\n", - " $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None) ['$64compare_op.2', '$66pred', 'bool66']\n", - " branch $66pred, 68, 74 ['$66pred']\n", - "label 68:\n", - " hi = n ['hi', 'n']\n", - " jump 98 []\n", - "label 74:\n", - " lo = const(int, 0) ['lo']\n", - " $82compare_op.3 = hi < n ['$82compare_op.3', 'hi', 'n']\n", - " bool84 = global(bool: ) ['bool84']\n", - " $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None) ['$82compare_op.3', '$84pred', 'bool84']\n", - " branch $84pred, 86, 94 ['$84pred']\n", - "label 86:\n", - " $const88.1 = const(int, 1) ['$const88.1']\n", - " $90binary_add.2 = hi + $const88.1 ['$90binary_add.2', '$const88.1', 'hi']\n", - " $phi96.0 = $90binary_add.2 ['$90binary_add.2', '$phi96.0']\n", - " jump 96 []\n", - "label 94:\n", - " $phi96.0 = n ['$phi96.0', 'n']\n", - " jump 96 []\n", - "label 96:\n", - " hi = $phi96.0 ['$phi96.0', 'hi']\n", - " jump 98 []\n", - "label 98:\n", - " $102compare_op.2 = hi > lo ['$102compare_op.2', 'hi', 'lo']\n", - " bool104 = global(bool: ) ['bool104']\n", - " $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$102compare_op.2', '$104pred', 'bool104']\n", - " branch $104pred, 106, 154 ['$104pred']\n", - "label 106:\n", - " $110binary_add.2 = lo + hi ['$110binary_add.2', 'hi', 'lo']\n", - " $const112.3 = const(int, 1) ['$const112.3']\n", - " mid = $110binary_add.2 >> $const112.3 ['$110binary_add.2', '$const112.3', 'mid']\n", - " $118load_deref.5 = freevar(func: ) ['$118load_deref.5']\n", - " $124binary_subscr.8 = getitem(value=a, index=mid, fn=) ['$124binary_subscr.8', 'a', 'mid']\n", - " $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$118load_deref.5', '$124binary_subscr.8', '$128call_function.10', 'v']\n", - " bool130 = global(bool: ) ['bool130']\n", - " $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None) ['$128call_function.10', '$130pred', 'bool130']\n", - " branch $130pred, 132, 142 ['$130pred']\n", - "label 132:\n", - " $const134.1 = const(int, 1) ['$const134.1']\n", - " lo = mid + $const134.1 ['$const134.1', 'lo', 'mid']\n", - " jump 146 []\n", - "label 142:\n", - " hi = mid ['hi', 'mid']\n", - " jump 146 []\n", - "label 146:\n", - " $150compare_op.2 = hi > lo ['$150compare_op.2', 'hi', 'lo']\n", - " bool152 = global(bool: ) ['bool152']\n", - " $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$150compare_op.2', '$152pred', 'bool152']\n", - " branch $152pred, 106, 154 ['$152pred']\n", - "label 154:\n", - " $156return_value.1 = cast(value=lo) ['$156return_value.1', 'lo']\n", - " return $156return_value.1 ['$156return_value.1']\n", - "\n", - "2024-10-16 10:11:14,817 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:14,817 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,818 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:14,818 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:14,818 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:14,819 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:14,819 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:14,820 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:14,820 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:14,820 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:14,821 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,821 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:14,822 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,822 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:14,822 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 12\n", - "2024-10-16 10:11:14,823 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,823 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:14,824 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:14,824 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:14,824 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,825 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:14,825 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:14,826 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:14,826 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 24\n", - "2024-10-16 10:11:14,826 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,827 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:14,827 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:14,828 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:14,828 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:14,828 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:14,829 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 26\n", - "2024-10-16 10:11:14,829 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,830 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:14,830 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:14,830 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:14,831 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:14,831 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:14,832 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:14,832 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,832 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:14,833 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,833 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:14,834 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-10-16 10:11:14,834 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,834 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:14,835 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:14,835 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-10-16 10:11:14,835 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,836 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:14,836 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-10-16 10:11:14,837 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,837 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:14,837 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:14,838 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:14,838 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 60\n", - "2024-10-16 10:11:14,839 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,839 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:14,839 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:14,840 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,840 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:14,841 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 68\n", - "2024-10-16 10:11:14,841 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,841 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:14,842 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:14,842 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-10-16 10:11:14,843 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,843 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-10-16 10:11:14,844 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:14,844 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:14,844 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,845 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:14,845 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 86\n", - "2024-10-16 10:11:14,846 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,846 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:14,847 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:14,847 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:14,848 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:14,848 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 94\n", - "2024-10-16 10:11:14,848 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,849 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:14,849 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:14,850 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 96\n", - "2024-10-16 10:11:14,850 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,851 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:14,851 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:14,851 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 98\n", - "2024-10-16 10:11:14,852 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,852 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:14,853 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:14,853 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,853 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:14,854 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 106\n", - "2024-10-16 10:11:14,854 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,855 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:14,855 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:14,856 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:14,856 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-10-16 10:11:14,856 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:14,857 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,857 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:14,858 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,858 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:14,859 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 132\n", - "2024-10-16 10:11:14,859 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,860 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:14,860 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-10-16 10:11:14,861 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:14,861 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 142\n", - "2024-10-16 10:11:14,862 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,862 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:14,863 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:14,863 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 146\n", - "2024-10-16 10:11:14,864 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,864 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:14,865 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:14,865 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,865 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:14,866 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 154\n", - "2024-10-16 10:11:14,866 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,867 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:14,867 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:14,869 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102compare_op.2': [],\n", - " '$104pred': [],\n", - " '$10pred': [],\n", - " '$110binary_add.2': [],\n", - " '$118load_deref.5': [],\n", - " '$124binary_subscr.8': [],\n", - " '$128call_function.10': [],\n", - " '$12load_global.0': [],\n", - " '$130pred': [],\n", - " '$150compare_op.2': [],\n", - " '$152pred': [],\n", - " '$156return_value.1': [],\n", - " '$20call_function.4': [],\n", - " '$22get_iter.5': [],\n", - " '$24for_iter.1': [],\n", - " '$24for_iter.2': [],\n", - " '$24for_iter.3': [],\n", - " '$28load_global.2': [],\n", - " '$2load_global.0': [],\n", - " '$30load_method.3': [],\n", - " '$38binary_subtract.7': [],\n", - " '$40binary_subscr.8': [],\n", - " '$42call_method.9': [],\n", - " '$44pred': [],\n", - " '$4load_method.1': [],\n", - " '$52return_value.2': [],\n", - " '$58return_value.1': [],\n", - " '$64compare_op.2': [],\n", - " '$66pred': [],\n", - " '$82compare_op.3': [],\n", - " '$84pred': [],\n", - " '$8call_method.3': [],\n", - " '$90binary_add.2': [],\n", - " '$const112.3': [],\n", - " '$const134.1': [],\n", - " '$const16.2': [],\n", - " '$const18.3': [],\n", - " '$const36.6': [],\n", - " '$const56.0': [],\n", - " '$const88.1': [],\n", - " '$phi24.0': [],\n", - " '$phi26.1': [],\n", - " '$phi96.0': [,\n", - " ],\n", - " 'a': [],\n", - " 'bool10': [],\n", - " 'bool104': [],\n", - " 'bool130': [],\n", - " 'bool152': [],\n", - " 'bool44': [],\n", - " 'bool66': [],\n", - " 'bool84': [],\n", - " 'hi': [,\n", - " ,\n", - " ,\n", - " ],\n", - " 'i': [],\n", - " 'lo': [,\n", - " ,\n", - " ],\n", - " 'mid': [],\n", - " 'n': [],\n", - " 'v': [],\n", - " 'v_last': []})\n", - "2024-10-16 10:11:14,869 - numba.core.ssa - DEBUG - SSA violators {'lo', 'hi', '$phi96.0'}\n", - "2024-10-16 10:11:14,870 - numba.core.ssa - DEBUG - Fix SSA violator on var lo\n", - "2024-10-16 10:11:14,870 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:14,871 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,871 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:14,871 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:14,872 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:14,872 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:14,873 - numba.core.ssa - DEBUG - first assign: lo\n", - "2024-10-16 10:11:14,873 - numba.core.ssa - DEBUG - replaced with: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:14,873 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:14,874 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:14,874 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:14,875 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:14,875 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,875 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:14,876 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,892 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:14,892 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:14,892 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,893 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:14,893 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:14,893 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:14,894 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,894 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:14,895 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:14,895 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:14,895 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:14,896 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,896 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:14,897 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:14,899 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:14,900 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:14,900 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:14,901 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:14,902 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,902 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:14,903 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:14,903 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:14,904 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:14,905 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:14,905 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:14,906 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,907 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:14,907 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,908 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:14,908 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:14,909 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,910 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:14,911 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:14,911 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:14,912 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,912 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:14,913 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:14,913 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,914 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:14,915 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:14,915 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:14,916 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:14,916 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,917 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:14,918 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:14,918 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,919 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:14,920 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:14,920 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,920 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:14,921 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:14,921 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:14,922 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,922 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-10-16 10:11:14,923 - numba.core.ssa - DEBUG - replaced with: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:14,923 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:14,923 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:14,924 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,924 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:14,925 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:14,925 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,926 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:14,926 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:14,927 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:14,927 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:14,927 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:14,928 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,928 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:14,929 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:14,929 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:14,930 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,934 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:14,934 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:14,935 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:14,935 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,935 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:14,936 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:14,936 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,937 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:14,937 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:14,938 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,938 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:14,939 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:14,939 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:14,940 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-10-16 10:11:14,940 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:14,940 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,941 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:14,941 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,942 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:14,943 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:14,946 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,947 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:14,947 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-10-16 10:11:14,948 - numba.core.ssa - DEBUG - replaced with: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:14,949 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:14,949 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:14,950 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,950 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:14,951 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:14,952 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:14,953 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,953 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:14,954 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:14,954 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,955 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:14,956 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:14,956 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,957 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:14,958 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:14,958 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 74: [],\n", - " 132: []})\n", - "2024-10-16 10:11:14,959 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:14,959 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,960 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:14,960 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:14,961 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:14,961 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:14,961 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:14,962 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:14,962 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:14,963 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:14,963 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,964 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:14,964 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,965 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:14,965 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:14,966 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,966 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:14,967 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:14,967 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:14,968 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,968 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:14,969 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:14,969 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:14,970 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:14,970 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,971 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:14,971 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:14,972 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:14,972 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:14,972 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:14,973 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:14,973 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,974 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:14,979 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:14,979 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:14,980 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:14,980 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:14,981 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:14,981 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,982 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:14,983 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,984 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:14,984 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:14,985 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,986 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:14,986 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:14,987 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:14,987 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,988 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:14,989 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:14,989 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,990 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:14,990 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:14,991 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:14,992 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:14,992 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,993 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:14,993 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:14,994 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:14,995 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:14,995 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:14,996 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,997 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:14,997 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:14,998 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:14,998 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:14,999 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:15,000 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:15,001 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:15,001 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,002 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:15,002 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:15,003 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,003 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:15,004 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:15,005 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:15,005 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,006 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:15,007 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,007 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:15,008 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,009 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:15,009 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,010 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:15,010 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:15,011 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:15,012 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,012 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:15,013 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$102compare_op.2 = hi > lo\n", - "2024-10-16 10:11:15,013 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-10-16 10:11:15,014 - numba.core.ssa - DEBUG - insert phi node lo.3 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-10-16 10:11:15,014 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-10-16 10:11:15,015 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-10-16 10:11:15,015 - numba.core.ssa - DEBUG - idom 74 from label 96\n", - "2024-10-16 10:11:15,016 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-10-16 10:11:15,016 - numba.core.ssa - DEBUG - incoming_def lo.1 = const(int, 0)\n", - "2024-10-16 10:11:15,017 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:15,017 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-10-16 10:11:15,018 - numba.core.ssa - DEBUG - idom 60 from label 68\n", - "2024-10-16 10:11:15,018 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-10-16 10:11:15,019 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-10-16 10:11:15,019 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-10-16 10:11:15,020 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:15,020 - numba.core.ssa - DEBUG - incoming_def lo = arg(3, name=lo)\n", - "2024-10-16 10:11:15,020 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:15,021 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:15,021 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,022 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:15,022 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:15,023 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,023 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:15,027 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$110binary_add.2 = lo + hi\n", - "2024-10-16 10:11:15,027 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-10-16 10:11:15,028 - numba.core.ssa - DEBUG - insert phi node lo.4 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-10-16 10:11:15,028 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-10-16 10:11:15,029 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:15,030 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-10-16 10:11:15,030 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-10-16 10:11:15,031 - numba.core.ssa - DEBUG - insert phi node lo.5 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-10-16 10:11:15,032 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-10-16 10:11:15,032 - numba.core.ssa - DEBUG - incoming_def lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:15,033 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-10-16 10:11:15,034 - numba.core.ssa - DEBUG - find_def_from_top label 142\n", - "2024-10-16 10:11:15,034 - numba.core.ssa - DEBUG - idom 106 from label 142\n", - "2024-10-16 10:11:15,035 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-10-16 10:11:15,036 - numba.core.ssa - DEBUG - incoming_def lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-10-16 10:11:15,036 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:15,037 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:15,037 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:15,038 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:15,039 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-10-16 10:11:15,040 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:15,040 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,041 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:15,041 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,042 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:15,043 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:15,043 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,044 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:15,045 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:15,045 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,046 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:15,047 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,047 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:15,048 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,049 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:15,049 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,050 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:15,050 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$150compare_op.2 = hi > lo\n", - "2024-10-16 10:11:15,051 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:15,052 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:15,052 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,053 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:15,054 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:15,054 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,055 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:15,056 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$156return_value.1 = cast(value=lo)\n", - "2024-10-16 10:11:15,056 - numba.core.ssa - DEBUG - find_def_from_top label 154\n", - "2024-10-16 10:11:15,057 - numba.core.ssa - DEBUG - insert phi node lo.6 = phi(incoming_values=[], incoming_blocks=[]) at 154\n", - "2024-10-16 10:11:15,058 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-10-16 10:11:15,058 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:15,059 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-10-16 10:11:15,059 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:15,060 - numba.core.ssa - DEBUG - replaced with: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:15,061 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:15,062 - numba.core.ssa - DEBUG - Fix SSA violator on var hi\n", - "2024-10-16 10:11:15,062 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:15,063 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,063 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:15,064 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:15,065 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:15,065 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:15,066 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:15,067 - numba.core.ssa - DEBUG - first assign: hi\n", - "2024-10-16 10:11:15,067 - numba.core.ssa - DEBUG - replaced with: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:15,068 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:15,068 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:15,069 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:15,070 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,070 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:15,071 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,071 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:15,072 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:15,072 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,072 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:15,074 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:15,075 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:15,075 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,076 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:15,076 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:15,076 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:15,077 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:15,077 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,078 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:15,078 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:15,079 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:15,079 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:15,080 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:15,082 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:15,082 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,083 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:15,083 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:15,084 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:15,084 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:15,085 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:15,086 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:15,086 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,087 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:15,087 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,088 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:15,088 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:15,089 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,089 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:15,090 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:15,090 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:15,091 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,091 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:15,092 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:15,092 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,093 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:15,093 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:15,094 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:15,094 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:15,095 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,095 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:15,096 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:15,096 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,097 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:15,097 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:15,100 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,100 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-10-16 10:11:15,101 - numba.core.ssa - DEBUG - replaced with: hi.1 = n\n", - "2024-10-16 10:11:15,101 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:15,102 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:15,102 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,103 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:15,104 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:15,105 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:15,105 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,106 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:15,107 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:15,107 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,108 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:15,108 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:15,109 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:15,110 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,110 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:15,111 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,111 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:15,112 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,113 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:15,113 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,114 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-10-16 10:11:15,115 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0\n", - "2024-10-16 10:11:15,115 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:15,116 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:15,116 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,117 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:15,118 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:15,118 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:15,119 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,119 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:15,120 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:15,120 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,121 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,121 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:15,121 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:15,122 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:15,122 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-10-16 10:11:15,123 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:15,123 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,124 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:15,124 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,125 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:15,125 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:15,126 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,126 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:15,126 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:15,127 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,127 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:15,128 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,128 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-10-16 10:11:15,129 - numba.core.ssa - DEBUG - replaced with: hi.3 = mid\n", - "2024-10-16 10:11:15,129 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,129 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:15,130 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,130 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:15,131 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:15,131 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:15,132 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,132 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:15,133 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:15,133 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,134 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,134 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:15,135 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:15,135 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 68: [],\n", - " 96: [],\n", - " 142: []})\n", - "2024-10-16 10:11:15,136 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:15,136 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,137 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:15,137 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:15,143 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:15,144 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:15,144 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:15,145 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:15,145 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:15,146 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:15,146 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,147 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:15,147 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,148 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:15,149 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:15,150 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,150 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:15,151 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:15,151 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:15,152 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,152 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:15,154 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:15,154 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:15,155 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:15,155 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,156 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:15,156 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:15,156 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:15,158 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:15,158 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:15,159 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:15,159 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,160 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:15,160 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:15,161 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:15,161 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:15,162 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:15,162 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:15,164 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,164 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:15,165 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,165 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:15,166 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:15,166 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,167 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:15,167 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:15,168 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:15,168 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,170 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:15,170 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:15,171 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,171 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:15,172 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:15,172 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:15,173 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:15,173 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,173 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:15,174 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:15,174 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,175 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:15,175 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:15,176 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,176 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-10-16 10:11:15,177 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:15,177 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:15,178 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,178 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:15,181 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:15,182 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$82compare_op.3 = hi < n\n", - "2024-10-16 10:11:15,182 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-10-16 10:11:15,183 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-10-16 10:11:15,183 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-10-16 10:11:15,184 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-10-16 10:11:15,184 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-10-16 10:11:15,185 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:15,186 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:15,186 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,187 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:15,187 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:15,188 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,188 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:15,190 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:15,190 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:15,191 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-10-16 10:11:15,191 - numba.core.ssa - DEBUG - idom 74 from label 86\n", - "2024-10-16 10:11:15,192 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-10-16 10:11:15,192 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-10-16 10:11:15,192 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-10-16 10:11:15,193 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-10-16 10:11:15,193 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-10-16 10:11:15,194 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-10-16 10:11:15,194 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-10-16 10:11:15,195 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:15,195 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,197 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:15,198 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,198 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:15,199 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,200 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:15,200 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,201 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-10-16 10:11:15,201 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:15,202 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:15,203 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,203 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:15,204 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:15,204 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$102compare_op.2 = hi > lo.3\n", - "2024-10-16 10:11:15,205 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-10-16 10:11:15,205 - numba.core.ssa - DEBUG - insert phi node hi.4 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-10-16 10:11:15,206 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-10-16 10:11:15,206 - numba.core.ssa - DEBUG - incoming_def hi.2 = $phi96.0\n", - "2024-10-16 10:11:15,207 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-10-16 10:11:15,207 - numba.core.ssa - DEBUG - incoming_def hi.1 = n\n", - "2024-10-16 10:11:15,209 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi.4 > lo.3\n", - "2024-10-16 10:11:15,210 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:15,210 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,211 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:15,211 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:15,212 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,212 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,213 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:15,214 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$110binary_add.2 = lo.4 + hi\n", - "2024-10-16 10:11:15,214 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-10-16 10:11:15,215 - numba.core.ssa - DEBUG - insert phi node hi.5 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-10-16 10:11:15,215 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-10-16 10:11:15,216 - numba.core.ssa - DEBUG - incoming_def hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:15,216 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-10-16 10:11:15,217 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-10-16 10:11:15,217 - numba.core.ssa - DEBUG - insert phi node hi.6 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-10-16 10:11:15,218 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-10-16 10:11:15,219 - numba.core.ssa - DEBUG - find_def_from_top label 132\n", - "2024-10-16 10:11:15,220 - numba.core.ssa - DEBUG - idom 106 from label 132\n", - "2024-10-16 10:11:15,220 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-10-16 10:11:15,221 - numba.core.ssa - DEBUG - incoming_def hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-10-16 10:11:15,221 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-10-16 10:11:15,222 - numba.core.ssa - DEBUG - incoming_def hi.3 = mid\n", - "2024-10-16 10:11:15,222 - numba.core.ssa - DEBUG - incoming_def hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:15,223 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi.5\n", - "2024-10-16 10:11:15,223 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:15,224 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:15,226 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-10-16 10:11:15,226 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:15,227 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,227 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:15,228 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,228 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:15,229 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:15,230 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,230 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:15,231 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:15,231 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,232 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:15,232 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,233 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-10-16 10:11:15,233 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,234 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:15,234 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,235 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:15,235 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:15,236 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$150compare_op.2 = hi > lo.5\n", - "2024-10-16 10:11:15,236 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi.6 > lo.5\n", - "2024-10-16 10:11:15,237 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:15,237 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,240 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:15,240 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:15,241 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,241 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,242 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:15,242 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:15,243 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi96.0\n", - "2024-10-16 10:11:15,243 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:15,244 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,244 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:15,246 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:15,246 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:15,247 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:15,247 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:15,248 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:15,248 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:15,249 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:15,250 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,251 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:15,251 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,252 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:15,252 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:15,253 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,253 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:15,254 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:15,255 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:15,255 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,256 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:15,257 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:15,257 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:15,258 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:15,259 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,259 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:15,260 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:15,260 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:15,261 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:15,261 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:15,262 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:15,262 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,262 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:15,263 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:15,263 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:15,264 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:15,264 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:15,265 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:15,265 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,266 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:15,266 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,267 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:15,267 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:15,270 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,271 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:15,271 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:15,272 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:15,272 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,272 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:15,273 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:15,273 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,274 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:15,274 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:15,275 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:15,275 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:15,276 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,278 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:15,278 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:15,279 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,279 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:15,280 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:15,280 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,281 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-10-16 10:11:15,281 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:15,282 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:15,282 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,282 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:15,283 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:15,283 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:15,284 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,284 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:15,285 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:15,285 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,286 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:15,286 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:15,289 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:15,290 - numba.core.ssa - DEBUG - first assign: $phi96.0\n", - "2024-10-16 10:11:15,290 - numba.core.ssa - DEBUG - replaced with: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:15,291 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,292 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:15,292 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,293 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-10-16 10:11:15,293 - numba.core.ssa - DEBUG - replaced with: $phi96.0.1 = n\n", - "2024-10-16 10:11:15,294 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,294 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:15,295 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,295 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-10-16 10:11:15,296 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:15,296 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:15,296 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,297 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:15,297 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:15,298 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-10-16 10:11:15,298 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:15,299 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,299 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:15,302 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:15,302 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,303 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,303 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,304 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-10-16 10:11:15,304 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:15,305 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:15,305 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-10-16 10:11:15,306 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:15,306 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,308 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:15,308 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,309 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:15,309 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:15,310 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,310 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:15,311 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:15,311 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,312 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:15,312 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,314 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-10-16 10:11:15,314 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,315 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:15,315 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,316 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:15,317 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:15,317 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-10-16 10:11:15,318 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:15,318 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,319 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:15,319 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:15,320 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,321 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,322 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:15,322 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:15,323 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {86: [],\n", - " 94: []})\n", - "2024-10-16 10:11:15,323 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-10-16 10:11:15,324 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,324 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:15,326 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-10-16 10:11:15,326 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-10-16 10:11:15,326 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-10-16 10:11:15,327 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-10-16 10:11:15,327 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-10-16 10:11:15,328 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-10-16 10:11:15,328 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-10-16 10:11:15,329 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,329 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:15,330 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,330 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-10-16 10:11:15,331 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-10-16 10:11:15,331 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,331 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-10-16 10:11:15,332 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-10-16 10:11:15,332 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-10-16 10:11:15,335 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,336 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-10-16 10:11:15,336 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-10-16 10:11:15,337 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:15,337 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-10-16 10:11:15,338 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,338 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-10-16 10:11:15,339 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-10-16 10:11:15,340 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-10-16 10:11:15,340 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-10-16 10:11:15,341 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-10-16 10:11:15,342 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-10-16 10:11:15,342 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,343 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-10-16 10:11:15,344 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-10-16 10:11:15,344 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-10-16 10:11:15,345 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-10-16 10:11:15,345 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-10-16 10:11:15,346 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-10-16 10:11:15,347 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,348 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:15,348 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,349 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-10-16 10:11:15,349 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-10-16 10:11:15,350 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,351 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-10-16 10:11:15,351 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-10-16 10:11:15,352 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-10-16 10:11:15,353 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,353 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-10-16 10:11:15,354 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-10-16 10:11:15,354 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,355 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-10-16 10:11:15,355 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-10-16 10:11:15,356 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-10-16 10:11:15,357 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-10-16 10:11:15,358 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,358 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-10-16 10:11:15,359 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-10-16 10:11:15,359 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,360 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-10-16 10:11:15,361 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-10-16 10:11:15,361 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,362 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-10-16 10:11:15,363 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:15,363 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-10-16 10:11:15,364 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,364 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-10-16 10:11:15,365 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-10-16 10:11:15,365 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-10-16 10:11:15,366 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,366 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-10-16 10:11:15,368 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-10-16 10:11:15,368 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,369 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-10-16 10:11:15,369 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-10-16 10:11:15,370 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:15,371 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,371 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-10-16 10:11:15,372 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,373 - numba.core.ssa - DEBUG - on stmt: $phi96.0.1 = n\n", - "2024-10-16 10:11:15,373 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-10-16 10:11:15,374 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-10-16 10:11:15,374 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,375 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-10-16 10:11:15,376 - numba.core.ssa - DEBUG - find_def var='$phi96.0' stmt=hi.2 = $phi96.0\n", - "2024-10-16 10:11:15,376 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-10-16 10:11:15,377 - numba.core.ssa - DEBUG - insert phi node $phi96.0.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-10-16 10:11:15,378 - numba.core.ssa - DEBUG - find_def_from_bottom label 94\n", - "2024-10-16 10:11:15,378 - numba.core.ssa - DEBUG - incoming_def $phi96.0.1 = n\n", - "2024-10-16 10:11:15,379 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-10-16 10:11:15,379 - numba.core.ssa - DEBUG - incoming_def $phi96.0 = $90binary_add.2\n", - "2024-10-16 10:11:15,380 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0.2\n", - "2024-10-16 10:11:15,381 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-10-16 10:11:15,381 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-10-16 10:11:15,382 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,383 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:15,383 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-10-16 10:11:15,384 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-10-16 10:11:15,385 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-10-16 10:11:15,385 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,386 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-10-16 10:11:15,387 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-10-16 10:11:15,387 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,388 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,388 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,389 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-10-16 10:11:15,390 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-10-16 10:11:15,391 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-10-16 10:11:15,391 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-10-16 10:11:15,392 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-10-16 10:11:15,392 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,393 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-10-16 10:11:15,394 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,395 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-10-16 10:11:15,395 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-10-16 10:11:15,396 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,396 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-10-16 10:11:15,397 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-10-16 10:11:15,397 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,398 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-10-16 10:11:15,399 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,400 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-10-16 10:11:15,400 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-10-16 10:11:15,401 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-10-16 10:11:15,401 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,402 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:15,403 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-10-16 10:11:15,403 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-10-16 10:11:15,404 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-10-16 10:11:15,405 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,405 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-10-16 10:11:15,406 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-10-16 10:11:15,406 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,407 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-10-16 10:11:15,408 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-10-16 10:11:15,408 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-10-16 10:11:15,439 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=1049)\n", - " 2\tLOAD_FAST(arg=0, lineno=1051)\n", - " 4\tLOAD_FAST(arg=1, lineno=1051)\n", - " 6\tCOMPARE_OP(arg=0, lineno=1051)\n", - " 8\tRETURN_VALUE(arg=None, lineno=1051)\n", - "2024-10-16 10:11:15,440 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:15,441 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,441 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:15,442 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=1049)\n", - "2024-10-16 10:11:15,442 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,443 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=1051)\n", - "2024-10-16 10:11:15,443 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,444 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=1, lineno=1051)\n", - "2024-10-16 10:11:15,444 - numba.core.byteflow - DEBUG - stack ['$a2.0']\n", - "2024-10-16 10:11:15,444 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=COMPARE_OP(arg=0, lineno=1051)\n", - "2024-10-16 10:11:15,445 - numba.core.byteflow - DEBUG - stack ['$a2.0', '$b4.1']\n", - "2024-10-16 10:11:15,447 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=1051)\n", - "2024-10-16 10:11:15,447 - numba.core.byteflow - DEBUG - stack ['$6compare_op.2']\n", - "2024-10-16 10:11:15,448 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:15,448 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:15,449 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:15,450 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:15,451 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:15,451 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:15,452 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:15,452 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:15,453 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:15,453 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$a2.0'}), (4, {'res': '$b4.1'}), (6, {'lhs': '$a2.0', 'rhs': '$b4.1', 'res': '$6compare_op.2'}), (8, {'retval': '$6compare_op.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:15,455 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " b = arg(1, name=b) ['b']\n", - " $6compare_op.2 = a < b ['$6compare_op.2', 'a', 'b']\n", - " $8return_value.3 = cast(value=$6compare_op.2) ['$6compare_op.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-10-16 10:11:15,467 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:15,468 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,468 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-10-16 10:11:15,469 - numba.core.ssa - DEBUG - on stmt: b = arg(1, name=b)\n", - "2024-10-16 10:11:15,469 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = a < b\n", - "2024-10-16 10:11:15,470 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6compare_op.2)\n", - "2024-10-16 10:11:15,470 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-10-16 10:11:15,471 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$6compare_op.2': [],\n", - " '$8return_value.3': [],\n", - " 'a': [],\n", - " 'b': []})\n", - "2024-10-16 10:11:15,472 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:15,642 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=255)\n", - " 2\tLOAD_FAST(arg=0, lineno=257)\n", - " 4\tLOAD_ATTR(arg=0, lineno=257)\n", - " 6\tLOAD_CONST(arg=1, lineno=257)\n", - " 8\tCOMPARE_OP(arg=4, lineno=257)\n", - " 10\tPOP_JUMP_IF_FALSE(arg=19, lineno=257)\n", - " 12\tLOAD_FAST(arg=1, lineno=257)\n", - " 14\tLOAD_FAST(arg=0, lineno=257)\n", - " 16\tLOAD_ATTR(arg=1, lineno=257)\n", - " 18\tCOMPARE_OP(arg=0, lineno=257)\n", - " 20\tPOP_JUMP_IF_TRUE(arg=17, lineno=257)\n", - " 22\tLOAD_FAST(arg=1, lineno=257)\n", - " 24\tLOAD_FAST(arg=0, lineno=257)\n", - " 26\tLOAD_ATTR(arg=2, lineno=257)\n", - " 28\tCOMPARE_OP(arg=5, lineno=257)\n", - " 30\tPOP_JUMP_IF_FALSE(arg=19, lineno=257)\n", - "> 32\tLOAD_CONST(arg=2, lineno=258)\n", - " 34\tRETURN_VALUE(arg=None, lineno=258)\n", - "> 36\tLOAD_FAST(arg=0, lineno=259)\n", - " 38\tLOAD_ATTR(arg=0, lineno=259)\n", - " 40\tLOAD_CONST(arg=1, lineno=259)\n", - " 42\tCOMPARE_OP(arg=0, lineno=259)\n", - " 44\tPOP_JUMP_IF_FALSE(arg=36, lineno=259)\n", - " 46\tLOAD_FAST(arg=1, lineno=259)\n", - " 48\tLOAD_FAST(arg=0, lineno=259)\n", - " 50\tLOAD_ATTR(arg=2, lineno=259)\n", - " 52\tCOMPARE_OP(arg=1, lineno=259)\n", - " 54\tPOP_JUMP_IF_TRUE(arg=34, lineno=259)\n", - " 56\tLOAD_FAST(arg=1, lineno=259)\n", - " 58\tLOAD_FAST(arg=0, lineno=259)\n", - " 60\tLOAD_ATTR(arg=1, lineno=259)\n", - " 62\tCOMPARE_OP(arg=4, lineno=259)\n", - " 64\tPOP_JUMP_IF_FALSE(arg=36, lineno=259)\n", - "> 66\tLOAD_CONST(arg=2, lineno=260)\n", - " 68\tRETURN_VALUE(arg=None, lineno=260)\n", - "> 70\tLOAD_FAST(arg=1, lineno=262)\n", - " 72\tLOAD_FAST(arg=0, lineno=262)\n", - " 74\tLOAD_ATTR(arg=1, lineno=262)\n", - " 76\tBINARY_SUBTRACT(arg=None, lineno=262)\n", - " 78\tLOAD_FAST(arg=0, lineno=262)\n", - " 80\tLOAD_ATTR(arg=0, lineno=262)\n", - " 82\tBINARY_MODULO(arg=None, lineno=262)\n", - " 84\tLOAD_CONST(arg=1, lineno=262)\n", - " 86\tCOMPARE_OP(arg=2, lineno=262)\n", - " 88\tRETURN_VALUE(arg=None, lineno=262)\n", - "2024-10-16 10:11:15,643 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:15,643 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,643 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:15,644 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=255)\n", - "2024-10-16 10:11:15,644 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,645 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=257)\n", - "2024-10-16 10:11:15,645 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,645 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=0, lineno=257)\n", - "2024-10-16 10:11:15,646 - numba.core.byteflow - DEBUG - stack ['$robj2.0']\n", - "2024-10-16 10:11:15,646 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_CONST(arg=1, lineno=257)\n", - "2024-10-16 10:11:15,647 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-10-16 10:11:15,647 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=COMPARE_OP(arg=4, lineno=257)\n", - "2024-10-16 10:11:15,647 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$const6.2']\n", - "2024-10-16 10:11:15,648 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=POP_JUMP_IF_FALSE(arg=19, lineno=257)\n", - "2024-10-16 10:11:15,648 - numba.core.byteflow - DEBUG - stack ['$8compare_op.3']\n", - "2024-10-16 10:11:15,649 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=12, stack=(), blockstack=(), npush=0), Edge(pc=36, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:15,649 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=12 nstack_initial=0), State(pc_initial=36 nstack_initial=0)])\n", - "2024-10-16 10:11:15,649 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,650 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=12 nstack_initial=0)\n", - "2024-10-16 10:11:15,650 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=1, lineno=257)\n", - "2024-10-16 10:11:15,651 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,651 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=0, lineno=257)\n", - "2024-10-16 10:11:15,651 - numba.core.byteflow - DEBUG - stack ['$val12.0']\n", - "2024-10-16 10:11:15,652 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_ATTR(arg=1, lineno=257)\n", - "2024-10-16 10:11:15,652 - numba.core.byteflow - DEBUG - stack ['$val12.0', '$robj14.1']\n", - "2024-10-16 10:11:15,653 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=COMPARE_OP(arg=0, lineno=257)\n", - "2024-10-16 10:11:15,653 - numba.core.byteflow - DEBUG - stack ['$val12.0', '$16load_attr.2']\n", - "2024-10-16 10:11:15,653 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=POP_JUMP_IF_TRUE(arg=17, lineno=257)\n", - "2024-10-16 10:11:15,654 - numba.core.byteflow - DEBUG - stack ['$18compare_op.3']\n", - "2024-10-16 10:11:15,654 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=22, stack=(), blockstack=(), npush=0), Edge(pc=32, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:15,655 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=36 nstack_initial=0), State(pc_initial=22 nstack_initial=0), State(pc_initial=32 nstack_initial=0)])\n", - "2024-10-16 10:11:15,655 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,656 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=36 nstack_initial=0)\n", - "2024-10-16 10:11:15,656 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_FAST(arg=0, lineno=259)\n", - "2024-10-16 10:11:15,656 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,657 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_ATTR(arg=0, lineno=259)\n", - "2024-10-16 10:11:15,657 - numba.core.byteflow - DEBUG - stack ['$robj36.0']\n", - "2024-10-16 10:11:15,658 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_CONST(arg=1, lineno=259)\n", - "2024-10-16 10:11:15,658 - numba.core.byteflow - DEBUG - stack ['$38load_attr.1']\n", - "2024-10-16 10:11:15,658 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=COMPARE_OP(arg=0, lineno=259)\n", - "2024-10-16 10:11:15,659 - numba.core.byteflow - DEBUG - stack ['$38load_attr.1', '$const40.2']\n", - "2024-10-16 10:11:15,659 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_FALSE(arg=36, lineno=259)\n", - "2024-10-16 10:11:15,660 - numba.core.byteflow - DEBUG - stack ['$42compare_op.3']\n", - "2024-10-16 10:11:15,660 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=(), blockstack=(), npush=0), Edge(pc=70, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:15,660 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=22 nstack_initial=0), State(pc_initial=32 nstack_initial=0), State(pc_initial=46 nstack_initial=0), State(pc_initial=70 nstack_initial=0)])\n", - "2024-10-16 10:11:15,661 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,661 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=22 nstack_initial=0)\n", - "2024-10-16 10:11:15,662 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=1, lineno=257)\n", - "2024-10-16 10:11:15,662 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,662 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_FAST(arg=0, lineno=257)\n", - "2024-10-16 10:11:15,663 - numba.core.byteflow - DEBUG - stack ['$val22.0']\n", - "2024-10-16 10:11:15,663 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_ATTR(arg=2, lineno=257)\n", - "2024-10-16 10:11:15,664 - numba.core.byteflow - DEBUG - stack ['$val22.0', '$robj24.1']\n", - "2024-10-16 10:11:15,664 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=COMPARE_OP(arg=5, lineno=257)\n", - "2024-10-16 10:11:15,665 - numba.core.byteflow - DEBUG - stack ['$val22.0', '$26load_attr.2']\n", - "2024-10-16 10:11:15,665 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=POP_JUMP_IF_FALSE(arg=19, lineno=257)\n", - "2024-10-16 10:11:15,665 - numba.core.byteflow - DEBUG - stack ['$28compare_op.3']\n", - "2024-10-16 10:11:15,666 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=32, stack=(), blockstack=(), npush=0), Edge(pc=36, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:15,666 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=0), State(pc_initial=46 nstack_initial=0), State(pc_initial=70 nstack_initial=0), State(pc_initial=32 nstack_initial=0), State(pc_initial=36 nstack_initial=0)])\n", - "2024-10-16 10:11:15,667 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,667 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=32 nstack_initial=0)\n", - "2024-10-16 10:11:15,667 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_CONST(arg=2, lineno=258)\n", - "2024-10-16 10:11:15,668 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,668 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=RETURN_VALUE(arg=None, lineno=258)\n", - "2024-10-16 10:11:15,669 - numba.core.byteflow - DEBUG - stack ['$const32.0']\n", - "2024-10-16 10:11:15,669 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:15,669 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=0), State(pc_initial=70 nstack_initial=0), State(pc_initial=32 nstack_initial=0), State(pc_initial=36 nstack_initial=0)])\n", - "2024-10-16 10:11:15,670 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,670 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=0)\n", - "2024-10-16 10:11:15,671 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=1, lineno=259)\n", - "2024-10-16 10:11:15,671 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,671 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_FAST(arg=0, lineno=259)\n", - "2024-10-16 10:11:15,672 - numba.core.byteflow - DEBUG - stack ['$val46.0']\n", - "2024-10-16 10:11:15,672 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_ATTR(arg=2, lineno=259)\n", - "2024-10-16 10:11:15,672 - numba.core.byteflow - DEBUG - stack ['$val46.0', '$robj48.1']\n", - "2024-10-16 10:11:15,673 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=COMPARE_OP(arg=1, lineno=259)\n", - "2024-10-16 10:11:15,673 - numba.core.byteflow - DEBUG - stack ['$val46.0', '$50load_attr.2']\n", - "2024-10-16 10:11:15,674 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=POP_JUMP_IF_TRUE(arg=34, lineno=259)\n", - "2024-10-16 10:11:15,674 - numba.core.byteflow - DEBUG - stack ['$52compare_op.3']\n", - "2024-10-16 10:11:15,675 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=56, stack=(), blockstack=(), npush=0), Edge(pc=66, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:15,675 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=70 nstack_initial=0), State(pc_initial=32 nstack_initial=0), State(pc_initial=36 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=66 nstack_initial=0)])\n", - "2024-10-16 10:11:15,675 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,676 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=70 nstack_initial=0)\n", - "2024-10-16 10:11:15,676 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=LOAD_FAST(arg=1, lineno=262)\n", - "2024-10-16 10:11:15,677 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,677 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=LOAD_FAST(arg=0, lineno=262)\n", - "2024-10-16 10:11:15,677 - numba.core.byteflow - DEBUG - stack ['$val70.0']\n", - "2024-10-16 10:11:15,678 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_ATTR(arg=1, lineno=262)\n", - "2024-10-16 10:11:15,678 - numba.core.byteflow - DEBUG - stack ['$val70.0', '$robj72.1']\n", - "2024-10-16 10:11:15,679 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=BINARY_SUBTRACT(arg=None, lineno=262)\n", - "2024-10-16 10:11:15,679 - numba.core.byteflow - DEBUG - stack ['$val70.0', '$74load_attr.2']\n", - "2024-10-16 10:11:15,680 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=0, lineno=262)\n", - "2024-10-16 10:11:15,680 - numba.core.byteflow - DEBUG - stack ['$76binary_subtract.3']\n", - "2024-10-16 10:11:15,680 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_ATTR(arg=0, lineno=262)\n", - "2024-10-16 10:11:15,681 - numba.core.byteflow - DEBUG - stack ['$76binary_subtract.3', '$robj78.4']\n", - "2024-10-16 10:11:15,681 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=BINARY_MODULO(arg=None, lineno=262)\n", - "2024-10-16 10:11:15,682 - numba.core.byteflow - DEBUG - stack ['$76binary_subtract.3', '$80load_attr.5']\n", - "2024-10-16 10:11:15,682 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=LOAD_CONST(arg=1, lineno=262)\n", - "2024-10-16 10:11:15,682 - numba.core.byteflow - DEBUG - stack ['$82binary_modulo.6']\n", - "2024-10-16 10:11:15,683 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=COMPARE_OP(arg=2, lineno=262)\n", - "2024-10-16 10:11:15,683 - numba.core.byteflow - DEBUG - stack ['$82binary_modulo.6', '$const84.7']\n", - "2024-10-16 10:11:15,684 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=RETURN_VALUE(arg=None, lineno=262)\n", - "2024-10-16 10:11:15,684 - numba.core.byteflow - DEBUG - stack ['$86compare_op.8']\n", - "2024-10-16 10:11:15,685 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:15,685 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=0), State(pc_initial=36 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=66 nstack_initial=0)])\n", - "2024-10-16 10:11:15,685 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=36 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=66 nstack_initial=0)])\n", - "2024-10-16 10:11:15,686 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=0), State(pc_initial=66 nstack_initial=0)])\n", - "2024-10-16 10:11:15,686 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,687 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=0)\n", - "2024-10-16 10:11:15,687 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_FAST(arg=1, lineno=259)\n", - "2024-10-16 10:11:15,687 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,688 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_FAST(arg=0, lineno=259)\n", - "2024-10-16 10:11:15,688 - numba.core.byteflow - DEBUG - stack ['$val56.0']\n", - "2024-10-16 10:11:15,689 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_ATTR(arg=1, lineno=259)\n", - "2024-10-16 10:11:15,689 - numba.core.byteflow - DEBUG - stack ['$val56.0', '$robj58.1']\n", - "2024-10-16 10:11:15,689 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=COMPARE_OP(arg=4, lineno=259)\n", - "2024-10-16 10:11:15,690 - numba.core.byteflow - DEBUG - stack ['$val56.0', '$60load_attr.2']\n", - "2024-10-16 10:11:15,690 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=POP_JUMP_IF_FALSE(arg=36, lineno=259)\n", - "2024-10-16 10:11:15,691 - numba.core.byteflow - DEBUG - stack ['$62compare_op.3']\n", - "2024-10-16 10:11:15,691 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=66, stack=(), blockstack=(), npush=0), Edge(pc=70, stack=(), blockstack=(), npush=0)]\n", - "2024-10-16 10:11:15,692 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=66 nstack_initial=0), State(pc_initial=66 nstack_initial=0), State(pc_initial=70 nstack_initial=0)])\n", - "2024-10-16 10:11:15,692 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,692 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=66 nstack_initial=0)\n", - "2024-10-16 10:11:15,693 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_CONST(arg=2, lineno=260)\n", - "2024-10-16 10:11:15,693 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,694 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=RETURN_VALUE(arg=None, lineno=260)\n", - "2024-10-16 10:11:15,694 - numba.core.byteflow - DEBUG - stack ['$const66.0']\n", - "2024-10-16 10:11:15,694 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:15,695 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=66 nstack_initial=0), State(pc_initial=70 nstack_initial=0)])\n", - "2024-10-16 10:11:15,695 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=70 nstack_initial=0)])\n", - "2024-10-16 10:11:15,696 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:15,696 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=12 nstack_initial=0): set(),\n", - " State(pc_initial=22 nstack_initial=0): set(),\n", - " State(pc_initial=32 nstack_initial=0): set(),\n", - " State(pc_initial=36 nstack_initial=0): set(),\n", - " State(pc_initial=46 nstack_initial=0): set(),\n", - " State(pc_initial=56 nstack_initial=0): set(),\n", - " State(pc_initial=66 nstack_initial=0): set(),\n", - " State(pc_initial=70 nstack_initial=0): set()})\n", - "2024-10-16 10:11:15,697 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:15,697 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:15,698 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:15,698 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:15,698 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:15,699 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:15,712 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$robj2.0'}), (4, {'item': '$robj2.0', 'res': '$4load_attr.1'}), (6, {'res': '$const6.2'}), (8, {'lhs': '$4load_attr.1', 'rhs': '$const6.2', 'res': '$8compare_op.3'}), (10, {'pred': '$8compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={12: (), 36: ()})\n", - "2024-10-16 10:11:15,713 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=12 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((12, {'res': '$val12.0'}), (14, {'res': '$robj14.1'}), (16, {'item': '$robj14.1', 'res': '$16load_attr.2'}), (18, {'lhs': '$val12.0', 'rhs': '$16load_attr.2', 'res': '$18compare_op.3'}), (20, {'pred': '$18compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={22: (), 32: ()})\n", - "2024-10-16 10:11:15,713 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=22 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((22, {'res': '$val22.0'}), (24, {'res': '$robj24.1'}), (26, {'item': '$robj24.1', 'res': '$26load_attr.2'}), (28, {'lhs': '$val22.0', 'rhs': '$26load_attr.2', 'res': '$28compare_op.3'}), (30, {'pred': '$28compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={32: (), 36: ()})\n", - "2024-10-16 10:11:15,714 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=32 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((32, {'res': '$const32.0'}), (34, {'retval': '$const32.0', 'castval': '$34return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:15,714 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=36 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((36, {'res': '$robj36.0'}), (38, {'item': '$robj36.0', 'res': '$38load_attr.1'}), (40, {'res': '$const40.2'}), (42, {'lhs': '$38load_attr.1', 'rhs': '$const40.2', 'res': '$42compare_op.3'}), (44, {'pred': '$42compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: (), 70: ()})\n", - "2024-10-16 10:11:15,715 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((46, {'res': '$val46.0'}), (48, {'res': '$robj48.1'}), (50, {'item': '$robj48.1', 'res': '$50load_attr.2'}), (52, {'lhs': '$val46.0', 'rhs': '$50load_attr.2', 'res': '$52compare_op.3'}), (54, {'pred': '$52compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={56: (), 66: ()})\n", - "2024-10-16 10:11:15,716 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((56, {'res': '$val56.0'}), (58, {'res': '$robj58.1'}), (60, {'item': '$robj58.1', 'res': '$60load_attr.2'}), (62, {'lhs': '$val56.0', 'rhs': '$60load_attr.2', 'res': '$62compare_op.3'}), (64, {'pred': '$62compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={66: (), 70: ()})\n", - "2024-10-16 10:11:15,716 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=66 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((66, {'res': '$const66.0'}), (68, {'retval': '$const66.0', 'castval': '$68return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:15,717 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=70 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((70, {'res': '$val70.0'}), (72, {'res': '$robj72.1'}), (74, {'item': '$robj72.1', 'res': '$74load_attr.2'}), (76, {'lhs': '$val70.0', 'rhs': '$74load_attr.2', 'res': '$76binary_subtract.3'}), (78, {'res': '$robj78.4'}), (80, {'item': '$robj78.4', 'res': '$80load_attr.5'}), (82, {'lhs': '$76binary_subtract.3', 'rhs': '$80load_attr.5', 'res': '$82binary_modulo.6'}), (84, {'res': '$const84.7'}), (86, {'lhs': '$82binary_modulo.6', 'rhs': '$const84.7', 'res': '$86compare_op.8'}), (88, {'retval': '$86compare_op.8', 'castval': '$88return_value.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:15,719 - numba.core.interpreter - DEBUG - label 0:\n", - " robj = arg(0, name=robj) ['robj']\n", - " val = arg(1, name=val) ['val']\n", - " $4load_attr.1 = getattr(value=robj, attr=step) ['$4load_attr.1', 'robj']\n", - " $const6.2 = const(int, 0) ['$const6.2']\n", - " $8compare_op.3 = $4load_attr.1 > $const6.2 ['$4load_attr.1', '$8compare_op.3', '$const6.2']\n", - " bool10 = global(bool: ) ['bool10']\n", - " $10pred = call bool10($8compare_op.3, func=bool10, args=(Var($8compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None) ['$10pred', '$8compare_op.3', 'bool10']\n", - " branch $10pred, 12, 36 ['$10pred']\n", - "label 12:\n", - " $16load_attr.2 = getattr(value=robj, attr=start) ['$16load_attr.2', 'robj']\n", - " $18compare_op.3 = val < $16load_attr.2 ['$16load_attr.2', '$18compare_op.3', 'val']\n", - " bool20 = global(bool: ) ['bool20']\n", - " $20pred = call bool20($18compare_op.3, func=bool20, args=(Var($18compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None) ['$18compare_op.3', '$20pred', 'bool20']\n", - " branch $20pred, 32, 22 ['$20pred']\n", - "label 22:\n", - " $26load_attr.2 = getattr(value=robj, attr=stop) ['$26load_attr.2', 'robj']\n", - " $28compare_op.3 = val >= $26load_attr.2 ['$26load_attr.2', '$28compare_op.3', 'val']\n", - " bool30 = global(bool: ) ['bool30']\n", - " $30pred = call bool30($28compare_op.3, func=bool30, args=(Var($28compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None) ['$28compare_op.3', '$30pred', 'bool30']\n", - " branch $30pred, 32, 36 ['$30pred']\n", - "label 32:\n", - " $const32.0 = const(bool, False) ['$const32.0']\n", - " $34return_value.1 = cast(value=$const32.0) ['$34return_value.1', '$const32.0']\n", - " return $34return_value.1 ['$34return_value.1']\n", - "label 36:\n", - " $38load_attr.1 = getattr(value=robj, attr=step) ['$38load_attr.1', 'robj']\n", - " $const40.2 = const(int, 0) ['$const40.2']\n", - " $42compare_op.3 = $38load_attr.1 < $const40.2 ['$38load_attr.1', '$42compare_op.3', '$const40.2']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42compare_op.3, func=bool44, args=(Var($42compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None) ['$42compare_op.3', '$44pred', 'bool44']\n", - " branch $44pred, 46, 70 ['$44pred']\n", - "label 46:\n", - " $50load_attr.2 = getattr(value=robj, attr=stop) ['$50load_attr.2', 'robj']\n", - " $52compare_op.3 = val <= $50load_attr.2 ['$50load_attr.2', '$52compare_op.3', 'val']\n", - " bool54 = global(bool: ) ['bool54']\n", - " $54pred = call bool54($52compare_op.3, func=bool54, args=(Var($52compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None) ['$52compare_op.3', '$54pred', 'bool54']\n", - " branch $54pred, 66, 56 ['$54pred']\n", - "label 56:\n", - " $60load_attr.2 = getattr(value=robj, attr=start) ['$60load_attr.2', 'robj']\n", - " $62compare_op.3 = val > $60load_attr.2 ['$60load_attr.2', '$62compare_op.3', 'val']\n", - " bool64 = global(bool: ) ['bool64']\n", - " $64pred = call bool64($62compare_op.3, func=bool64, args=(Var($62compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None) ['$62compare_op.3', '$64pred', 'bool64']\n", - " branch $64pred, 66, 70 ['$64pred']\n", - "label 66:\n", - " $const66.0 = const(bool, False) ['$const66.0']\n", - " $68return_value.1 = cast(value=$const66.0) ['$68return_value.1', '$const66.0']\n", - " return $68return_value.1 ['$68return_value.1']\n", - "label 70:\n", - " $74load_attr.2 = getattr(value=robj, attr=start) ['$74load_attr.2', 'robj']\n", - " $76binary_subtract.3 = val - $74load_attr.2 ['$74load_attr.2', '$76binary_subtract.3', 'val']\n", - " $80load_attr.5 = getattr(value=robj, attr=step) ['$80load_attr.5', 'robj']\n", - " $82binary_modulo.6 = $76binary_subtract.3 % $80load_attr.5 ['$76binary_subtract.3', '$80load_attr.5', '$82binary_modulo.6']\n", - " $const84.7 = const(int, 0) ['$const84.7']\n", - " $86compare_op.8 = $82binary_modulo.6 == $const84.7 ['$82binary_modulo.6', '$86compare_op.8', '$const84.7']\n", - " $88return_value.9 = cast(value=$86compare_op.8) ['$86compare_op.8', '$88return_value.9']\n", - " return $88return_value.9 ['$88return_value.9']\n", - "\n", - "2024-10-16 10:11:15,731 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:15,731 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,732 - numba.core.ssa - DEBUG - on stmt: robj = arg(0, name=robj)\n", - "2024-10-16 10:11:15,732 - numba.core.ssa - DEBUG - on stmt: val = arg(1, name=val)\n", - "2024-10-16 10:11:15,733 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=robj, attr=step)\n", - "2024-10-16 10:11:15,733 - numba.core.ssa - DEBUG - on stmt: $const6.2 = const(int, 0)\n", - "2024-10-16 10:11:15,734 - numba.core.ssa - DEBUG - on stmt: $8compare_op.3 = $4load_attr.1 > $const6.2\n", - "2024-10-16 10:11:15,734 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-10-16 10:11:15,734 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8compare_op.3, func=bool10, args=(Var($8compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,735 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 36\n", - "2024-10-16 10:11:15,735 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 12\n", - "2024-10-16 10:11:15,736 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,736 - numba.core.ssa - DEBUG - on stmt: $16load_attr.2 = getattr(value=robj, attr=start)\n", - "2024-10-16 10:11:15,737 - numba.core.ssa - DEBUG - on stmt: $18compare_op.3 = val < $16load_attr.2\n", - "2024-10-16 10:11:15,737 - numba.core.ssa - DEBUG - on stmt: bool20 = global(bool: )\n", - "2024-10-16 10:11:15,738 - numba.core.ssa - DEBUG - on stmt: $20pred = call bool20($18compare_op.3, func=bool20, args=(Var($18compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,738 - numba.core.ssa - DEBUG - on stmt: branch $20pred, 32, 22\n", - "2024-10-16 10:11:15,738 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 22\n", - "2024-10-16 10:11:15,739 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,739 - numba.core.ssa - DEBUG - on stmt: $26load_attr.2 = getattr(value=robj, attr=stop)\n", - "2024-10-16 10:11:15,740 - numba.core.ssa - DEBUG - on stmt: $28compare_op.3 = val >= $26load_attr.2\n", - "2024-10-16 10:11:15,740 - numba.core.ssa - DEBUG - on stmt: bool30 = global(bool: )\n", - "2024-10-16 10:11:15,741 - numba.core.ssa - DEBUG - on stmt: $30pred = call bool30($28compare_op.3, func=bool30, args=(Var($28compare_op.3, rangeobj.py:257),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,741 - numba.core.ssa - DEBUG - on stmt: branch $30pred, 32, 36\n", - "2024-10-16 10:11:15,742 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 32\n", - "2024-10-16 10:11:15,742 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,742 - numba.core.ssa - DEBUG - on stmt: $const32.0 = const(bool, False)\n", - "2024-10-16 10:11:15,743 - numba.core.ssa - DEBUG - on stmt: $34return_value.1 = cast(value=$const32.0)\n", - "2024-10-16 10:11:15,743 - numba.core.ssa - DEBUG - on stmt: return $34return_value.1\n", - "2024-10-16 10:11:15,744 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 36\n", - "2024-10-16 10:11:15,744 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,744 - numba.core.ssa - DEBUG - on stmt: $38load_attr.1 = getattr(value=robj, attr=step)\n", - "2024-10-16 10:11:15,745 - numba.core.ssa - DEBUG - on stmt: $const40.2 = const(int, 0)\n", - "2024-10-16 10:11:15,745 - numba.core.ssa - DEBUG - on stmt: $42compare_op.3 = $38load_attr.1 < $const40.2\n", - "2024-10-16 10:11:15,746 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-10-16 10:11:15,746 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42compare_op.3, func=bool44, args=(Var($42compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,747 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 46, 70\n", - "2024-10-16 10:11:15,747 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-10-16 10:11:15,748 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,748 - numba.core.ssa - DEBUG - on stmt: $50load_attr.2 = getattr(value=robj, attr=stop)\n", - "2024-10-16 10:11:15,748 - numba.core.ssa - DEBUG - on stmt: $52compare_op.3 = val <= $50load_attr.2\n", - "2024-10-16 10:11:15,749 - numba.core.ssa - DEBUG - on stmt: bool54 = global(bool: )\n", - "2024-10-16 10:11:15,749 - numba.core.ssa - DEBUG - on stmt: $54pred = call bool54($52compare_op.3, func=bool54, args=(Var($52compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,750 - numba.core.ssa - DEBUG - on stmt: branch $54pred, 66, 56\n", - "2024-10-16 10:11:15,750 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-10-16 10:11:15,751 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,751 - numba.core.ssa - DEBUG - on stmt: $60load_attr.2 = getattr(value=robj, attr=start)\n", - "2024-10-16 10:11:15,752 - numba.core.ssa - DEBUG - on stmt: $62compare_op.3 = val > $60load_attr.2\n", - "2024-10-16 10:11:15,752 - numba.core.ssa - DEBUG - on stmt: bool64 = global(bool: )\n", - "2024-10-16 10:11:15,753 - numba.core.ssa - DEBUG - on stmt: $64pred = call bool64($62compare_op.3, func=bool64, args=(Var($62compare_op.3, rangeobj.py:259),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,753 - numba.core.ssa - DEBUG - on stmt: branch $64pred, 66, 70\n", - "2024-10-16 10:11:15,754 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 66\n", - "2024-10-16 10:11:15,754 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,754 - numba.core.ssa - DEBUG - on stmt: $const66.0 = const(bool, False)\n", - "2024-10-16 10:11:15,755 - numba.core.ssa - DEBUG - on stmt: $68return_value.1 = cast(value=$const66.0)\n", - "2024-10-16 10:11:15,755 - numba.core.ssa - DEBUG - on stmt: return $68return_value.1\n", - "2024-10-16 10:11:15,756 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 70\n", - "2024-10-16 10:11:15,756 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,756 - numba.core.ssa - DEBUG - on stmt: $74load_attr.2 = getattr(value=robj, attr=start)\n", - "2024-10-16 10:11:15,757 - numba.core.ssa - DEBUG - on stmt: $76binary_subtract.3 = val - $74load_attr.2\n", - "2024-10-16 10:11:15,757 - numba.core.ssa - DEBUG - on stmt: $80load_attr.5 = getattr(value=robj, attr=step)\n", - "2024-10-16 10:11:15,758 - numba.core.ssa - DEBUG - on stmt: $82binary_modulo.6 = $76binary_subtract.3 % $80load_attr.5\n", - "2024-10-16 10:11:15,758 - numba.core.ssa - DEBUG - on stmt: $const84.7 = const(int, 0)\n", - "2024-10-16 10:11:15,759 - numba.core.ssa - DEBUG - on stmt: $86compare_op.8 = $82binary_modulo.6 == $const84.7\n", - "2024-10-16 10:11:15,759 - numba.core.ssa - DEBUG - on stmt: $88return_value.9 = cast(value=$86compare_op.8)\n", - "2024-10-16 10:11:15,760 - numba.core.ssa - DEBUG - on stmt: return $88return_value.9\n", - "2024-10-16 10:11:15,761 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10pred': [],\n", - " '$16load_attr.2': [],\n", - " '$18compare_op.3': [],\n", - " '$20pred': [],\n", - " '$26load_attr.2': [],\n", - " '$28compare_op.3': [],\n", - " '$30pred': [],\n", - " '$34return_value.1': [],\n", - " '$38load_attr.1': [],\n", - " '$42compare_op.3': [],\n", - " '$44pred': [],\n", - " '$4load_attr.1': [],\n", - " '$50load_attr.2': [],\n", - " '$52compare_op.3': [],\n", - " '$54pred': [],\n", - " '$60load_attr.2': [],\n", - " '$62compare_op.3': [],\n", - " '$64pred': [],\n", - " '$68return_value.1': [],\n", - " '$74load_attr.2': [],\n", - " '$76binary_subtract.3': [],\n", - " '$80load_attr.5': [],\n", - " '$82binary_modulo.6': [],\n", - " '$86compare_op.8': [],\n", - " '$88return_value.9': [],\n", - " '$8compare_op.3': [],\n", - " '$const32.0': [],\n", - " '$const40.2': [],\n", - " '$const6.2': [],\n", - " '$const66.0': [],\n", - " '$const84.7': [],\n", - " 'bool10': [],\n", - " 'bool20': [],\n", - " 'bool30': [],\n", - " 'bool44': [],\n", - " 'bool54': [],\n", - " 'bool64': [],\n", - " 'robj': [],\n", - " 'val': []})\n", - "2024-10-16 10:11:15,761 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:15,873 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=5394)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=5395)\n", - " 4\tLOAD_FAST(arg=0, lineno=5395)\n", - " 6\tLOAD_FAST(arg=1, lineno=5395)\n", - " 8\tCALL_FUNCTION(arg=2, lineno=5395)\n", - " 10\tRETURN_VALUE(arg=None, lineno=5395)\n", - "2024-10-16 10:11:15,873 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-10-16 10:11:15,874 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-10-16 10:11:15,874 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-10-16 10:11:15,874 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=5394)\n", - "2024-10-16 10:11:15,875 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,875 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=5395)\n", - "2024-10-16 10:11:15,876 - numba.core.byteflow - DEBUG - stack []\n", - "2024-10-16 10:11:15,876 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=5395)\n", - "2024-10-16 10:11:15,876 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-10-16 10:11:15,877 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=5395)\n", - "2024-10-16 10:11:15,877 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$object4.1']\n", - "2024-10-16 10:11:15,878 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_FUNCTION(arg=2, lineno=5395)\n", - "2024-10-16 10:11:15,878 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$object4.1', '$dtype6.2']\n", - "2024-10-16 10:11:15,879 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=RETURN_VALUE(arg=None, lineno=5395)\n", - "2024-10-16 10:11:15,879 - numba.core.byteflow - DEBUG - stack ['$8call_function.3']\n", - "2024-10-16 10:11:15,879 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-10-16 10:11:15,880 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-10-16 10:11:15,880 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-10-16 10:11:15,881 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-10-16 10:11:15,881 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-10-16 10:11:15,881 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-10-16 10:11:15,882 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-10-16 10:11:15,882 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-10-16 10:11:15,883 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-10-16 10:11:15,883 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$object4.1'}), (6, {'res': '$dtype6.2'}), (8, {'func': '$2load_global.0', 'args': ['$object4.1', '$dtype6.2'], 'res': '$8call_function.3'}), (10, {'retval': '$8call_function.3', 'castval': '$10return_value.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-10-16 10:11:15,884 - numba.core.interpreter - DEBUG - label 0:\n", - " object = arg(0, name=object) ['object']\n", - " dtype = arg(1, name=dtype) ['dtype']\n", - " $2load_global.0 = global(np_array: ) ['$2load_global.0']\n", - " $8call_function.3 = call $2load_global.0(object, dtype, func=$2load_global.0, args=[Var(object, arrayobj.py:5394), Var(dtype, arrayobj.py:5394)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', '$8call_function.3', 'dtype', 'object']\n", - " $10return_value.4 = cast(value=$8call_function.3) ['$10return_value.4', '$8call_function.3']\n", - " return $10return_value.4 ['$10return_value.4']\n", - "\n", - "2024-10-16 10:11:15,889 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-10-16 10:11:15,890 - numba.core.ssa - DEBUG - Running \n", - "2024-10-16 10:11:15,890 - numba.core.ssa - DEBUG - on stmt: object = arg(0, name=object)\n", - "2024-10-16 10:11:15,891 - numba.core.ssa - DEBUG - on stmt: dtype = arg(1, name=dtype)\n", - "2024-10-16 10:11:15,892 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np_array: )\n", - "2024-10-16 10:11:15,892 - numba.core.ssa - DEBUG - on stmt: $8call_function.3 = call $2load_global.0(object, dtype, func=$2load_global.0, args=[Var(object, arrayobj.py:5394), Var(dtype, arrayobj.py:5394)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-10-16 10:11:15,893 - numba.core.ssa - DEBUG - on stmt: $10return_value.4 = cast(value=$8call_function.3)\n", - "2024-10-16 10:11:15,894 - numba.core.ssa - DEBUG - on stmt: return $10return_value.4\n", - "2024-10-16 10:11:15,895 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10return_value.4': [],\n", - " '$2load_global.0': [],\n", - " '$8call_function.3': [],\n", - " 'dtype': [],\n", - " 'object': []})\n", - "2024-10-16 10:11:15,895 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-10-16 10:11:16,991 - root - INFO - Successfully imported data from /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d\n", - "2024-10-16 10:11:16,992 - utils.ims_utils - INFO - No output directory provided, using the directory of the .d file\n", - "2024-10-16 10:11:16,993 - utils.ims_utils - INFO - HDF file /cmnfs/proj/ORIGINS/data/HeLa_sample_amount_and_LC_columns/raw_data/Hela_30min_5ug_R2_RA1_1_5163.d/Hela_30min_5ug_R2_RA1_1_5163.hdf already exists\n" - ] - } - ], - "source": [ - "from utils.ims_utils import load_dotd_data\n", - "\n", - "data, hdf_file_name = load_dotd_data(\n", - " cfg.DATA_PATH, swaps_result_dir=cfg.EXPORT_DATA_HDF5_DIR\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "4.901027627804154" - ] - }, - "execution_count": 61, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.log10(79621)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 11:25:02,500 - matplotlib.colorbar - DEBUG - locator: \n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from utils.plot import plot_im_mz\n", - "\n", - "mz_rank = 30783\n", - "ms1_range = maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank,\n", - " [\n", - " \"MS1_frame_idx_left_exp\",\n", - " \"MS1_frame_idx_right_exp\",\n", - " ],\n", - "].values\n", - "precursor = '_'.join(map(str, maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank,\n", - " [\n", - " \"Modified sequence\",\n", - " \"Charge\",\n", - " ],\n", - " ]\n", - " .values[0]))\n", - "IsoMZ = maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"IsoMZ\"\n", - "].values[0]\n", - "\n", - "df = data[\n", - " {\n", - " # \"frame_indices\": slice(int(ms1_range[0][0]) - 1, int(ms1_range[0][1]) + 1),\n", - " \"frame_indices\": slice(\n", - " ms1scans.loc[ms1_range[0][0], \"Id\"] - 1,\n", - " ms1scans.loc[ms1_range[0][1], \"Id\"] + 1,\n", - " ),\n", - " \"precursor_indices\": [0],\n", - " # # \"scan_indices\": slice(300, 800, 10),\n", - " \"mz_values\": slice(IsoMZ.min() - 0.1, IsoMZ.max() + 0.1),\n", - " # \"mobility_values\": [0.9, 1.0],\n", - " # # \"intensity_values\": 50,\n", - " }\n", - "]\n", - "im = maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"mobility_values_center_exp\"\n", - "].values\n", - "im_length = maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"1/K0 length\"\n", - "].values[0]\n", - "plot_im_mz(\n", - " sliced_frame=df,\n", - " mark_mz=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"IsoMZ\"\n", - " ].values[0],\n", - " distr_mz=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"IsoAbundance\"\n", - " ].values[0],\n", - " mark_im=[im - 0.5*im_length, im, im + 0.5*im_length],\n", - " title = precursor,\n", - " save_dir = os.path.join(eval_dir, \"outlier_raw_data\"),\n", - " fig_spec_name=\"overestimated\"+precursor+\"_\"+str(mz_rank),\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 10:38:43,580 - matplotlib.colorbar - DEBUG - locator: \n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from utils.plot import plot_im_mz\n", - "\n", - "mz_rank = 50905\n", - "ms1_range = maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank,\n", - " [\n", - " \"MS1_frame_idx_left_exp\",\n", - " \"MS1_frame_idx_right_exp\",\n", - " ],\n", - "].values\n", - "precursor = '_'.join(map(str, maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank,\n", - " [\n", - " \"Modified sequence\",\n", - " \"Charge\",\n", - " ],\n", - " ]\n", - " .values[0]))\n", - "IsoMZ = maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"IsoMZ\"\n", - "].values[0]\n", - "\n", - "df = data[\n", - " {\n", - " # \"frame_indices\": slice(int(ms1_range[0][0]) - 1, int(ms1_range[0][1]) + 1),\n", - " \"frame_indices\": slice(\n", - " ms1scans.loc[ms1_range[0][0], \"Id\"] - 1,\n", - " ms1scans.loc[ms1_range[0][1], \"Id\"] + 1,\n", - " ),\n", - " \"precursor_indices\": [0],\n", - " # # \"scan_indices\": slice(300, 800, 10),\n", - " \"mz_values\": slice(IsoMZ.min() - 0.1, IsoMZ.max() + 0.1),\n", - " # \"mobility_values\": [0.9, 1.0],\n", - " # # \"intensity_values\": 50,\n", - " }\n", - "]\n", - "im = maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"mobility_values_center_exp\"\n", - "].values\n", - "im_length = maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"1/K0 length\"\n", - "].values[0]\n", - "plot_im_mz(\n", - " sliced_frame=df,\n", - " mark_mz=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"IsoMZ\"\n", - " ].values[0],\n", - " distr_mz=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"] == mz_rank, \"IsoAbundance\"\n", - " ].values[0],\n", - " mark_im=[im - 0.5*im_length, im, im + 0.5*im_length],\n", - " title = precursor,\n", - " save_dir = os.path.join(eval_dir, \"outlier_raw_data\"),\n", - " fig_spec_name=\"underestimated\"+precursor+\"_\"+str(mz_rank),\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Exam individual peptide image" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Find candidates to plot" - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "metadata": {}, - "outputs": [], - "source": [ - "a = maxquant_result_ref[\"mz_bin\"].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 112, - "metadata": {}, - "outputs": [ - { - "data": { - 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mz_binMS1_frame_idx_left_expMS1_frame_idx_right_expmz_rank
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" - ], - "text/plain": [ - " mz_bin MS1_frame_idx_left_exp MS1_frame_idx_right_exp mz_rank\n", - "7594 760.38 852.0 868.0 23915\n", - "15426 760.38 1099.0 1108.0 23922\n", - "16989 760.38 1143.0 1153.0 23923\n", - "18129 760.38 1174.0 1184.0 23916\n", - "19574 760.38 1208.0 1222.0 23924\n", - "25128 760.38 1361.0 1370.0 23918\n", - "25651 760.38 1376.0 1383.0 23913\n", - "29441 760.38 1465.0 1480.0 23914\n", - "34165 760.38 1598.0 1611.0 23919\n", - "34446 760.38 1605.0 1619.0 23920\n", - "35154 760.38 1627.0 1639.0 23917\n", - "47119 760.38 2077.0 2083.0 23921" - ] - }, - "execution_count": 112, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "maxquant_result_ref.loc[\n", - " (maxquant_result_ref[\"mz_bin\"] == 760.38),\n", - " [\"mz_bin\", \"MS1_frame_idx_left_exp\", \"MS1_frame_idx_right_exp\", \"mz_rank\"],\n", - "]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Deconvolution with heatmap" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- frame number 1055, candidate mz rank 8553, 8555\n", - "- frame number 828, candidate mz rank 19100, 19103\n", - "- fraome number 1608, candidate mz rank 23919, 23920" - ] - }, - { - "cell_type": "code", - "execution_count": 135, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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1/K0 lengthmobility_values_center_expmz_rank
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" - ], - "text/plain": [ - " 1/K0 length mobility_values_center_exp mz_rank\n", - "13669 0.063347 0.898293 8555\n", - "13806 0.115991 0.941988 8553" - ] - }, - "execution_count": 135, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"].isin([8553, 8555]),\n", - " [\"1/K0 length\", \"mobility_values_center_exp\", \"mz_rank\"],\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 132, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 14:30:28,043 - optimization.inference - DEBUG - Start data preparation.\n", - "2024-10-16 14:30:28,160 - optimization.inference - DEBUG - Frame data shape: 437098\n", - "2024-10-16 14:30:28,164 - optimization.inference - INFO - Number of candidates by RT in frame 1609: 496\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/optimization/inference.py:790: SettingWithCopyWarning:\n", - "\n", - "\n", - "A value is trying to be set on a copy of a slice from a DataFrame\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - "\n", - "2024-10-16 14:30:28,341 - optimization.inference - DEBUG - Number of mz values in candidate, frame and joint:2656, 86516, 86536\n", - "2024-10-16 14:30:28,384 - optimization.inference - DEBUG - min and max mz index: 1821 72462\n", - "2024-10-16 14:30:28,386 - optimization.inference - DEBUG - Number of mz values in filtered candidate index: 2656\n", - "2024-10-16 14:30:28,570 - optimization.inference - DEBUG - Start optimization with sparse encoding.\n", - "2024-10-16 14:30:28,590 - optimization.inference - DEBUG - Start peak selection.\n", - "2024-10-16 14:30:28,591 - optimization.inference - DEBUG - Scan-wise opimtization completed.\n" - ] - } - ], - "source": [ - "from optimization.inference import process_one_frame_ims\n", - "import matplotlib.pyplot as plt\n", - "\n", - "frame_idx = 1609\n", - "(\n", - " peaks_df,\n", - " im_pept_act_coo,\n", - " frame_array,\n", - " candidate_array,\n", - " im_pept_act,\n", - " candidate_precursor_by_rt,\n", - " all_frame_pept_idx,\n", - ") = process_one_frame_ims(\n", - " data=data,\n", - " ms1scans=ms1scans,\n", - " ms1_frame_idx=frame_idx,\n", - " maxquant_result_ref_with_im_index_sortmz=maxquant_result_ref,\n", - " mobility_values=mobility_values_df,\n", - " debug=True,\n", - " mz_bin_digits=2,\n", - " extract_im_peak=False,\n", - " return_im_pept_act=True,\n", - ")\n", - "a = np.where(all_frame_pept_idx == 23919)\n", - "b = np.where(all_frame_pept_idx == 23920)\n", - "# c = np.where(all_frame_pept_idx == 31371)\n", - "candidate_act = im_pept_act[:, [a, b]].reshape(-1, 2)\n", - "candidate_mz_pattern = candidate_array[[a, b], :].reshape(2, candidate_array.shape[1])\n", - "non_zero_columns = np.where(np.any(candidate_mz_pattern != 0, axis=0))[0]\n", - "\n", - "candidate_mz_pattern = candidate_mz_pattern[:, non_zero_columns]\n", - "frame_candidate_mz_range = frame_array[:, non_zero_columns].reshape(\n", - " -1, len(non_zero_columns)\n", - ")\n", - "# frame_array = frame_array[:, non_zero_columns]\n", - "non_zero_rows = np.where(np.any(frame_candidate_mz_range != 0, axis=1))[0]\n", - "frame_candidate_mz_range = frame_candidate_mz_range[non_zero_rows, :]\n", - "candidate_act = candidate_act[non_zero_rows, :]" - ] - }, - { - "cell_type": "code", - "execution_count": 134, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'm/z Bin Index')" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'Ion Mobility Index')" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 14:30:38,319 - matplotlib.colorbar - DEBUG - locator: \n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'm/z Bin Index')" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'Candidate Precursors')" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "([,\n", - " ],\n", - " [Text(0, 0, 'A'), Text(1, 0, 'B')])" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 14:30:39,008 - matplotlib.colorbar - DEBUG - locator: \n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'Candidate Precursors')" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "([,\n", - " ],\n", - " [Text(0, 0, 'A'), Text(0, 1, 'B')])" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'Ion Mobility Index')" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 14:30:39,646 - matplotlib.colorbar - DEBUG - locator: \n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 134, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from utils.plot import save_plot\n", - "\n", - "plt.rcParams.update({\"font.size\": 12})\n", - "plt.imshow(frame_candidate_mz_range.T, aspect=\"auto\", cmap=\"hot\", interpolation=\"none\")\n", - "plt.ylabel(\"m/z Bin Index\")\n", - "plt.xlabel(\"Ion Mobility Index\")\n", - "plt.colorbar()\n", - "save_plot(\n", - " os.path.join(eval_dir, \"optimzation_ilustration\", str(frame_idx)),\n", - " \"heat_map\",\n", - " \"ms1_frame\",\n", - ")\n", - "plt.imshow(candidate_mz_pattern.T, aspect=\"auto\", cmap=\"hot\", interpolation=\"none\")\n", - "plt.ylabel(\"m/z Bin Index\")\n", - "plt.xlabel(\"Candidate Precursors\")\n", - "plt.xticks(ticks=[0, 1], labels=[\"A\", \"B\"])\n", - "plt.colorbar()\n", - "save_plot(\n", - " os.path.join(eval_dir, \"optimzation_ilustration\", str(frame_idx)),\n", - " \"heat_map\",\n", - " \"dictioanry_mz_pattern\",\n", - ")\n", - "plt.imshow(candidate_act.T, aspect=\"auto\", cmap=\"hot\", interpolation=\"none\")\n", - "plt.ylabel(\"Candidate Precursors\")\n", - "plt.yticks(ticks=[0, 1], labels=[\"A\", \"B\"])\n", - "plt.xlabel(\"Ion Mobility Index\")\n", - "plt.colorbar()\n", - "save_plot(\n", - " os.path.join(eval_dir, \"optimzation_ilustration\", str(frame_idx)),\n", - " \"heat_map\",\n", - " \"candidate_act\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 75, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 75, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 75, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 75, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 75, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 75, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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HiRMnVFlZGbZHPb755ht1dHQoIyOjb/914sQJvfjiixo1apTd8UIq7MtHbGyspkyZoqqqqr55gUBAVVVVysnJsTFZ6FiWpSVLlqiiokL79u1TZmam3ZFCZsaMGfrxxx/V2NjYN2VlZWnBggVqbGxUdHS03RGDLjc395JLp48ePaqRI0falCi0zp49q6io/ruq6OhoBQIBmxKZk5mZqbS0tH77L5/Pp0OHDoXt/uti8Th27Ji+/vprJScn2x0pZBYuXKgffvih3/7L4/FoxYoV+uqrr+yOF1IR8bFLUVGRCgoKlJWVpezsbG3evFl+v1+LFi2yO1pIeL1elZeXa/fu3XK5XH2fDbvdbsXHx9ucLrhcLtcl57IkJCQoOTk5bM9xWb58uaZPn67169dr/vz5qqur0/bt27V9+3a7o4XE7NmztW7dOmVkZGj8+PH67rvvtGnTJi1evNjuaEFx5swZ/fLLL323jx8/rsbGRiUlJSkjI0OFhYV67bXXNHr0aGVmZqq4uFgej0dz5syxL/RNuNJ4hw8frkcffVQNDQ3au3event7+/ZfSUlJio2NtSv2Dbva9v1ruRoyZIjS0tJ01113mY5qlt2X25iydetWKyMjw4qNjbWys7Ot2tpauyOFjKTLTjt27LA7mhHhfqmtZVnWnj17rAkTJlhOp9MaM2aMtX37drsjhYzP57OWLVtmZWRkWHFxcdYdd9xhvfzyy1Z3d7fd0YJi//79l/33WlBQYFnWhctti4uLrdTUVMvpdFozZsywmpub7Q19E6403uPHj//t/mv//v12R78hV9u+fxUpl9o6LGtgfU1gIBBQa2urXC5XxJ2AAwDAYGVZlrq6uuTxeC75qPSvBtzHLq2trUpPT7c7BgAAuAEtLS1XvchhwJUPl8sl6UL4cD3DGQCAcOPz+ZSent73Pn4lA658XPyoJTExkfIBAMAgcy2nTIT9pbYAAGBgoXwAAACjKB8ILr9fcjguTH6/3WkAAAMQ5QMAABhF+QAAAEZFTvng4wAAAAaEyCkfAABgQKB8AAAAoygfAADAKMoHAAAwivIBAACMonwAAACjKB8AAMAoygcAADCK8gEAAIyifAAAAKMoHwAAwCjKBwAAMIryAQAAjKJ8AAAAoygfAADAKMoHAAAwivIBAACMonwAAACjKB8AAMAoygcAADCK8gEAAIyifAAAAKMoHwAAwCjKBwAAMIryAQAAjKJ8AAAAoygfAADAKMoHAAAwivIBAACMonwAAACjKB8AAMAoygcAADDquspHSUmJpk6dKpfLpZSUFM2ZM0fNzc39ljl37py8Xq+Sk5N16623at68eWpvbw9qaAAAMHhdV/morq6W1+tVbW2tKisr1dPTo5kzZ8rv9/cts3z5cu3Zs0effPKJqqur1draqrlz5wY9OAAAGJwclmVZN/rgP/74QykpKaqurtYDDzygzs5O/eMf/1B5ebkeffRRSdKRI0c0duxY1dTU6L777rvqOn0+n9xutzo7O5WYmHij0S7l90u33nrhz2fOSAkJwVs3/oXXGQAi0vW8f9/UOR+dnZ2SpKSkJElSfX29enp6lJeX17fMmDFjlJGRoZqamsuuo7u7Wz6fr98EAADC1w2Xj0AgoMLCQuXm5mrChAmSpLa2NsXGxmro0KH9lk1NTVVbW9tl11NSUiK32903paen32gkAAAwCNxw+fB6vWpqatLOnTtvKsDq1avV2dnZN7W0tNzU+gAAwMAWcyMPWrJkifbu3asDBw5oxIgRffPT0tJ0/vx5nT59ut/Rj/b2dqWlpV12XU6nU06n80ZiADCNc3oABMF1HfmwLEtLlixRRUWF9u3bp8zMzH73T5kyRUOGDFFVVVXfvObmZp08eVI5OTnBSQwAAAa16zry4fV6VV5ert27d8vlcvWdx+F2uxUfHy+3261nn31WRUVFSkpKUmJiol544QXl5ORc05UuAAAg/F1X+SgrK5MkPfTQQ/3m79ixQ88884wk6a233lJUVJTmzZun7u5u5efn69133w1KWAAAMPjd1Pd8hALf8zHI8TqHN7YvgL9h7Hs+AAAArhflAwAAGEX5AAAARlE+AACAUZQPAABgFOUDAAAYRfkAAABGUT4AAIBRlA8AAGAU5QMAABhF+QAAAEZRPgAAgFGUDwAAYBTlAwAAGEX5AAAARlE+AACAUZQPAABgFOUDAAAYRfkAAABGUT4AAIBRlA8AAGAU5QMAABhF+QAAAEZRPgAAgFGUDwAAYBTlAwAAGEX5AAAARlE+AACAUZQPAABgFOUDAAAYRfkAAABGUT4AAIBRlA8AAGAU5QMAABhF+QAAAEZRPgAAgFGUDwAAYBTlAwAAGEX5AAAARlE+AAD28/slh+PC5PfbnQYhRvkAAABGUT4AAIBRlA8AwL/w8QcMoHwAAACjKB8AAMAoygcAADCK8gEAAIyifAAAAKNCVj5KS0s1atQoxcXFadq0aaqrqwvVUwEAgEEkJOVj165dKioq0tq1a9XQ0KBJkyYpPz9fHR0doXg6AABwLQbIpdQhKR+bNm3Sc889p0WLFmncuHHatm2bbrnlFn3wwQeheDoAADCIBL18nD9/XvX19crLy/vXk0RFKS8vTzU1NZcs393dLZ/P128CAADhK+jl49SpU+rt7VVqamq/+ampqWpra7tk+ZKSErnd7r4pPT092JEuSEiQLOvClJAQmucAr3O4Y/uGP7u2MX+3zBggr7PtV7usXr1anZ2dfVNLS4vdkQAAQAjFBHuFw4YNU3R0tNrb2/vNb29vV1pa2iXLO51OOZ3OYMcAAAADVNCPfMTGxmrKlCmqqqrqmxcIBFRVVaWcnJxgPx0AABhkgn7kQ5KKiopUUFCgrKwsZWdna/PmzfL7/Vq0aNFVH2tZliRx4ikAAIPIxffti+/jVxKS8vH444/rjz/+0Jo1a9TW1qZ77rlHX3755SUnoV5OV1eXJIXuxFMAABAyXV1dcrvdV1zGYV1LRTEoEAiotbVVLpdLDocjqOv2+XxKT09XS0uLEhMTg7rugYjxhjfGG94ibbxS5I053MZrWZa6urrk8XgUFXXlszpCcuTjZkRFRWnEiBEhfY7ExMSw2NDXivGGN8Yb3iJtvFLkjTmcxnu1Ix4X2X6pLQAAiCyUDwAAYFRElQ+n06m1a9dGzPeKMN7wxnjDW6SNV4q8MUfaeP/dgDvhFAAAhLeIOvIBAADsR/kAAABGUT4AAIBRlA8AAGBUxJSP0tJSjRo1SnFxcZo2bZrq6ursjhQyJSUlmjp1qlwul1JSUjRnzhw1NzfbHcuI119/XQ6HQ4WFhXZHCanff/9dTz31lJKTkxUfH6+JEyfq22+/tTtWSPT29qq4uFiZmZmKj4/XnXfeqVdfffWafj9iMDhw4IBmz54tj8cjh8Ohzz77rN/9lmVpzZo1Gj58uOLj45WXl6djx47ZEzYIrjTenp4erVy5UhMnTlRCQoI8Ho+efvpptba22hf4Jl1t+/67559/Xg6HQ5s3bzaWzy4RUT527dqloqIirV27Vg0NDZo0aZLy8/PV0dFhd7SQqK6ultfrVW1trSorK9XT06OZM2fK7/fbHS2kDh8+rPfee09333233VFC6s8//1Rubq6GDBmiL774Qj/99JPefPNN3XbbbXZHC4kNGzaorKxM77zzjn7++Wdt2LBBGzdu1NatW+2OFhR+v1+TJk1SaWnpZe/fuHGjtmzZom3btunQoUNKSEhQfn6+zp07ZzhpcFxpvGfPnlVDQ4OKi4vV0NCgTz/9VM3NzXrkkUdsSBocV9u+F1VUVKi2tlYej8dQMptZESA7O9vyer19t3t7ey2Px2OVlJTYmMqcjo4OS5JVXV1td5SQ6erqskaPHm1VVlZaDz74oLVs2TK7I4XMypUrrfvvv9/uGMbMmjXLWrx4cb95c+fOtRYsWGBTotCRZFVUVPTdDgQCVlpamvXGG2/0zTt9+rTldDqtjz76yIaEwfXX8V5OXV2dJck6ceKEmVAh9Hfj/e2336zbb7/dampqskaOHGm99dZbxrOZFvZHPs6fP6/6+nrl5eX1zYuKilJeXp5qampsTGZOZ2enJCkpKcnmJKHj9Xo1a9asfts5XH3++efKysrSY489ppSUFE2ePFnvv/++3bFCZvr06aqqqtLRo0clSd9//70OHjyohx9+2OZkoXf8+HG1tbX1+3vtdrs1bdq0iNp/ORwODR061O4oIREIBLRw4UKtWLFC48ePtzuOMQPuh+WC7dSpU+rt7VVqamq/+ampqTpy5IhNqcwJBAIqLCxUbm6uJkyYYHeckNi5c6caGhp0+PBhu6MY8euvv6qsrExFRUV66aWXdPjwYS1dulSxsbEqKCiwO17QrVq1Sj6fT2PGjFF0dLR6e3u1bt06LViwwO5oIdfW1iZJl91/XbwvnJ07d04rV67Uk08+GTY/vPZXGzZsUExMjJYuXWp3FKPCvnxEOq/Xq6amJh08eNDuKCHR0tKiZcuWqbKyUnFxcXbHMSIQCCgrK0vr16+XJE2ePFlNTU3atm1bWJaPjz/+WB9++KHKy8s1fvx4NTY2qrCwUB6PJyzHiwt6eno0f/58WZalsrIyu+OERH19vd5++201NDTI4XDYHceosP/YZdiwYYqOjlZ7e3u/+e3t7UpLS7MplRlLlizR3r17tX//fo0YMcLuOCFRX1+vjo4O3XvvvYqJiVFMTIyqq6u1ZcsWxcTEqLe31+6IQTd8+HCNGzeu37yxY8fq5MmTNiUKrRUrVmjVqlV64oknNHHiRC1cuFDLly9XSUmJ3dFC7uI+KtL2XxeLx4kTJ1RZWRm2Rz2++eYbdXR0KCMjo2//deLECb344osaNWqU3fFCKuzLR2xsrKZMmaKqqqq+eYFAQFVVVcrJybExWehYlqUlS5aooqJC+/btU2Zmpt2RQmbGjBn68ccf1djY2DdlZWVpwYIFamxsVHR0tN0Rgy43N/eSS6ePHj2qkSNH2pQotM6ePauoqP67qujoaAUCAZsSmZOZmam0tLR++y+fz6dDhw6F7f7rYvE4duyYvv76ayUnJ9sdKWQWLlyoH374od/+y+PxaMWKFfrqq6/sjhdSEfGxS1FRkQoKCpSVlaXs7Gxt3rxZfr9fixYtsjtaSHi9XpWXl2v37t1yuVx9nw273W7Fx8fbnC64XC7XJeeyJCQkKDk5OWzPcVm+fLmmT5+u9evXa/78+aqrq9P27du1fft2u6OFxOzZs7Vu3TplZGRo/Pjx+u6777Rp0yYtXrzY7mhBcebMGf3yyy99t48fP67GxkYlJSUpIyNDhYWFeu211zR69GhlZmaquLhYHo9Hc+bMsS/0TbjSeIcPH65HH31UDQ0N2rt3r3p7e/v2X0lJSYqNjbUr9g272vb9a7kaMmSI0tLSdNddd5mOapbdl9uYsnXrVisjI8OKjY21srOzrdraWrsjhYyky047duywO5oR4X6prWVZ1p49e6wJEyZYTqfTGjNmjLV9+3a7I4WMz+ezli1bZmVkZFhxcXHWHXfcYb388stWd3e33dGCYv/+/Zf991pQUGBZ1oXLbYuLi63U1FTL6XRaM2bMsJqbm+0NfROuNN7jx4//7f5r//79dke/IVfbvn8VKZfaOixrYH1NYCAQUGtrq1wuV8SdgAMAwGBlWZa6urrk8Xgu+aj0rwbcxy6tra1KT0+3OwYAALgBLS0tV73IYcCVD5fLJelC+HA9wxkAgHDj8/mUnp7e9z5+JQOufFz8qCUxMZHyAQDAIHMtp0yE/aW2AABgYKF8AAAAoygfYcp/3i/HKw45XnHIf95vdxwAAPpQPgAAgFGUDwAAYBTlAwAAGEX5AAAARlE+AACAUZQPAABgFOUDAAAYRfkAAABGUT4AAIBRlA8AAGAU5QMAABhF+QAAAEZRPgAAgFGUD+Am8OvBAHD9KB8AAMAoygcAADCK8gEAAIyifAAAAKMoHwAAwCjKBwAAMIryAQAAjKJ8AAAAoygfAADAKMoHAAAw6rrKR0lJiaZOnSqXy6WUlBTNmTNHzc3N/ZY5d+6cvF6vkpOTdeutt2revHlqb28PamgAADB4XVf5qK6ultfrVW1trSorK9XT06OZM2fK7//Xb1osX75ce/bs0SeffKLq6mq1trZq7ty5QQ8OAAAGp5jrWfjLL7/sd/uf//ynUlJSVF9frwceeECdnZ363//9X5WXl+s//uM/JEk7duzQ2LFjVVtbq/vuuy94yQEAwKB0U+d8dHZ2SpKSkpIkSfX19erp6VFeXl7fMmPGjFFGRoZqamouu47u7m75fL5+EwAACF83XD4CgYAKCwuVm5urCRMmSJLa2toUGxuroUOH9ls2NTVVbW1tl11PSUmJ3G5335Senn6jkQAAwCBww+XD6/WqqalJO3fuvKkAq1evVmdnZ9/U0tJyU+sDAAAD23Wd83HRkiVLtHfvXh04cEAjRozom5+Wlqbz58/r9OnT/Y5+tLe3Ky0t7bLrcjqdcjqdNxIDAAAMQtd15MOyLC1ZskQVFRXat2+fMjMz+90/ZcoUDRkyRFVVVX3zmpubdfLkSeXk5AQnMQAAGNSu68iH1+tVeXm5du/eLZfL1Xceh9vtVnx8vNxut5599lkVFRUpKSlJiYmJeuGFF5STk8OVLgAAQNJ1lo+ysjJJ0kMPPdRv/o4dO/TMM89Ikt566y1FRUVp3rx56u7uVn5+vt59992ghAUAAIPfdZUPy7KuukxcXJxKS0tVWlp6w6EAAED44rddAACAUZSPEPOf98vxikOOVxzyn/df/QEAAIQ5ygcAADCK8gEAAIyifAAAAKMoHwAAwCjKBwAAMIryAQAAjKJ8AAAAoygfAADAKMoHAAAwivIBAACMonwAAACjKB8ABjx+IwkIL5QPAABgFOUDAAAYRfkAAABGUT4AAIBRlA8AAGAU5QMAABhF+QAAAEZRPgAAgFGUDwAAYBTlAwAAGEX5AAAARlE+AACAUZQPAABgFOUDAAAYRfkAAABGUT4AAIBRlA8AAGAU5QMAABhF+QAAAEZRPgAAgFGUDwAAYBTlAwAAGEX5AAAARlE+AACAUZQPAABgFOUDAAAYRfkAgAHGf94vxysOOV5xyH/eb3ccIOgoHwAAwCjKBwAAMIryAQAAjKJ8AAAAoygfAADAKMoHAAAwivIBAACMonwAAACjKB8AAMAoygcAADCK8gEAAIyifAAAAKMoHwAAwCjKBwAAMIryAQAAjKJ8AAAAoygfAADAqJCVj9LSUo0aNUpxcXGaNm2a6urqQvVUAABgEAlJ+di1a5eKioq0du1aNTQ0aNKkScrPz1dHR0cong4AAAwiISkfmzZt0nPPPadFixZp3Lhx2rZtm2655RZ98MEHoXg6AAAwiAS9fJw/f1719fXKy8v715NERSkvL081NTWXLN/d3S2fz9dvAgAA4Ssm2Cs8deqUent7lZqa2m9+amqqjhw5csnyJSUleuWVV4IdY8BIiE2QtdaKmOeNNLzOZkTa6xxp40Xksf1ql9WrV6uzs7NvamlpsTsSAAAIoaAf+Rg2bJiio6PV3t7eb357e7vS0tIuWd7pdMrpdAY7BgAAGKCCfuQjNjZWU6ZMUVVVVd+8QCCgqqoq5eTkBPvpAADAIBP0Ix+SVFRUpIKCAmVlZSk7O1ubN2+W3+/XokWLrvpYy7rwOScnngIAMHhcfN+++D5+JSEpH48//rj++OMPrVmzRm1tbbrnnnv05ZdfXnIS6uV0dXVJktLT00MRDQAAhFBXV5fcbvcVl3FY11JRDAoEAmptbZXL5ZLD4Qjqun0+n9LT09XS0qLExMSgrnsgYrzhjfGGt0gbrxR5Yw638VqWpa6uLnk8HkVFXfmsjpAc+bgZUVFRGjFiREifIzExMSw29LVivOGN8Ya3SBuvFHljDqfxXu2Ix0W2X2oLAAAiC+UDAAAYFVHlw+l0au3atRHzvSKMN7wx3vAWaeOVIm/MkTbefzfgTjgFAADhLaKOfAAAAPtRPgAAgFGUDwAAYBTlAwAAGBUx5aO0tFSjRo1SXFycpk2bprq6OrsjhUxJSYmmTp0ql8ullJQUzZkzR83NzXbHMuL111+Xw+FQYWGh3VFC6vfff9dTTz2l5ORkxcfHa+LEifr222/tjhUSvb29Ki4uVmZmpuLj43XnnXfq1VdfvabfjxgMDhw4oNmzZ8vj8cjhcOizzz7rd79lWVqzZo2GDx+u+Ph45eXl6dixY/aEDYIrjbenp0crV67UxIkTlZCQII/Ho6efflqtra32Bb5JV9u+/+7555+Xw+HQ5s2bjeWzS0SUj127dqmoqEhr165VQ0ODJk2apPz8fHV0dNgdLSSqq6vl9XpVW1uryspK9fT0aObMmfL7/XZHC6nDhw/rvffe09133213lJD6888/lZubqyFDhuiLL77QTz/9pDfffFO33Xab3dFCYsOGDSorK9M777yjn3/+WRs2bNDGjRu1detWu6MFhd/v16RJk1RaWnrZ+zdu3KgtW7Zo27ZtOnTokBISEpSfn69z584ZThocVxrv2bNn1dDQoOLiYjU0NOjTTz9Vc3OzHnnkERuSBsfVtu9FFRUVqq2tlcfjMZTMZlYEyM7Otrxeb9/t3t5ey+PxWCUlJTamMqejo8OSZFVXV9sdJWS6urqs0aNHW5WVldaDDz5oLVu2zO5IIbNy5Urr/vvvtzuGMbNmzbIWL17cb97cuXOtBQsW2JQodCRZFRUVfbcDgYCVlpZmvfHGG33zTp8+bTmdTuujjz6yIWFw/XW8l1NXV2dJsk6cOGEmVAj93Xh/++036/bbb7eampqskSNHWm+99ZbxbKaF/ZGP8+fPq76+Xnl5eX3zoqKilJeXp5qaGhuTmdPZ2SlJSkpKsjlJ6Hi9Xs2aNavfdg5Xn3/+ubKysvTYY48pJSVFkydP1vvvv293rJCZPn26qqqqdPToUUnS999/r4MHD+rhhx+2OVnoHT9+XG1tbf3+Xrvdbk2bNi2i9l8Oh0NDhw61O0pIBAIBLVy4UCtWrND48ePtjmPMgPthuWA7deqUent7lZqa2m9+amqqjhw5YlMqcwKBgAoLC5Wbm6sJEybYHSckdu7cqYaGBh0+fNjuKEb8+uuvKisrU1FRkV566SUdPnxYS5cuVWxsrAoKCuyOF3SrVq2Sz+fTmDFjFB0drd7eXq1bt04LFiywO1rItbW1SdJl918X7wtn586d08qVK/Xkk0+GzQ+v/dWGDRsUExOjpUuX2h3FqLAvH5HO6/WqqalJBw8etDtKSLS0tGjZsmWqrKxUXFyc3XGMCAQCysrK0vr16yVJkydPVlNTk7Zt2xaW5ePjjz/Whx9+qPLyco0fP16NjY0qLCyUx+MJy/Higp6eHs2fP1+WZamsrMzuOCFRX1+vt99+Ww0NDXI4HHbHMSrsP3YZNmyYoqOj1d7e3m9+e3u70tLSbEplxpIlS7R3717t379fI0aMsDtOSNTX16ujo0P33nuvYmJiFBMTo+rqam3ZskUxMTHq7e21O2LQDR8+XOPGjes3b+zYsTp58qRNiUJrxYoVWrVqlZ544glNnDhRCxcu1PLly1VSUmJ3tJC7uI+KtP3XxeJx4sQJVVZWhu1Rj2+++UYdHR3KyMjo23+dOHFCL774okaNGmV3vJAK+/IRGxurKVOmqKqqqm9eIBBQVVWVcnJybEwWOpZlacmSJaqoqNC+ffuUmZlpd6SQmTFjhn788Uc1Njb2TVlZWVqwYIEaGxsVHR1td8Sgy83NveTS6aNHj2rkyJE2JQqts2fPKiqq/64qOjpagUDApkTmZGZmKi0trd/+y+fz6dChQ2G7/7pYPI4dO6avv/5aycnJdkcKmYULF+qHH37ot//yeDxasWKFvvrqK7vjhVREfOxSVFSkgoICZWVlKTs7W5s3b5bf79eiRYvsjhYSXq9X5eXl2r17t1wuV99nw263W/Hx8TanCy6Xy3XJuSwJCQlKTk4O23Ncli9frunTp2v9+vWaP3++6urqtH37dm3fvt3uaCExe/ZsrVu3ThkZGRo/fry+++47bdq0SYsXL7Y7WlCcOXNGv/zyS9/t48ePq7GxUUlJScrIyFBhYaFee+01jR49WpmZmSouLpbH49GcOXPsC30TrjTe4cOH69FHH1VDQ4P27t2r3t7evv1XUlKSYmNj7Yp9w662ff9aroYMGaK0tDTdddddpqOaZfflNqZs3brVysjIsGJjY63s7GyrtrbW7kghI+my044dO+yOZkS4X2prWZa1Z88ea8KECZbT6bTGjBljbd++3e5IIePz+axly5ZZGRkZVlxcnHXHHXdYL7/8stXd3W13tKDYv3//Zf+9FhQUWJZ14XLb4uJiKzU11XI6ndaMGTOs5uZme0PfhCuN9/jx43+7/9q/f7/d0W/I1bbvX0XKpbYOywqTrwkEAACDQtif8wEAAAYWygcAADCK8gEAAIyifAAAAKMoHwAAwCjKBwAAMIryAQAAjKJ8AAAAoygfAADAKMoHAAAwivIBAACMonwAAACj/j8aCnCgEUwrgAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.subplot(3, 1, 1)\n", - "plt.vlines(\n", - " x=np.arange(candidate_mz_pattern.shape[1]),\n", - " ymin=0,\n", - " ymax=candidate_mz_pattern[0, :] * 100,\n", - " color=\"blue\",\n", - " label=\"candidate_mz_range\",\n", - " # linestyle=\"--\",\n", - ")\n", - "\n", - "plt.subplot(3, 1, 2)\n", - "plt.vlines(\n", - " x=np.arange(candidate_mz_pattern.shape[1]),\n", - " ymin=0,\n", - " ymax=candidate_mz_pattern[1, :] * 100,\n", - " color=\"red\",\n", - " label=\"candidate_mz_range\",\n", - " # linestyle=\"--\",\n", - ")\n", - "\n", - "plt.subplot(3, 1, 3)\n", - "plt.vlines(\n", - " x=np.arange(candidate_mz_pattern.shape[1]),\n", - " ymin=0,\n", - " ymax=candidate_mz_pattern[2, :] * 100,\n", - " color=\"green\",\n", - " label=\"candidate_mz_range\",\n", - " # linestyle=\"--\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.vlines(x=[0, 1, 2], ymin=0, ymax=candidate_act.sum(axis=0), label=\"candidate_act\")" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([288.79387178, 244.42120607, 392.89648914, 296.1748629 ,\n", - " 92.02655651, 334.03321061, 192.77713893, 169.12514039,\n", - " 195.96219309, 211.05564988, 245.85471113, 28.45774238,\n", - " 39.70407997, 90.324775 , 32.79577544, 9.09302447])" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.multiply(candidate_act.sum(axis=0), candidate_mz_pattern.T).sum(axis=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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xCDAAAMA4BJhm4NZeAAAuDgQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACM06wAk52drWuvvVadO3dWdHS0brvtNpWVlQXUjBgxQiEhIQHLlClTAmoqKiqUlpamDh06KDo6WjNmzFB9fX1AzaZNmzRo0CA5nU716tVLOTk55zZDAADQ5jQrwBQVFSk9PV3btm1TQUGBTp48qdTUVNXU1ATU3X///Tp06JC9LFy40B5raGhQWlqa6urqtHXrVr3++uvKycnR3Llz7Zry8nKlpaXpxhtvVGlpqTIyMnTfffdp3bp15zldAADQFoQ3p3jt2rUB6zk5OYqOjlZJSYmGDx9ub+/QoYPcbvcpj7F+/Xrt379fGzZsUExMjK6++motWLBAs2bN0rx58+RwOLR8+XIlJiZq0aJFkqS+fftqy5YtWrx4sbxeb3PnCAAA2pjzugamurpakhQVFRWwfcWKFerWrZv69++vrKwsHTt2zB4rLi5WcnKyYmJi7G1er1d+v1/79u2za1JSUgKO6fV6VVxcfNpeamtr5ff7AxYAANA2NesMzHc1NjYqIyND119/vfr3729vv/vuu5WQkKC4uDjt3r1bs2bNUllZmd58801Jks/nCwgvkux1n893xhq/36/jx48rIiLiB/1kZ2frscceO9fpAAAAg5xzgElPT9fevXu1ZcuWgO0PPPCA/XNycrJiY2M1cuRIffHFF7ryyivPvdOzyMrKUmZmpr3u9/sVHx/faq8HAACC55w+Qpo2bZry8vL0/vvvq3v37mesHTp0qCTp888/lyS53W5VVlYG1DStN103c7oal8t1yrMvkuR0OuVyuQIWAADQNjUrwFiWpWnTpmnNmjXauHGjEhMTz7pPaWmpJCk2NlaS5PF4tGfPHlVVVdk1BQUFcrlcSkpKsmsKCwsDjlNQUCCPx9OcdgHgknasrl49Z+er5+x8HaurP/sOgEGaFWDS09P1X//1X8rNzVXnzp3l8/nk8/l0/PhxSdIXX3yhBQsWqKSkRH//+9/19ttva8KECRo+fLgGDBggSUpNTVVSUpLGjx+vv/zlL1q3bp3mzJmj9PR0OZ1OSdKUKVP0t7/9TTNnztSnn36qF198UatXr9b06dNbePpm4E0IAIBAzQowy5YtU3V1tUaMGKHY2Fh7WbVqlSTJ4XBow4YNSk1NVZ8+ffTwww9rzJgxeuedd+xjhIWFKS8vT2FhYfJ4PLrnnns0YcIEzZ8/365JTExUfn6+CgoKNHDgQC1atEgvv/wyt1ADAABJzbyI17KsM47Hx8erqKjorMdJSEjQu+++e8aaESNG6OOPP25OewAA4BLBs5AAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAaGXH6urVc3a+es7O17G6+mC3A7QJBBgAAGAcAgwAADAOAQYAABiHAAMAAIzTrACTnZ2ta6+9Vp07d1Z0dLRuu+02lZWVBdScOHFC6enp6tq1qzp16qQxY8aosrIyoKaiokJpaWnq0KGDoqOjNWPGDNXXB17YtmnTJg0aNEhOp1O9evVSTk7Ouc0QAAC0Oc0KMEVFRUpPT9e2bdtUUFCgkydPKjU1VTU1NXbN9OnT9c477+iNN95QUVGRDh48qNtvv90eb2hoUFpamurq6rR161a9/vrrysnJ0dy5c+2a8vJypaWl6cYbb1RpaakyMjJ03333ad26dS0wZQAAYLrw5hSvXbs2YD0nJ0fR0dEqKSnR8OHDVV1drVdeeUW5ubm66aabJEmvvfaa+vbtq23btmnYsGFav3699u/frw0bNigmJkZXX321FixYoFmzZmnevHlyOBxavny5EhMTtWjRIklS3759tWXLFi1evFher7eFpg4AAEx1XtfAVFdXS5KioqIkSSUlJTp58qRSUlLsmj59+qhHjx4qLi6WJBUXFys5OVkxMTF2jdfrld/v1759++ya7x6jqabpGKdSW1srv98fsAAAgLbpnANMY2OjMjIydP3116t///6SJJ/PJ4fDoS5dugTUxsTEyOfz2TXfDS9N401jZ6rx+/06fvz4KfvJzs5WZGSkvcTHx5/r1AAAwEXunANMenq69u7dq5UrV7ZkP+csKytL1dXV9nLgwIFgtwQAAFpJs66BaTJt2jTl5eVp8+bN6t69u73d7Xarrq5Ohw8fDjgLU1lZKbfbbdfs2LEj4HhNdyl9t+b7dy5VVlbK5XIpIiLilD05nU45nc5zmQ4AADBMs87AWJaladOmac2aNdq4caMSExMDxgcPHqx27dqpsLDQ3lZWVqaKigp5PB5Jksfj0Z49e1RVVWXXFBQUyOVyKSkpya757jGaapqOAQAALm3NOgOTnp6u3Nxc/fnPf1bnzp3ta1YiIyMVERGhyMhITZ48WZmZmYqKipLL5dKDDz4oj8ejYcOGSZJSU1OVlJSk8ePHa+HChfL5fJozZ47S09PtMyhTpkzRCy+8oJkzZ2rSpEnauHGjVq9erfz8/BaePoBLybG6eiXN/efXMeyf71UHxzmdhAZwEWjWGZhly5apurpaI0aMUGxsrL2sWrXKrlm8eLF+9atfacyYMRo+fLjcbrfefPNNezwsLEx5eXkKCwuTx+PRPffcowkTJmj+/Pl2TWJiovLz81VQUKCBAwdq0aJFevnll7mFGgAASGrmGRjLss5a0759ey1dulRLly49bU1CQoLefffdMx5nxIgR+vjjj5vTHgAAuETwLCTgEnasrl49Z+er5+x8HaurP/sOAHCRIMAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYABfcsbp69Zydr56z83Wsrj7Y7QAwEAEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMZpdoDZvHmzRo8erbi4OIWEhOitt94KGP/Xf/1XhYSEBCw333xzQM0333yjcePGyeVyqUuXLpo8ebKOHj0aULN79279/Oc/V/v27RUfH6+FCxc2f3YAAKBNanaAqamp0cCBA7V06dLT1tx88806dOiQvfzpT38KGB83bpz27dungoIC5eXlafPmzXrggQfscb/fr9TUVCUkJKikpERPP/205s2bp5deeqm57QIAgDYovLk7jBo1SqNGjTpjjdPplNvtPuXYJ598orVr12rnzp0aMmSIJOn555/XLbfcot///veKi4vTihUrVFdXp1dffVUOh0P9+vVTaWmpnnnmmYCgAwAALk2tcg3Mpk2bFB0drd69e2vq1Kn6+uuv7bHi4mJ16dLFDi+SlJKSotDQUG3fvt2uGT58uBwOh13j9XpVVlamb7/99pSvWVtbK7/fH7AAAIC2qcUDzM0336w//vGPKiws1FNPPaWioiKNGjVKDQ0NkiSfz6fo6OiAfcLDwxUVFSWfz2fXxMTEBNQ0rTfVfF92drYiIyPtJT4+vqWnBgAALhLN/gjpbMaOHWv/nJycrAEDBujKK6/Upk2bNHLkyJZ+OVtWVpYyMzPtdb/fT4gBAKCNavXbqK+44gp169ZNn3/+uSTJ7XarqqoqoKa+vl7ffPONfd2M2+1WZWVlQE3T+umurXE6nXK5XAELAABom1o9wHz11Vf6+uuvFRsbK0nyeDw6fPiwSkpK7JqNGzeqsbFRQ4cOtWs2b96skydP2jUFBQXq3bu3LrvsstZuGQAAXOSaHWCOHj2q0tJSlZaWSpLKy8tVWlqqiooKHT16VDNmzNC2bdv097//XYWFhbr11lvVq1cveb1eSVLfvn1188036/7779eOHTv04Ycfatq0aRo7dqzi4uIkSXfffbccDocmT56sffv2adWqVVqyZEnAR0QAAODS1ewA89FHH+maa67RNddcI0nKzMzUNddco7lz5yosLEy7d+/Wr3/9a/30pz/V5MmTNXjwYH3wwQdyOp32MVasWKE+ffpo5MiRuuWWW3TDDTcEfMdLZGSk1q9fr/Lycg0ePFgPP/yw5s6dyy3UAABA0jlcxDtixAhZlnXa8XXr1p31GFFRUcrNzT1jzYABA/TBBx80tz0AAHAJ4FlIAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxmh1gNm/erNGjRysuLk4hISF66623AsYty9LcuXMVGxuriIgIpaSk6LPPPguo+eabbzRu3Di5XC516dJFkydP1tGjRwNqdu/erZ///Odq37694uPjtXDhwubPDgAAtEnNDjA1NTUaOHCgli5desrxhQsX6rnnntPy5cu1fft2dezYUV6vVydOnLBrxo0bp3379qmgoEB5eXnavHmzHnjgAXvc7/crNTVVCQkJKikp0dNPP6158+bppZdeOocpAgCAtia8uTuMGjVKo0aNOuWYZVl69tlnNWfOHN16662SpD/+8Y+KiYnRW2+9pbFjx+qTTz7R2rVrtXPnTg0ZMkSS9Pzzz+uWW27R73//e8XFxWnFihWqq6vTq6++KofDoX79+qm0tFTPPPNMQNABAACXpha9Bqa8vFw+n08pKSn2tsjISA0dOlTFxcWSpOLiYnXp0sUOL5KUkpKi0NBQbd++3a4ZPny4HA6HXeP1elVWVqZvv/32lK9dW1srv98fsAAAgLapRQOMz+eTJMXExARsj4mJscd8Pp+io6MDxsPDwxUVFRVQc6pjfPc1vi87O1uRkZH2Eh8ff/4TAgAAF6U2cxdSVlaWqqur7eXAgQPBbgkAALSSFg0wbrdbklRZWRmwvbKy0h5zu92qqqoKGK+vr9c333wTUHOqY3z3Nb7P6XTK5XIFLAAAoG1q0QCTmJgot9utwsJCe5vf79f27dvl8XgkSR6PR4cPH1ZJSYlds3HjRjU2Nmro0KF2zebNm3Xy5Em7pqCgQL1799Zll13Wki0DAAADNTvAHD16VKWlpSotLZX0zwt3S0tLVVFRoZCQEGVkZOh3v/ud3n77be3Zs0cTJkxQXFycbrvtNklS3759dfPNN+v+++/Xjh079OGHH2ratGkaO3as4uLiJEl33323HA6HJk+erH379mnVqlVasmSJMjMzW2ziAADAXM2+jfqjjz7SjTfeaK83hYqJEycqJydHM2fOVE1NjR544AEdPnxYN9xwg9auXav27dvb+6xYsULTpk3TyJEjFRoaqjFjxui5556zxyMjI7V+/Xqlp6dr8ODB6tatm+bOncst1AAAQNI5BJgRI0bIsqzTjoeEhGj+/PmaP3/+aWuioqKUm5t7xtcZMGCAPvjgg+a2BwAALgFt5i4koCUcq6tXz9n56jk7X8fq6oPdDgDgNAgwAACcB/7HJzgIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxmnxADNv3jyFhIQELH369LHHT5w4ofT0dHXt2lWdOnXSmDFjVFlZGXCMiooKpaWlqUOHDoqOjtaMGTNUX1/f0q0CAABDhbfGQfv166cNGzb8/4uE///LTJ8+Xfn5+XrjjTcUGRmpadOm6fbbb9eHH34oSWpoaFBaWprcbre2bt2qQ4cOacKECWrXrp2eeOKJ1mgXAAAYplUCTHh4uNxu9w+2V1dX65VXXlFubq5uuukmSdJrr72mvn37atu2bRo2bJjWr1+v/fv3a8OGDYqJidHVV1+tBQsWaNasWZo3b54cDkdrtAwAAAzSKtfAfPbZZ4qLi9MVV1yhcePGqaKiQpJUUlKikydPKiUlxa7t06ePevTooeLiYklScXGxkpOTFRMTY9d4vV75/X7t27fvtK9ZW1srv98fsAAAgLapxQPM0KFDlZOTo7Vr12rZsmUqLy/Xz3/+cx05ckQ+n08Oh0NdunQJ2CcmJkY+n0+S5PP5AsJL03jT2OlkZ2crMjLSXuLj41t2YgAA4KLR4h8hjRo1yv55wIABGjp0qBISErR69WpFRES09MvZsrKylJmZaa/7/X5CDAAAbVSr30bdpUsX/fSnP9Xnn38ut9uturo6HT58OKCmsrLSvmbG7Xb/4K6kpvVTXVfTxOl0yuVyBSwAAKBtavUAc/ToUX3xxReKjY3V4MGD1a5dOxUWFtrjZWVlqqiokMfjkSR5PB7t2bNHVVVVdk1BQYFcLpeSkpJau10AAGCAFv8I6d/+7d80evRoJSQk6ODBg3r00UcVFhamu+66S5GRkZo8ebIyMzMVFRUll8ulBx98UB6PR8OGDZMkpaamKikpSePHj9fChQvl8/k0Z84cpaeny+l0tnS7AADAQC0eYL766ivddddd+vrrr3X55Zfrhhtu0LZt23T55ZdLkhYvXqzQ0FCNGTNGtbW18nq9evHFF+39w8LClJeXp6lTp8rj8ahjx46aOHGi5s+f39KtAgAAQ7V4gFm5cuUZx9u3b6+lS5dq6dKlp61JSEjQu+++29KtAQCANoJnIQEAAOMQYAAAgHEIMACANuFYXb16zs5Xz9n5OlbHA4DbOgIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAGCgS/2iZQIMAAAwDgEGAAAYhwADAACMQ4ABALSoS/3aDFwYBBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAADwox2rq1fP2fnqOTtfx+rqg9YHAQYAABiHAAMAAIxzUQeYpUuXqmfPnmrfvr2GDh2qHTt2BLslAABwEbhoA8yqVauUmZmpRx99VLt27dLAgQPl9XpVVVUV7NYAAECQXbQB5plnntH999+ve++9V0lJSVq+fLk6dOigV199NditAQCAILsoA0xdXZ1KSkqUkpJibwsNDVVKSoqKi4tPuU9tba38fn/AAgAA2qYQy7KsYDfxfQcPHtRPfvITbd26VR6Px94+c+ZMFRUVafv27T/YZ968eXrsscd+sL26uloul6tV+wUAAC3D7/crMjLyrH+/L8ozMOciKytL1dXV9nLgwIFgtwQAAFpJeLAbOJVu3bopLCxMlZWVAdsrKyvldrtPuY/T6ZTT6bwQ7QEAgCC7KM/AOBwODR48WIWFhfa2xsZGFRYWBnykBAAALk0X5RkYScrMzNTEiRM1ZMgQXXfddXr22WdVU1Oje++9N9itAQCAILtoA8ydd96pf/zjH5o7d658Pp+uvvpqrV27VjExMcFuDQAABNlFeRdSS/ixVzEDAICLxyV3FxIAALh0EGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAONctI8SOF9NXzDs9/uD3AkAAPixmv5un+1BAW02wBw5ckSSFB8fH+ROAABAcx05ckSRkZGnHW+zz0JqbGzUwYMH1blzZ4WEhLTYcf1+v+Lj43XgwIFL5hlLl9qcmW/bxnzbNuZrPsuydOTIEcXFxSk09PRXurTZMzChoaHq3r17qx3f5XK1mX9ZfqxLbc7Mt21jvm0b8zXbmc68NOEiXgAAYBwCDAAAMA4BppmcTqceffRROZ3OYLdywVxqc2a+bRvzbduY76WjzV7ECwAA2i7OwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCTDMtXbpUPXv2VPv27TV06FDt2LEj2C21iuzsbF177bXq3LmzoqOjddttt6msrCzYbV0wTz75pEJCQpSRkRHsVlrN//zP/+iee+5R165dFRERoeTkZH300UfBbqtVNDQ06JFHHlFiYqIiIiJ05ZVXasGCBWd91opJNm/erNGjRysuLk4hISF66623AsYty9LcuXMVGxuriIgIpaSk6LPPPgtOsy3gTPM9efKkZs2apeTkZHXs2FFxcXGaMGGCDh48GLyGz9PZfr/fNWXKFIWEhOjZZ5+9YP0FAwGmGVatWqXMzEw9+uij2rVrlwYOHCiv16uqqqpgt9biioqKlJ6erm3btqmgoEAnT55Uamqqampqgt1aq9u5c6f+8Ic/aMCAAcFupdV8++23uv7669WuXTu999572r9/vxYtWqTLLrss2K21iqeeekrLli3TCy+8oE8++URPPfWUFi5cqOeffz7YrbWYmpoaDRw4UEuXLj3l+MKFC/Xcc89p+fLl2r59uzp27Civ16sTJ05c4E5bxpnme+zYMe3atUuPPPKIdu3apTfffFNlZWX69a9/HYROW8bZfr9N1qxZo23btikuLu4CdRZEFn606667zkpPT7fXGxoarLi4OCs7OzuIXV0YVVVVliSrqKgo2K20qiNHjlhXXXWVVVBQYP3iF7+wHnrooWC31CpmzZpl3XDDDcFu44JJS0uzJk2aFLDt9ttvt8aNGxekjlqXJGvNmjX2emNjo+V2u62nn37a3nb48GHL6XRaf/rTn4LQYcv6/nxPZceOHZYk68svv7wwTbWi0833q6++sn7yk59Ye/futRISEqzFixdf8N4uJM7A/Eh1dXUqKSlRSkqKvS00NFQpKSkqLi4OYmcXRnV1tSQpKioqyJ20rvT0dKWlpQX8ntuit99+W0OGDNG//Mu/KDo6Wtdcc43+8z//M9httZqf/exnKiws1F//+ldJ0l/+8hdt2bJFo0aNCnJnF0Z5ebl8Pl/Av9eRkZEaOnToJfH+Jf3zPSwkJERdunQJdiutorGxUePHj9eMGTPUr1+/YLdzQbTZhzm2tP/93/9VQ0ODYmJiArbHxMTo008/DVJXF0ZjY6MyMjJ0/fXXq3///sFup9WsXLlSu3bt0s6dO4PdSqv729/+pmXLlikzM1P//u//rp07d+q3v/2tHA6HJk6cGOz2Wtzs2bPl9/vVp08fhYWFqaGhQY8//rjGjRsX7NYuCJ/PJ0mnfP9qGmvLTpw4oVmzZumuu+5qUw88/K6nnnpK4eHh+u1vfxvsVi4YAgzOKj09XXv37tWWLVuC3UqrOXDggB566CEVFBSoffv2wW6n1TU2NmrIkCF64oknJEnXXHON9u7dq+XLl7fJALN69WqtWLFCubm56tevn0pLS5WRkaG4uLg2OV/8v5MnT+o3v/mNLMvSsmXLgt1OqygpKdGSJUu0a9cuhYSEBLudC4aPkH6kbt26KSwsTJWVlQHbKysr5Xa7g9RV65s2bZry8vL0/vvvq3v37sFup9WUlJSoqqpKgwYNUnh4uMLDw1VUVKTnnntO4eHhamhoCHaLLSo2NlZJSUkB2/r27auKioogddS6ZsyYodmzZ2vs2LFKTk7W+PHjNX36dGVnZwe7tQui6T3qUnv/agovX375pQoKCtrs2ZcPPvhAVVVV6tGjh/3+9eWXX+rhhx9Wz549g91eqyHA/EgOh0ODBw9WYWGhva2xsVGFhYXyeDxB7Kx1WJaladOmac2aNdq4caMSExOD3VKrGjlypPbs2aPS0lJ7GTJkiMaNG6fS0lKFhYUFu8UWdf311//gtvi//vWvSkhICFJHrevYsWMKDQ18uwsLC1NjY2OQOrqwEhMT5Xa7A96//H6/tm/f3ibfv6T/Dy+fffaZNmzYoK5duwa7pVYzfvx47d69O+D9Ky4uTjNmzNC6deuC3V6r4SOkZsjMzNTEiRM1ZMgQXXfddXr22WdVU1Oje++9N9ittbj09HTl5ubqz3/+szp37mx/Th4ZGamIiIggd9fyOnfu/IPrezp27KiuXbu2yet+pk+frp/97Gd64okn9Jvf/EY7duzQSy+9pJdeeinYrbWK0aNH6/HHH1ePHj3Ur18/ffzxx3rmmWc0adKkYLfWYo4eParPP//cXi8vL1dpaamioqLUo0cPZWRk6He/+52uuuoqJSYm6pFHHlFcXJxuu+224DV9Hs4039jYWN1xxx3atWuX8vLy1NDQYL+HRUVFyeFwBKvtc3a23+/3A1q7du3kdrvVu3fvC93qhRPs26BM8/zzz1s9evSwHA6Hdd1111nbtm0LdkutQtIpl9deey3YrV0wbfk2asuyrHfeecfq37+/5XQ6rT59+lgvvfRSsFtqNX6/33rooYesHj16WO3bt7euuOIK6z/+4z+s2traYLfWYt5///1T/jc7ceJEy7L+eSv1I488YsXExFhOp9MaOXKkVVZWFtymz8OZ5lteXn7a97D3338/2K2fk7P9fr/vUriNOsSy2tBXUQIAgEsC18AAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYJz/A/5Q9y+iuIcHAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.vlines(\n", - " x=np.arange(candidate_mz_pattern.shape[1]),\n", - " ymin=0,\n", - " ymax=np.multiply(candidate_act.sum(axis=0), candidate_mz_pattern.T).sum(axis=1)\n", - " * 10,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "([,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ],\n", - " [Text(-200.0, 0, '0.85'),\n", - " Text(0.0, 0, '0.93'),\n", - " Text(200.0, 0, '1.01'),\n", - " Text(400.0, 0, '1.08'),\n", - " Text(600.0, 0, '1.16'),\n", - " Text(800.0, 0, '1.24'),\n", - " Text(1000.0, 0, '1.32')])" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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bQkR+jOGGiCRXV1fndhpWbvSF1RrSE4YbIlIMu6WISAkMN0SkGIYb/eKYG9IThhsiIiIyFIYbIiIiMhSGGyJSBbul9IXdUqQnDDdEpBiOuSEiJTDcEJFiGG70i9Ua0hOGGyIiEoVBh7SO4YaIVMHKjb4w0JCeMNwQERFpAAOkdBhuiEgxHHOjXzxbivSE4YaIFMODIpFrDPzSYbghIlVwR64vDKakJww3RKQKhhv9YtAhrWO4ISIi0gCGRukw3BCRYjigWL944CU9YbghIsXwAGkM/BzlwcAvHYYbIlIFd+T6wkCjrGeeeYbb3Aeiwk1mZiZuv/12hIWFISoqChMnTkRJSYnDNCNGjEBAQIDD46mnnnKYpqysDMnJyQgNDUVUVBTmzJmDhoYG39eGiHSD4YbItezsbOzevVvtZuhWezET5+bmIjU1FbfffjsaGhrwhz/8AWPGjMGxY8fQqVMn+3TTp0/HokWL7L+Hhobaf25sbERycjJiYmKQl5eHiooKTJ06FR06dMBLL70kwSoREZHUWEWQX+ttfOnSJXUaYgCiws327dsdfl+9ejWioqJQWFiIe++91/58aGgoYmJinM5j586dOHbsGD799FNER0fjlltuweLFizF37lwsWLAAQUFBXqwGEekBBxQbA4MOaZ1PY26qq6sBAJGRkQ7Pr1mzBl27dsXAgQORnp6OK1eu2F/Lz8/HoEGDEB0dbX8uKSkJVqsVR48edbocm80Gq9Xq8CAi/eFBUb/42cmPgV86oio3LTU1NWHWrFkYNmwYBg4caH/+0UcfRc+ePREXF4fDhw9j7ty5KCkpwcaNGwEAFovFIdgAsP9usVicLiszMxMLFy70tqlEpEHckRORXLwON6mpqThy5Ai++OILh+dnzJhh/3nQoEGIjY3FqFGjUFpaij59+ni1rPT0dMyePdv+u9VqRXx8vHcNJyJNYLjRF944k/TEq26ptLQ0bN26FZ999hm6d+/e5rSJiYkAgFOnTgEAYmJiUFlZ6TBN8++uxukEBwfDZDI5PIhIfzjmhsg1hkbpiAo3giAgLS0NmzZtwp49e9CrVy+37ykqKgIAxMbGAgDMZjOKi4tRVVVln2bXrl0wmUxISEgQ0xwiIlIID7ykJ6K6pVJTU5GTk4MtW7YgLCzMPkYmPDwcHTt2RGlpKXJycvDAAw+gS5cuOHz4MJ577jnce++9GDx4MABgzJgxSEhIwJQpU7Bs2TJYLBZkZGQgNTUVwcHB0q8hEWkSKzf6xaAjD/5NSEdU5SY7OxvV1dUYMWIEYmNj7Y/169cDAIKCgvDpp59izJgx6N+/P55//nlMmjQJH3/8sX0egYGB2Lp1KwIDA2E2m/HYY49h6tSpDtfFISIi8ncMkd4TVblxt6Hj4+ORm5vrdj49e/bEtm3bxCyaiAyAO2v94mdHesJ7SxGRYjig2BgYdOTB7SodhhsiUgXDjb7wwEt6wnBDRKpguCFyxL8J6TDcEBGRW7yIH+kJww0RKYZjbohICQw3RKQY/sevXX//+99x00032a8m3xo/O/lxG0uH4YaIVMHKjfLOnDmDCxcuOH1t+vTpOHnyJJ555hm38+FBWBnczt7z+saZRES+YLhRVkVFBXr37g2g7YOmzWZz+jwPtPLj34R0WLkhIvIDX3/9tdpNIFIMww0RKYYDiolICQw3RKSYpqYmtZtAXuKp4PLjdpUOww0RKaZluGHlRpv4uZARMNwQkWLYLaVfrCrIj38T0mG4ISLFsHJjDAw6pHUMN0SkGI650S8GGtIThhsiUgy7pYhcY4CUDsMNESmGO2/tcxU6ebaU8ridvcdwQ0SK4ZgbItf4NyEdhhsiUgzDjX6xikB6wnBDRIrhgGJjYNAhrWO4ISLFtB5QzIOk9rCiph7+PUiH4YaIFNNy5/3aa6+hR48eKC0tVbFF5CkeeElPGG6ISDEtD5DfffcdfvjhBzz//PMqtoi8waBDWsdwQ0SSW79+PY4ePXrN842NjR49R9rDQEN6wnBDRJLbsWMHBg4ceM3zHFBM5Frr8U4MlN5juCEixXBnrV+8iJ/8uF2lw3BDRKSQK1euqN0EIr/AcENEpIAvvvgCnTp10u0AalYVlMdt7j2GGyIiBbzwwgsAgOXLl6vcEiLjY7ghIiK3OOZGfryAonQYboiIyI4HWPUwNEpHVLjJzMzE7bffjrCwMERFRWHixIkoKSlxmObq1atITU1Fly5d0LlzZ0yaNAmVlZUO05SVlSE5ORmhoaGIiorCnDlz0NDQ4PvaEJFquGMmIq0QFW5yc3ORmpqKgoIC7Nq1C/X19RgzZgxqa2vt0zz33HP4+OOPsWHDBuTm5uLcuXN48MEH7a83NjYiOTkZdXV1yMvLw7vvvovVq1fjxRdflG6tiIhIUuyWIj1pL2bi7du3O/y+evVqREVFobCwEPfeey+qq6vxzjvvICcnByNHjgQArFq1CjfffDMKCgpw5513YufOnTh27Bg+/fRTREdH45ZbbsHixYsxd+5cLFiwAEFBQdKtHREphge8tnH7ECnHpzE31dXVAIDIyEgAQGFhIerr6zF69Gj7NP3790ePHj2Qn58PAMjPz8egQYMQHR1tnyYpKQlWq9Xp5doBwGazwWq1OjyIiEg5DGfy43gn6XgdbpqamjBr1iwMGzbMfpl1i8WCoKAgREREOEwbHR0Ni8Vin6ZlsGl+vfk1ZzIzMxEeHm5/xMfHe9tsIpIJD35t08v2aWxsRFpaGtavX+9yGr2si9603q7czt7zOtykpqbiyJEjWLdunZTtcSo9PR3V1dX2R3l5uezLJCLyR7m5ucjKysLDDz/s8DwPtKQnosbcNEtLS8PWrVuxb98+dO/e3f58TEwM6urqcOnSJYfqTWVlJWJiYuzTHDhwwGF+zWdTNU/TWnBwMIKDg71pKhEphAc/ItIKUZUbQRCQlpaGTZs2Yc+ePejVq5fD60OHDkWHDh2we/du+3MlJSUoKyuD2WwGAJjNZhQXF6Oqqso+za5du2AymZCQkODLuhARaZbewx/PlpLH2bNnr/mHn3wnqnKTmpqKnJwcbNmyBWFhYfYxMuHh4ejYsSPCw8Mxbdo0zJ49G5GRkTCZTHj22WdhNptx5513AgDGjBmDhIQETJkyBcuWLYPFYkFGRgZSU1NZnSHSMR7w9EMQBA5e1Yjm3o+ioiJ+JhISVbnJzs5GdXU1RowYgdjYWPuj5cCzV199Fb/+9a8xadIk3HvvvYiJicHGjRvtrwcGBmLr1q0IDAyE2WzGY489hqlTp2LRokXSrRURkcZoKfy1bsuZM2dEv4eklZeXx20sIVGVG082fEhICLKyspCVleVymp49e2Lbtm1iFk1ERDIZO3asqOl5ECat472liEgSPODpR+vP6sSJEyq1hEgeDDdERArQe/jTe/v1iNvceww3RCQJ7oj1w9fPip81aR3DDRGpigdKfeDnJD9uY+kw3BCRJLhj1g9+VtrD08ClxXBDRKriTl0fGIjkx20sHYYbIpIEd8xt09L2UWrMTUNDAw4fPqypdSf/wHBDRERueRNQHnvsMQwZMgTLly+XoUVErjHcEJEk+N9527S0fZRqS/PV65ctW6bI8vROS98RvWO4ISIit3jjTNIThhsiIg8IgoCGhgaf3q8VWmoL/Qc/F+kw3BCRJIy+Yx43bhyioqJQU1OjdlN8ZvTPSo+cnTXIz8l7DDdERB7YsWMHfvrpJ+zYsUPtpqiC3VKkJww3RCQJHvDapqXto6W20H/wc5EOww0REbnFAy/pCcMNEUmCB7+2aWn78MaZ2sTtKh2GGyIiEfz1dhE88JKeMNwQkSR48NMPqT+ryspK5OXlSTpPIl8w3BARkVttnS0VExODYcOGITc3V+lmGQr/QZAOww0RSYI7Zv3w9LOaP38+1q5d6/F8P/30U2+b5Pd4nRtptVe7AURE/kCPB6pFixYBAB555BFdtl9vuI2lw8oNEZGf4UGUjI7hhogkwQOmtkl5hWGx7+d3g5TGcENEJIK3p4Lr/QCv9/brAbexdBhuiEgSau2Yv//+e8yZMwdlZWWqLF8vWoYypT8rf702kFg5OTlqN8EwOKCYiHRt7Nix+Pbbb/HJJ5/gyJEjajfHJb3/V84bZ0qv9Xbctm2bSi0xHlZuiEgSah3wvv32WwDA0aNHVVm+Hvn6Wf3+97+XqCX+jSFRPgw3RETkVssD8cmTJ1VsiXE0NTU5/bkZw4/3GG6ISBLcEbdNS9tHS23xZy0/h8bGRhVbYjwMN0RE5BYDkfQYbuTDcENEsiopKVG7CZIywqngSrdFS+uuJQw38hEdbvbt24fx48cjLi4OAQEB2Lx5s8Pr//M//4OAgACHx9ixYx2muXjxIiZPngyTyYSIiAhMmzYNNTU1Pq0IEanL1QFszJgxCrdEXv56oJZ7vYuKijBo0CD8+9//lnU5WtJymzobc0PeEx1uamtrMWTIEGRlZbmcZuzYsaioqLA/Wt94bfLkyTh69Ch27dqFrVu3Yt++fZgxY4b41hORZlgsFqfPe3L9mZ9//hnl5eVSN4lc0OJ1biZMmIAjR47g17/+tQIt0gZ3lRt/DdJSEH2dm3HjxmHcuHFtThMcHIyYmBinrx0/fhzbt2/HwYMHcdtttwEAVqxYgQceeACvvPIK4uLixDaJiFR2/vx5DBo0yOv3DxgwAGfOnEFxcTEGDhwoYcukxwvSyeOnn35SuwmKY7eUfGQZc7N3715ERUWhX79+ePrpp3HhwgX7a/n5+YiIiLAHGwAYPXo02rVrh/379zudn81mg9VqdXgQkXYcOnTIp/efOXMGALBp0yYpmkNueFMRkLuK4I9VCnfdUv64TaQiebgZO3Ys/vnPf2L37t14+eWXkZubi3HjxtlTqcViQVRUlMN72rdvj8jISJdl7czMTISHh9sf8fHxUjebiEhWah+otH6FYS22SW4tAw27paQl+e0XHn74YfvPgwYNwuDBg9GnTx/s3bsXo0aN8mqe6enpmD17tv13q9XKgENkQFrt8uFBRv5t4I8DatktJR/ZTwXv3bs3unbtilOnTgEAYmJiUFVV5TBNQ0MDLl686HKcTnBwMEwmk8ODiEgpRgg3vlRulFh/hhtWbqQke7j54YcfcOHCBcTGxgIAzGYzLl26hMLCQvs0e/bsQVNTExITE+VuDhGRaFIcZPR8oBIEwaf2e/JehhuGGymJ7paqqamxV2GAXwYCFhUVITIyEpGRkVi4cCEmTZqEmJgYlJaW4oUXXkDfvn2RlJQEALj55psxduxYTJ8+HW+99Rbq6+uRlpaGhx9+mGdKEfk5rXZLGYHWKzf+diC/cOECVq5caf/dH8OdnESHm6+++gr33Xef/ffmsTApKSnIzs7G4cOH8e677+LSpUuIi4vDmDFjsHjxYgQHB9vfs2bNGqSlpWHUqFFo164dJk2ahDfeeEOC1SEikl7LA68RrlDckidnn/paufFkm2l1+8jloYcewu7du+2/82wpaYkONyNGjGhzg+/YscPtPCIjI5GTkyN20UREqjDCQcZV5SYzM1PUe31dtiv+VrloGWwADiiWGu8tRUTkhhHCjSs//PCD22l8rdx4wsjb2BOs3EiL4YaINEOrY26MMKC45fKPHDli/7lr166i3usNrX6uWsIBxdJiuCEicsNoB5kxY8bYTwzxJNw0NTUZbhtoDbulpMVwQ0TkhtEqNwDst7vp0qWL6PeS9BoaGq55jtvdeww3RKQZ7L6QT+sDZfO2bnkmq6fvdeXPf/6zT+/3Z87CDXmP4YaIyA0pTgXXmub18CR4XLx4EWlpaR7Nt+V10MhzHHMjLYYbIiI3jHCQcVW58WTd/vKXv3i8HJvNds1zRgmEcmK3lLQYbojIrTNnzmDz5s2y72wbGxuxYcMGnDt3TtbliGXEg4yYcOMssIhhxO0nNXZLSUvyu4ITkfH07t0bALB582ZMmDBBtuVkZWXBYrHAZDKhurra6TT/+Mc/YDKZ8Nvf/la2drRmxAHFYsKNv11gTw2s3EiL4YaIPPb555+LCjdid84WiwWA61sClJeXY9q0aV7N2xdGPMiICTdGXH+tYbiRFruliMhjau9sL1y40Obrb775pizLVXu9peBL5cYI66917JaSFsMNEXlM7btJu5vfs88+K+nypKS1gKBkuOGAYvdYuZEWww0ReUztna2rmz8quVy9Hqh92V5K3DjT37FyIy2GGyLymNqVG6XmLceytHaAZ7eUtvA6N9JiuCEij6kdbrRQudErNcfc6LXapSR2S0mL4YaIPKb2zlbpcJOVlYURI0a4PHtLz5Q8FVzt740esFtKWjwVnIg8pnblRql5N2u+5YCYK/S6ovYBnmdLaRsrN9Ji5YaIPCbHzlbMPNXqlqqpqVFsWS2Vlpbi8OHDksyL4UbbGG6kxcoNEXlMjsqNp10e69ats1/kz5u2+EKtAcV9+/YFAJw/fx5dunTxuQ0tSRFuDhw4gBMnTkjaLn/FbilpMdwQkcfUCjfffPMNHnnkEZ/a4gu1/4MuKyvzOdzIUblJTEz0aNkcUOweKzfSYrcUkQ4dPnwYI0eORF5enqLLVatbqrS0VJG2uKJWd5icxAQOXudGfs5OBSfvMdwQ6VBSUhI+++wzDBs2TNHlqlW5cTYff6rcSEHNMTc//vgjsrOzfZqHK9XV1YYIBs7+DozwvVMLww2RDrUce6IkOXa23p5mrNaOX6nlamk5UtwV/JlnnvF5Hq2dOXMGERERGD58uOTzVhrDjbQYbojIY1u2bEFhYaHH00tVFdBS5cbb5apxGn1xcTE2bNjgdH6+Vm60cODNyckBAHz55Zcqt8R3UgRI+g8OKCYij1VWVuK2227z+MAmZ7eUWrRUUXFn8ODBAIDPPvvsmteMEG6MhJUbaTHcEJGq9NAtpcZBRsplfvPNN4iMjHR4rry8HOPHj9fFmCd/wHtLSYvhhohkY5RuqZYBQE/dUm2ZMWOGx9Oqvf39AbulpMUxN0TkM1+uY6KHyoEap4LLedNRJd9LnmG3lLQYbogkdPnyZaxbtw6XL19WuymKcrUTlvNMHL11S0lRubHZbFi/fj3Onz/vc3t8bYsvnzldi5UbaTHcEP2fHTt24PXXX/dpHlOmTMEjjzyClJQUiVplfEp18/hCK5WbjIwMPPzwwxgxYoQk8/OUklUFf72aMSs30mK4Ifo/Y8eOxaxZs7Bv3z6v57FlyxYAwKZNm6RqlqwuX76MyZMn4+OPP5Zl/ka8iJ+a4eaDDz4AABw9elSS+fnyXrkqNww3/8Fw4z3R4Wbfvn0YP3484uLiEBAQgM2bNzu8LggCXnzxRcTGxqJjx44YPXo0Tp486TDNxYsXMXnyZJhMJkRERGDatGmq3XWXqLXy8nK1m6CYJUuWICcnB//1X/8ly/zfeustt9McPHjQ7TRqhxspaG1AsRgMN/Jjt5S0RIeb2tpaDBkyBFlZWU5fX7ZsGd544w289dZb2L9/Pzp16oSkpCRcvXrVPs3kyZNx9OhR7Nq1C1u3bsW+fftEjdwnImmcPXvW6XO1tbWSzP+FF16QZD7ONDU14dSpU7LNvyU1KjdSH+yUGlDs6/Zp184/OxRYuZGW6FPBx40bh3Hjxjl9TRAEvPbaa8jIyMCECRMAAP/85z8RHR2NzZs34+GHH8bx48exfft2HDx4ELfddhsAYMWKFXjggQfwyiuvIC4uzofVISJflJWVoWfPnjCZTKiurla7OXbOdvJPPfUUNm7cqPjyjXIquBhKVm4Ybv5DS98BvZH0W3TmzBlYLBaMHj3a/lx4eDgSExORn58PAMjPz0dERIQ92ADA6NGj0a5dO+zfv9/pfG02G6xWq8ODiKTXfCVbsX9jcu+Enc1fqWDTevk8Fbzt+bFbyjvslpKWpOGm+WZ+0dHRDs9HR0fbX7NYLIiKinJ4vX379oiMjHR5M8DMzEyEh4fbH/Hx8VI2m4h8ZPT/MPV+hWJPdOzY0eVr3oQbb9vPcPMfRv+7kpMu6n/p6emorq62P/xpwCeRHqhRuVGSEbql3M2vre4gMVUFX8ONv3K2jTMyMrBixQoVWqN/koabmJgYAL/cXK+lyspK+2sxMTGoqqpyeL2hoQEXL160T9NacHAwTCaTw4OIfKeXA5Da7TRCt5Q7bYUbJSs3P//8s1fv0ztXAfL//b//p3BLjEHScNOrVy/ExMRg9+7d9uesViv2798Ps9kMADCbzbh06RIKCwvt0+zZswdNTU1ITEyUsjlEpBC1w4cRKV25aas7yJtw48sYkvfee8/r9+oV/4akJTrc1NTUoKioCEVFRQB+GURcVFSEsrIyBAQEYNasWfjzn/+Mjz76CMXFxZg6dSri4uIwceJEAMDNN9+MsWPHYvr06Thw4AC+/PJLpKWl4eGHH+aZUkQKk2p8A7ul5F2mEsRWbjZs2NDmtL60Pz093ev3EgFenAr+1Vdf4b777rP/Pnv2bABASkoKVq9ejRdeeAG1tbWYMWMGLl26hLvvvhvbt29HSEiI/T1r1qxBWloaRo0ahXbt2mHSpEl44403JFgdIlIDw428y1RifmIrN9OmTWtzWt6ok9QkOtyMGDGizS9eQEAAFi1ahEWLFrmcJjIyEjk5OWIXTUQaZfSDUcv1mzJlCu6991706NHD63nIMb2v8xNbuXE3rRKnNhv9e0fe08XZUkQkD6nO/PGnyg0ATJ8+XdFlKrH+WjpbSu3Pm/SP4YaIRFP64KP2wa718luf8enNPMRMr0RgkKpy08xZIKqsrMSRI0fcvtfT5fnrNXHIPdHdUkRkHN4eHJSu3PgjLVVuvOmWcvae5st9nDhxAjfeeKPIFhJ5jpUbIhLN37ullF5m88++VCqkHlDsbtq23lNQUODRPIi8xXBDRKIx3Mg/D6UrN1KHm7bG6bgbw6P25036x3BD5Me8PYi0PjgZ/WCklcqNVPNzpq3AIXXlprGx0eP5EXmD4YaIRGPlRv55KF25qaurc/naoUOHPJ6PJ+GGlRuSG8MNkR+TakCx0fm6vhcvXhR9hpXSlRubzebyNTH3e2K3FGkBww0RuDMVy9/OlvJ1/e6//36flql25UYMKbqljP59Ivkx3BCBO1Ox/K1byldff/216Pe0XGcprvbrbhtKHW58qdyIXRZRaww3RPDfnSSvUKzd5bcMAGqvvxgcc0NawHBDBO5Mm3m6Hfw93Fy8eBHnz59XbJlqDGj2dTlKhBteoZhcYbghgvoHT7VwQLFnWq9vWVkZunXr1uYgXCmXqaf7NXnSLcVTwUluDDdEUOYOxnrQMuyI+c/b3yo3zby5x5Q3y/Rm/dXaZmIqN3/729+wb98+l/NQwvvvv48dO3YotjxSBu8tRQT1D55aJAiCy8qOv3dLKb1Mb26/IPYziouLw7lz50S0sO3lugs3n3/+OWbMmOF0WqW296lTpzBlyhRFl0nKYOWGCP67Y2vroNLWNuGp4MouU4nKzWOPPYYnn3xS9HJccdctdfLkScmW5a2Kigq1m0AyYbghgvEPzt7QUrgx6udTVVWF+vp6p69JHW7czSMwMBDTp08XvRxXy3VXuZHqdg9EzjDcEIE702Ytuz2aDz7Oto3S4UbtMVGu1q+0tFTUrQlaOn78OKKjo3HHHXe4XaYSlZuAgABJzj7yNNy0HFTsb5VAkh/DDRH8d2fqyZ2gPQk3cpMj3OTn52PNmjU+zeO+++7DrbfeirKyMtHvXbduHQCgqKjI/ty//vUv5ObmAlC+chMQEIB27Xw/JHh6Eb+2ws3ly5fx5ptv4qeffhK9XCKA4YYIgPqVAbV40vWkhcqNHPO/66678NhjjyEvL8/n5X/xxRc+t+f06dP47W9/ixEjRlyzTD1VbmbOnIkrV664vf2Cu4sUPvvss5g6darHy2W4oZYYbojAHaMzWgo3coZPT26N4G79ysvLfW7H2bNnXS5TqcqNFOHm5MmTePnll0VVblxNu3XrVpfzkPo7yH2AsTDcEEH/O7ampiZcunRJ8nkC7sPNTz/9pJtwU11dfc0F5FxtNzHh4vvvv/e5bb4s3937PSFVtxTwSxWqre9j6wHFYtv6xhtvID4+HidOnHCYpy/0vg8gRww3RND/jm3ChAm47rrr8M0330g2z7YqN80HkgULFiAyMhI5OTmSLbettvji7NmziIiIwJ133unwvBThxmq1+tw+X5YP/PKZFBQU4MqVK/bfXc3PGakqNwBQUlKCxMREl6970i3VlpkzZ+Ls2bP45z//6fU8WvPXrmmjYrghgv7DTXP5fuXKlaLe5+uA4oULFwKA7Fd4leLAs3HjRgDAV1995fC8J+HGHTnucST29gvZ2dkwm8144IEHnE7ryfpItR4HDx5s83V3A4pdqa+vx7vvvuv0NYYbaonhhgj+u2OTakCx3OT8fKSo3EhNEATRy3/77bcBwOnZVp5o3S31/PPPi3q/GJ6OuWntlVdewf/8z/84fU2OMTdZWVk+n1FH6mC4IYL+KzdyEHOdG7nJuTxXXUpaDDdtVVZaj5fxdUCx3OHGm26pnTt3unxN6srN999/j7S0NDz22GM+zZfUwXBDBIYbZ4xWuXHVZk+ed7e+Um8Pbyo37sKNO63DjRxdbc18HXPjjNThpmVFj/sH/WG4IYK6/6VrldHCjVhqfieampokDzdi5yFnuGndLfXzzz/7PE85x9xI9fkLgoDDhw+7vOUGSYfhhgj+G270coViMctzNa3Yg7WWwo0n4c5duHF3mwhBEBSr3LQON8OHD/d5nnJe50aqcP3WW29hyJAhmDRpkiTzI9cYbojgv+HGkx26FsKNmIOLq7aJPV1d7XAjttvGXbhZu3Ztm+93Fm6mTZvmSXNFa90tdfz4cZ/nKWflRqpws3z5cgDAxx9/LMn8yDWGGyI47rz89cwpwPMDuq/b6Fe/+pWo6X0NN5cvX0ZBQYHH07f1vBKk6JYS+xm1DjcA8OCDD4qah6daV26koIdwQ8qRPNwsWLDAPjCt+dG/f3/761evXkVqaiq6dOmCzp07Y9KkSaisrJS6GUSi+GvlpjVPr63i6zYS2+Xha7i5evWqqOW1no8cA4bdvS7lmBtPtp+zyo1UVyxurXVlSqp5+kKJbilv+fM+yVuyfHMHDBiAiooK+6PlTeWee+45fPzxx9iwYQNyc3Nx7tw52f47IPIUw80vlAo3Ykkx5saXaaReX3dXNPa0ctPQ0IDTp08DaDvceDOAVc5wIwiC5IHBm8/I0wDIcKM/snxz27dvj5iYGPuja9euAH65r8s777yD5cuXY+TIkRg6dChWrVqFvLw8lyVjIiX4a7hpXUFxNs5DC+FGijE3vkzjbvqtW7eKauN1113X5uuehpvk5GT06dMHH330UZvhpq6uzm2blKzcCIKgiW4phhvjkuWbe/LkScTFxaF3796YPHkyysrKAACFhYWor6/H6NGj7dP2798fPXr0QH5+vsv52Ww2WK1WhweRlPw13LR1urCcA4qV7pbyZn5ivhPV1dV488033TfOw/m5Cjet39d8UbsVK1bornKjtXDDbiljkfybm5iYiNWrV2P79u3Izs7GmTNncM899+Dy5cuwWCwICgpCRESEw3uio6NhsVhczjMzMxPh4eH2R3x8vNTNJj/HAcW/0OqYG1+7pVo/J3W4AX45zVcqUl/nxlW4ufHGGx2mb/25GL1bytO/e7X3CQw34kn+zR03bhz++7//G4MHD0ZSUhK2bduGS5cu4YMPPvB6nunp6aiurrY/ysvLJWwxkf9WblrTarjxtXLT+v2tb9robP5i19HX/VLrqpmzz8Lb2y+46pb6y1/+4vC7Ut1SjY2Nmqjc6CXcqL18PZL9VPCIiAjcdNNNOHXqFGJiYlBXV3fNjeoqKysRExPjch7BwcEwmUwODyIpMdz8QsyYm4aGBlXa5Y4n4aZl9XjPnj3o3r07zp8/73I+nnwnampqPG6jM62XJ3b5rYOPJ5WbwMBAl8uQ+2wpLYSbtrax2LPN5OTP+yRvyR5uampqUFpaitjYWAwdOhQdOnTA7t277a+XlJSgrKwMZrNZ7qYQucRw8wtPx9w0NTX5FG6U7pZqfSBtXcmoqKjAypUrXc5Hie9E6yqC2OXv37/f5fxcVW7at2/vchl6OxVc6sqNlrqq/Xmf5K327icR5/e//z3Gjx+Pnj174ty5c5g/fz4CAwPxyCOPIDw8HNOmTcPs2bMRGRkJk8mEZ599FmazGXfeeafUTSHyGMON62qBq8qN1P95t8Xbys2XX36JH374waP9S1uVD62Hm/z8fNTW1jo850m3VOvKjZLXudFC5UYv4Ubt5euR5OHmhx9+wCOPPIILFy6gW7duuPvuu1FQUIBu3boBAF599VW0a9cOkyZNgs1mQ1JS0jX/MREpzSjhxpf7AWkt3LQ82Hobbu6++24AwJYtW7xavrOfpdLWIGdPz5Zq1jrYtJ7WVbdUy/Ci5IDixsZGybep1N1SWgo3et4nqUXycLNu3bo2Xw8JCUFWVhaysrKkXjSR17S0I1NL64G17sKNL9vJkxB24MABJCYmAri2W6ktztrbfKE7MbQYbrydv6vKjbvwImflRupt6s33US+VG4Yb8XhvKSIYp3Lji9aVG3fXuZG7cnPXXXfZf/Y13HhyEbu25uPpwU3MbR6WLFnisCxPwo2YypyWKzdyhBsjd0v56z7JFww3RDBOuPGl7a3DTfOdmuUIN54cpFseUHwNN3PnzvX4/c6W7+nBrVu3bh5P6+7sKCNXbrRyKrheuqXUXr4eMdwQwTjhxhetD6gTJkzA2bNnZemWEkvqKxSLnY+n86ypqYHNZhO9rNZnD0ndLeWqctMyZLau3AiCwLOlXLymNH/dJ/mC4YYIDDeA8wPOkSNHVKvctORr5cYb3l7nxNuDrC8Dip3NT2y3FHBt2OHZUs5fU5q/7pN8wXBDBG3tyNTSunLT8nlnz2k93Ph6QPA23HizXZyFm/fee89pWzxtQ8v37Nmzx+l0rcfchIeH238PCQkxfLhp65+alu3zta0lJSX49a9/jVOnTnn1fn/dJ/mC4YYIrNwA4sKNHN0KbfEm3PjaPqnCTXp6ukfLaivcNL/maShsaGjwqM2tw03nzp2Rn5+P/fv3Izg4WHNjbtr629RC5WbVqlW48cYbUVJS4vD8+PHj8e9//1t0+5r56z7JF5KfCk6kRww3xqvc+PrftlThZunSpW7f46xy46otnmhoaPDoPa27oQA4XPBQC5Wb8vJyBAcHIyoqqs3ptBBunnjiCQDA008/7VAtKy0tFd22lvx1n+QLhhsiMNwArsONq2mVvEKxnsKNN7elcDeAWK5w07py09brUhJT+evRowcA99tAS2dL/fzzz6Lb0hZ/3Sf5gt1SRGC4AVwfcOQ4W8qfKjeeWLVqlejKTcvr5LTmTbjx5nVveTPmRo5wo5cBxWovX48Yboig73Aj5dlBSnVLieXN2UpSjrkRs4292S4zZ86ExWKx/+4q3LRsR0ZGhsv5+dIt1ZKWxty4m15LVyiWeh+it32SFjDcEEFb/6WJJVV7tRxu1K7ciJmXt8utrq62/6zUmBs9VW7cdfdpqVtKagw34jHcEEHflZuWO14pb5zZ8nlnz/lTt5SY2zd4u1xPuqXEnC2l9TE3Wgg3clVufPk7dEbtcKVHDDdEME648YWrwMKzpVxfBM8ZOcONp7ReuWlsbBT9vdVTuJGa3vZJWsBwQwSGm+b5ODtLx9V1bhhunJMi3EhxtpQn3wu1xtwYvXIjNb3tk7SA4YYIDDeA8yDj6u7NvnZLieVNYFBrzI03p4K3fp8nA4rdzcto3VLuptfSmBsOKFYfww0RtPVfmlhyhpvWl/FvOa0/DSgWo+Vyxcyj5bgeNbqltB5u/Llyo/by9Yjhhgj+W7lpvd6t5yVXuNFbt5QYLZcr5rPxJNwYZUCxN6eC+3O40ds+SQsYbojAcNP8s5jKjZI7fLWvcyNGy4O2mC4qNSo37sKSFq5Q3IyngpMYDDdEME64Edv21jvw1u93dZBk5cY1b+8mzW6ptumpciP1qeB62ydpAe8tRQTjhBux9FK5USLc+HqGUjMpKjet32fEU8GlDjdGvkKx2pUjPWLlhgj6Dje+tJ1jblwvQ81w0/rUc7nOltLTqeB6OltKanrbJ2kBww0RtLUjE8uXbilWbv7D166gZlJ0S7W+IrLYtrj63FpjtxQHFBsVww0R9F258WUn7O2YGyNexE+qyk3Lg7DUlRsxZ0t58l1QM9xoYUCxXsKN2svXI465IYL/hhtfKjcMN+7n423lxlW48ZTWBxQ3NjaK/g7wbCkSg5UbIhgn3Cg55sZop4LL0S0lpnLTMtC0DjfeVDm0fio4u6U8p7d9khawckME44QbVm60VbnxtlvK1ZgbqQcUu6vcSH1KczNvwoIcA4oZboyL4YYI2tqRiSV3uHH1PqPdfsHfu6WckSvceDrguaWGhoY222Pkbim1l69HDDdE8N/KjS8X8ePZUs7JWbnxlFSVG7l4891htxSJwXBDBP8NN7zOjetlaLFyI/W9peSqzLjj6m7zbdF6uJEzAOltn6QFDDdEYLhp/lmpMTdi6TXcSH0quKf8sXLjzTyl7JYS81mLpXblSI8YbojAcNP8s6fhxpvrlLSkxcqNVN1S3l7npq2zpbwJN1Jc50Yu3gRjd4FN7cqNnOFGb/skLVD1VPCsrCzccMMNCAkJQWJiIg4cOKBmc8iPMdzwbCm1u6VsNpv9Z63cfkEu3t5+oa3vt9ThRuznKGclU2/7JC1QLdysX78es2fPxvz58/H1119jyJAhSEpKQlVVlVpNIj+mpcGDYqk1oFjJcKPEdW601C3lDwOKvbl2j9ThRi/dUgw34qkWbpYvX47p06fj8ccfR0JCAt566y2EhobiH//4h1pNIj/Gyo22L+Knp24pPQ0olusife54e1dwJSs3Yv+u5Kzc6O0fLi1QZcxNXV0dCgsLkZ6ebn+uXbt2GD16NPLz86+Z3mazOZRsrVarIu00um+//RZvvfWW2s3QhNLSUvvPn3/+OWbNmuXzPKWYhyeWLVtm/7m4uFjUcr/99lv7z0uXLsU333zj8PquXbtw+vTpa963atUqXLlyRXxjRWpel9aVjLYsW7YM3bp1w8mTJ0Ut68CBAw7brqKiQtT7m61fv96+XcvKyjx+X8t1/Oyzzxxe2759O6qrqz2ubH/00UfYv3+/2+n0NKD4/fffd/pdbLZixQps3rxZ1Dy//PJL+8/vvfceCgsL7b8XFBTYf167di2OHDnS5rxa/j189913Dt8lX8PJq6++ivXr13s0bffu3fH73//ep+UZgqCCs2fPCgCEvLw8h+fnzJkj3HHHHddMP3/+fAHANY/q6mqlmmxI27dvd7pd+eBDzscNN9wgzJw5U/V28AGhqanJ/nN2drbT/YTabeRD3ONXv/qVwkcScaqrqwVA/uO3Ls6WSk9Px+zZs+2/W61WxMfHq9giY+jduzf+8Ic/qN0MzaitrUVNTQ2io6N9ms/p06fRu3dviVrl2XLq6+thsVi8+rsoLy9HTEwMOnToAACwWCwICAhAu3bt0K1bNwC/dId06dIFx44dQ2hoKDp37gwACAkJweTJk7F27Vp89dVX6NKlCwRBwIABA3DlyhUEBASgtLQUCQkJuPnmm/H9999j4sSJCAoKQrdu3XD8+HE0NTXh9ttvR9++fbF27Vrcdttt+Oqrr9CrVy+HdkZERCA8PByjRo3CmjVr7F00J0+eRH19PTp06OCwHgBQU1ODK1euICwsDGfOnAEA3HDDDbBYLLjpppsQFhaGiooKXLx4EXFxcddsG5vNhvPnz+P6669HaGgoAODo0aO47rrr0NTUhOjoaHTq1AmBgYE4deoUAgICEBER4TCPn3/+GZcuXYLNZsPQoUNx/PhxnD9/HjfddBMqKyvRvn17dOjQAZGRkfjxxx8RHBwMk8kEm82G06dPo1u3bujatavD5x4fHw+LxYLrr78eZWVluOGGG3Du3DnEx8cjODjYXkX4+eefYbPZ0L17dzQ1NeHHH39Ex44dERYWhjvuuAMBAQE4fvw4Pv/8czzxxBNOvx/5+fnYt28fSktLERsbiwsXLiA8PBy1tbUICAjA9ddfj7y8PAiCgF69eiEoKMheuRo0aBDuuecevPfee6irq0O/fv0QFhaGn376CQBw3XXXobi4GFeuXEHHjh0xZMgQBAQE4KeffsLJkyfRp08fXLhwAe3bt0d4eDgA4MyZM4iPj8cPP/xgX+/IyEiEhIS0+T13peU2b+38+fPo0KGDfdnuCIKA77777prvLvCfv9fTp09DEAT06dMHp0+fhtlsRo8ePbB+/XoMHDgQP/74I9q3b4+xY8diw4YNCAsLQ3BwsMfrExsb6/G0RhYgCMoPMKirq0NoaCg+/PBDTJw40f58SkoKLl26hC1btrT5fqvVivDwcFRXVzv9QhIREZH2KHX8VmU0WVBQEIYOHYrdu3fbn2tqasLu3bthNpvVaBIREREZhGrdUrNnz0ZKSgpuu+023HHHHXjttddQW1uLxx9/XK0mERERkQGoFm4eeugh/Pjjj3jxxRdhsVhwyy23YPv27T6PdyAiIiL/psqYG19xzA0REZH+GHrMDREREZFcGG6IiIjIUBhuiIiIyFAYboiIiMhQGG6IiIjIUBhuiIiIyFAYboiIiMhQGG6IiIjIUBhuiIiIyFBUu/2CL5ovqmy1WlVuCREREXmq+bgt980RdBluLly4AACIj49XuSVEREQk1oULFxAeHi7b/HUZbiIjIwEAZWVlsm4cf2C1WhEfH4/y8nLep8sH3I7S4baUDrelNLgdpVNdXY0ePXrYj+Ny0WW4adful6FC4eHh/KJJxGQycVtKgNtROtyW0uG2lAa3o3Saj+OyzV/WuRMREREpjOGGiIiIDEWX4SY4OBjz589HcHCw2k3RPW5LaXA7SofbUjrcltLgdpSOUtsyQJD7fCwiIiIiBemyckNERETkCsMNERERGQrDDRERERkKww0REREZimbCTVZWFm644QaEhIQgMTERBw4caHP61157Df369UPHjh0RHx+P5557DlevXrW/vmDBAgQEBDg8+vfvL/dqqE7Mdqyvr8eiRYvQp08fhISEYMiQIdi+fbvDNNnZ2Rg8eLD94lVmsxmffPKJ3Kuhun379mH8+PGIi4tDQEAANm/e7PY9e/fuxa233org4GD07dsXq1ev9nmeeifHdmxsbMSf/vQn9OrVCx07dkSfPn2wePFi2e9Vozax27KiogKPPvoobrrpJrRr1w6zZs1yOt2lS5eQmpqK2NhYBAcH46abbsK2bdukXwENEbstN27ciPvvvx/dunWz7wd37NjhcvqlS5ciICDA5TY3CrHb8YsvvsCwYcPQpUsXdOzYEf3798err77qME1mZiZuv/12hIWFISoqChMnTkRJSYnotmki3Kxfvx6zZ8/G/Pnz8fXXX2PIkCFISkpCVVWV0+lzcnIwb948zJ8/H8ePH8c777yD9evX4w9/+IPDdAMGDEBFRYX98cUXXyixOqoRux0zMjLw9ttvY8WKFTh27Bieeuop/OY3v8GhQ4fs03Tv3h1Lly5FYWEhvvrqK4wcORITJkzA0aNHlVotVdTW1mLIkCHIysryaPozZ84gOTkZ9913H4qKijBr1iw8+eSTDjtAsfM0Ajm248svv4zs7Gy8+eabOH78OF5++WUsW7YMK1askGs1NEHstrTZbOjWrRsyMjIwZMgQp9PU1dXh/vvvx3fffYcPP/wQJSUl+Nvf/obrr79eyqZrjthtuW/fPtx///3Ytm0bCgsLcd9992H8+PEO+8pmBw8exNtvv43BgwdL3WzNEbsdO3XqhLS0NOzbtw/Hjx9HRkYGMjIy8Ne//tU+TW5uLlJTU1FQUIBdu3ahvr4eY8aMQW1trbjGCRpwxx13CKmpqfbfGxsbhbi4OCEzM9Pp9KmpqcLIkSMdnps9e7YwbNgw++/z588XhgwZIkt7tUrsdoyNjRXefPNNh+cefPBBYfLkyW0u57rrrhP+/ve/+95gnQAgbNq0qc1pXnjhBWHAgAEOzz300ENCUlKS1/M0Gqm2Y3JysvDEE084TOPJ99ZIxH5/hg8fLsycOfOa57Ozs4XevXsLdXV10jVOZ7z9W0xISBAWLlzo8Nzly5eFG2+8Udi1a5fLbW5U3m7H3/zmN8Jjjz3m8vWqqioBgJCbmytqvqpXburq6lBYWIjRo0fbn2vXrh1Gjx6N/Px8p++56667UFhYaO9yOX36NLZt24YHHnjAYbqTJ08iLi4OvXv3xuTJk1FWVibfiqjMm+1os9kQEhLi8FzHjh1dVrgaGxuxbt061NbWwmw2S9d4A8jPz3fY9gCQlJTkctuTc55sx7vuugu7d+/GiRMnAADffPMNvvjiC4wbN07RthrBRx99BLPZjNTUVERHR2PgwIF46aWX0NjYqHbTNK2pqQmXL1++5uaPqampSE5OvuY7TM4dOnQIeXl5GD58uMtpqqurAUD0jTZVv3Hm+fPn0djYiOjoaIfno6Oj8e233zp9z6OPPorz58/j7rvvhiAIaGhowFNPPeXQLZWYmIjVq1ejX79+qKiowMKFC3HPPffgyJEjCAsLk3Wd1ODNdkxKSsLy5ctx7733ok+fPti9ezc2btx4zY6tuLgYZrMZV69eRefOnbFp0yYkJCTIti56ZLFYnG57q9WKn3/+GR07dlSpZfriyXacN28erFYr+vfvj8DAQDQ2NmLJkiWYPHmySq3Wr9OnT2PPnj2YPHkytm3bhlOnTuGZZ55BfX095s+fr3bzNOuVV15BTU0Nfve739mfW7duHb7++mscPHhQxZbpQ/fu3fHjjz+ioaEBCxYswJNPPul0uqamJsyaNQvDhg3DwIEDRS1D9XDjjb179+Kll17CypUrkZiYiFOnTmHmzJlYvHgx/vSnPwGAw39xgwcPRmJiInr27IkPPvgA06ZNU6vpmvL6669j+vTp6N+/PwICAtCnTx88/vjj+Mc//uEwXb9+/VBUVITq6mp8+OGHSElJQW5uLgMOqeKDDz7AmjVrkJOTgwEDBtjH5sTFxSElJUXt5ulKU1MToqKi8Ne//hWBgYEYOnQozp49i//93/9luHEhJycHCxcuxJYtWxAVFQUAKC8vx8yZM7Fr165rquF0rc8//xw1NTUoKCjAvHnz0LdvXzzyyCPXTJeamoojR454NV5W9XDTtWtXBAYGorKy0uH5yspKxMTEOH3Pn/70J0yZMsWe9gYNGoTa2lrMmDEDf/zjH53eSj0iIgI33XQTTp06Jf1KaIA327Fbt27YvHkzrl69igsXLiAuLg7z5s1D7969HaYLCgpC3759AQBDhw7FwYMH8frrr+Ptt9+WZ2V0KCYmxum2N5lMrNqI4Ml2nDNnDubNm4eHH34YwC9//99//z0yMzMZbkSKjY1Fhw4dEBgYaH/u5ptvhsViQV1dHYKCglRsnfasW7cOTz75JDZs2ODQ9VRYWIiqqirceuut9ucaGxuxb98+vPnmm7DZbA7b2N/16tULwC9/u5WVlViwYME14SYtLQ1bt27Fvn370L17d9HLUH3MTVBQEIYOHYrdu3fbn2tqasLu3btdjuu4cuXKNQGm+YsjuDgdtKamBqWlpYiNjZWo5drizXZsFhISguuvvx4NDQ3417/+hQkTJrQ5fVNTE2w2myTtNgqz2eyw7QFg165dHJskkifb0dXff1NTkyJtNJJhw4bh1KlTDtvuxIkTiI2NZbBpZe3atXj88cexdu1aJCcnO7w2atQoFBcXo6ioyP647bbbMHnyZBQVFTHYtKH18UQQBKSlpWHTpk3Ys2ePPQiJJnposwzWrVsnBAcHC6tXrxaOHTsmzJgxQ4iIiBAsFosgCIIwZcoUYd68efbp58+fL4SFhQlr164VTp8+LezcuVPo06eP8Lvf/c4+zfPPPy/s3btXOHPmjPDll18Ko0ePFrp27SpUVVUpvn5KEbsdCwoKhH/9619CaWmpsG/fPmHkyJFCr169hJ9++sk+zbx584Tc3FzhzJkzwuHDh4V58+YJAQEBws6dO5VePUVdvnxZOHTokHDo0CEBgLB8+XLh0KFDwvfffy8Iwi/bZcqUKfbpT58+LYSGhgpz5swRjh8/LmRlZQmBgYHC9u3bPZ6nEcmxHVNSUoTrr79e2Lp1q3DmzBlh48aNQteuXYUXXnhB8fVTkthtKQiCffqhQ4cKjz76qHDo0CHh6NGj9tfLysqEsLAwIS0tTSgpKRG2bt0qREVFCX/+858VXTelid2Wa9asEdq3by9kZWUJFRUV9selS5dcLsMfzpYSux3ffPNN4aOPPhJOnDghnDhxQvj73/8uhIWFCX/84x/t0zz99NNCeHi4sHfvXodtfeXKFVFt00S4EQRBWLFihdCjRw8hKChIuOOOO4SCggL7a8OHDxdSUlLsv9fX1wsLFiwQ+vTpI4SEhAjx8fHCM88843BQfuihh4TY2FghKChIuP7664WHHnpIOHXqlIJrpA4x23Hv3r3CzTffLAQHBwtdunQRpkyZIpw9e9Zhfk888YTQs2dPISgoSOjWrZswatQowwcbQRCEzz77TABwzaN5+6WkpAjDhw+/5j233HKLEBQUJPTu3VtYtWqVqHkakRzb0Wq1CjNnzhR69OghhISECL179xb++Mc/CjabTZmVUok329LZ9D179nSYJi8vT0hMTBSCg4OF3r17C0uWLBEaGhqUWSmViN2Ww4cPF/236w/hRux2fOONN4QBAwYIoaGhgslkEn71q18JK1euFBobG+3TOJsfgGv2A+4E/N/MiIiIiAxB9TE3RERERFJiuCEiIiJDYbghIiIiQ2G4ISIiIkNhuCEiIiJDYbghIiIiQ2G4ISIiIkNhuCEiIiJDYbghIiIiQ2G4ISIiIkNhuCEiIiJDYbghIiIiQ/n/lNmo7ugVVZQAAAAASUVORK5CYII=", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "plt.plot(\n", - " frame_array[:, non_zero_columns].sum(axis=1).reshape(-1, 1),\n", - " color=\"black\",\n", - ")\n", - "# Retrieve the current x-tick positions\n", - "current_ticks = plt.gca().get_xticks()\n", - "\n", - "# Calculate new labels based on the range 0.8 to 1.3\n", - "# Map the current tick range (0 to 900) to the new label range (0.8 to 1.3)\n", - "new_labels = np.linspace(\n", - " mobility_values_df[\"mobility_values\"].min(),\n", - " mobility_values_df[\"mobility_values\"].max(),\n", - " len(current_ticks),\n", - ")\n", - "\n", - "# Apply the new labels to the x-axis\n", - "plt.xticks(current_ticks, labels=np.round(new_labels, 2))" - ] - }, - { - "cell_type": "code", - "execution_count": 81, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[,\n", - " ,\n", - " ]" - ] - }, - "execution_count": 81, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "([,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ],\n", - " [Text(-200.0, 0, '0.85'),\n", - " Text(0.0, 0, '0.93'),\n", - " Text(200.0, 0, '1.01'),\n", - " Text(400.0, 0, '1.08'),\n", - " Text(600.0, 0, '1.16'),\n", - " Text(800.0, 0, '1.24'),\n", - " Text(1000.0, 0, '1.32')])" - ] - }, - "execution_count": 81, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "plt.plot(candidate_act)\n", - "# Retrieve the current x-tick positions\n", - "current_ticks = plt.gca().get_xticks()\n", - "\n", - "# Calculate new labels based on the range 0.8 to 1.3\n", - "# Map the current tick range (0 to 900) to the new label range (0.8 to 1.3)\n", - "new_labels = np.linspace(\n", - " mobility_values_df[\"mobility_values\"].min(),\n", - " mobility_values_df[\"mobility_values\"].max(),\n", - " len(current_ticks),\n", - ")\n", - "\n", - "# Apply the new labels to the x-axis\n", - "plt.xticks(current_ticks, labels=np.round(new_labels, 2))" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from utils.plot import plot_im_or_mz_int_reduced\n", - "\n", - "plot_im_or_mz_int_reduced(df, group_by=\"mz_values\")" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%autoreload 2\n", - "from utils.plot import plot_im_mz_int\n", - "\n", - "df = data[\n", - " {\n", - " \"frame_indices\": 1674,\n", - " # # \"scan_indices\": slice(300, 800, 10),\n", - " \"mz_values\": slice(1003.5, 1005.5),\n", - " # \"mobility_values\": [0.9, 1.0],\n", - " # # \"intensity_values\": 50,\n", - " }\n", - "]\n", - "plot_im_mz_int(df)" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-12 10:50:36,994 - utils.plot - INFO - Dictionary entry Modified sequence Charge 1/K0 RT_search_left \\\n", - "25495 _ESILQRPLSLPSLHVFGDTDK_ 3 0.939356 16.313 \n", - "\n", - " RT_search_right RT_search_center Retention time \\\n", - "25495 16.492 16.388 16.388 \n", - "\n", - " Number of data points Number of scans \n", - "25495 532 13 \n", - "2024-09-12 10:50:37,004 - utils.plot - INFO - Experiment result: Modified sequence Charge Calibrated retention time start \\\n", - "25495 _ESILQRPLSLPSLHVFGDTDK_ 3 16.314 \n", - "\n", - " Calibrated retention time finish 1/K0 1/K0 length \\\n", - "25495 16.491 0.939356 0.066442 \n", - "\n", - " Number of data points Retention length \n", - "25495 532 0.17627 , bounding box available: [16.314, 16.491, 0.1769999999999996, 0.906134625, 0.9725765749999999, 0.06644195]\n", - "2024-09-12 10:50:37,009 - postprocessing.ims_3d - DEBUG - No reference RT range given, using dictionary entries: 16.388, (16.313, 16.492).\n", - "2024-09-12 10:50:37,011 - postprocessing.ims_3d - DEBUG - No reference IM range given, using dictionary entries: 0.9393555976519395, (0.8993555976519395, 0.9793555976519396).\n", - "2024-09-12 10:50:37,012 - utils.plot - INFO - Reference entry: [16.388, 0.9393555976519395]\n", - "2024-09-12 10:50:37,017 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=398)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=455)\n", - " 4\tLOAD_ATTR(arg=1, lineno=455)\n", - " 6\tLOAD_ATTR(arg=2, lineno=455)\n", - " 8\tLOAD_METHOD(arg=3, lineno=455)\n", - " 10\tLOAD_GLOBAL(arg=0, lineno=455)\n", - " 12\tLOAD_ATTR(arg=4, lineno=455)\n", - " 14\tLOAD_ATTR(arg=5, lineno=455)\n", - " 16\tCALL_METHOD(arg=1, lineno=455)\n", - " 18\tSTORE_FAST(arg=2, lineno=455)\n", - " 20\tLOAD_FAST(arg=2, lineno=456)\n", - " 22\tLOAD_METHOD(arg=6, lineno=456)\n", - " 24\tLOAD_CONST(arg=1, lineno=456)\n", - " 26\tCALL_METHOD(arg=1, lineno=456)\n", - " 28\tPOP_TOP(arg=None, lineno=456)\n", - " 30\tLOAD_GLOBAL(arg=0, lineno=457)\n", - " 32\tLOAD_ATTR(arg=1, lineno=457)\n", - " 34\tLOAD_ATTR(arg=2, lineno=457)\n", - " 36\tLOAD_METHOD(arg=3, lineno=457)\n", - " 38\tLOAD_GLOBAL(arg=0, lineno=457)\n", - " 40\tLOAD_ATTR(arg=4, lineno=457)\n", - " 42\tLOAD_ATTR(arg=5, lineno=457)\n", - " 44\tCALL_METHOD(arg=1, lineno=457)\n", - " 46\tSTORE_FAST(arg=3, lineno=457)\n", - " 48\tLOAD_FAST(arg=3, lineno=458)\n", - " 50\tLOAD_METHOD(arg=6, lineno=458)\n", - " 52\tLOAD_FAST(arg=0, lineno=458)\n", - " 54\tLOAD_ATTR(arg=7, lineno=458)\n", - " 56\tLOAD_CONST(arg=2, lineno=458)\n", - " 58\tBINARY_SUBSCR(arg=None, lineno=458)\n", - " 60\tCALL_METHOD(arg=1, lineno=458)\n", - " 62\tPOP_TOP(arg=None, lineno=458)\n", - " 64\tLOAD_GLOBAL(arg=8, lineno=459)\n", - " 66\tLOAD_METHOD(arg=5, lineno=459)\n", - " 68\tLOAD_FAST(arg=0, lineno=459)\n", - " 70\tLOAD_ATTR(arg=7, lineno=459)\n", - " 72\tLOAD_CONST(arg=2, lineno=459)\n", - " 74\tBINARY_SUBSCR(arg=None, lineno=459)\n", - " 76\tCALL_METHOD(arg=1, lineno=459)\n", - " 78\tSTORE_FAST(arg=4, lineno=459)\n", - " 80\tLOAD_CONST(arg=1, lineno=461)\n", - " 82\tSTORE_FAST(arg=5, lineno=461)\n", - " 84\tLOAD_FAST(arg=5, lineno=462)\n", - " 86\tLOAD_GLOBAL(arg=9, lineno=462)\n", - " 88\tLOAD_FAST(arg=1, lineno=462)\n", - " 90\tCALL_FUNCTION(arg=1, lineno=462)\n", - " 92\tCOMPARE_OP(arg=0, lineno=462)\n", - " 94\tPOP_JUMP_IF_FALSE(arg=118, lineno=462)\n", - "> 96\tLOAD_GLOBAL(arg=9, lineno=468)\n", - " 98\tLOAD_FAST(arg=2, lineno=468)\n", - " 100\tCALL_FUNCTION(arg=1, lineno=468)\n", - " 102\tSTORE_FAST(arg=6, lineno=468)\n", - " 104\tLOAD_GLOBAL(arg=9, lineno=469)\n", - " 106\tLOAD_GLOBAL(arg=10, lineno=469)\n", - " 108\tLOAD_FAST(arg=1, lineno=469)\n", - " 110\tLOAD_FAST(arg=5, lineno=469)\n", - " 112\tLOAD_CONST(arg=1, lineno=469)\n", - " 114\tBUILD_TUPLE(arg=2, lineno=469)\n", - " 116\tBINARY_SUBSCR(arg=None, lineno=469)\n", - " 118\tLOAD_FAST(arg=1, lineno=469)\n", - " 120\tLOAD_FAST(arg=5, lineno=469)\n", - " 122\tLOAD_CONST(arg=2, lineno=469)\n", - " 124\tBUILD_TUPLE(arg=2, lineno=469)\n", - " 126\tBINARY_SUBSCR(arg=None, lineno=469)\n", - " 128\tLOAD_FAST(arg=1, lineno=469)\n", - " 130\tLOAD_FAST(arg=5, lineno=469)\n", - " 132\tLOAD_CONST(arg=3, lineno=469)\n", - " 134\tBUILD_TUPLE(arg=2, lineno=469)\n", - " 136\tBINARY_SUBSCR(arg=None, lineno=469)\n", - " 138\tCALL_FUNCTION(arg=3, lineno=469)\n", - " 140\tCALL_FUNCTION(arg=1, lineno=469)\n", - " 142\tLOAD_FAST(arg=6, lineno=469)\n", - " 144\tBINARY_MULTIPLY(arg=None, lineno=469)\n", - " 146\tLOAD_CONST(arg=3, lineno=469)\n", - " 148\tBINARY_ADD(arg=None, lineno=469)\n", - " 150\tSTORE_FAST(arg=7, lineno=469)\n", - " 152\tLOAD_FAST(arg=7, lineno=470)\n", - " 154\tLOAD_GLOBAL(arg=8, lineno=470)\n", - " 156\tLOAD_METHOD(arg=11, lineno=470)\n", - " 158\tLOAD_FAST(arg=7, lineno=470)\n", - " 160\tLOAD_GLOBAL(arg=12, lineno=470)\n", - " 162\tLOAD_FAST(arg=6, lineno=470)\n", - " 164\tLOAD_CONST(arg=2, lineno=470)\n", - " 166\tCALL_FUNCTION(arg=2, lineno=470)\n", - " 168\tBINARY_TRUE_DIVIDE(arg=None, lineno=470)\n", - " 170\tCALL_METHOD(arg=1, lineno=470)\n", - " 172\tBINARY_MULTIPLY(arg=None, lineno=470)\n", - " 174\tLOAD_FAST(arg=4, lineno=470)\n", - " 176\tLOAD_FAST(arg=6, lineno=470)\n", - " 178\tBINARY_ADD(arg=None, lineno=470)\n", - " 180\tCOMPARE_OP(arg=4, lineno=470)\n", - " 182\tPOP_JUMP_IF_FALSE(arg=94, lineno=470)\n", - " 184\tJUMP_FORWARD(arg=24, lineno=471)\n", - "> 186\tLOAD_GLOBAL(arg=13, lineno=477)\n", - " 188\tLOAD_FAST(arg=2, lineno=477)\n", - " 190\tLOAD_FAST(arg=3, lineno=477)\n", - " 192\tLOAD_FAST(arg=0, lineno=477)\n", - " 194\tLOAD_FAST(arg=5, lineno=477)\n", - " 196\tBINARY_SUBSCR(arg=None, lineno=477)\n", - " 198\tLOAD_FAST(arg=1, lineno=477)\n", - " 200\tLOAD_FAST(arg=5, lineno=477)\n", - " 202\tBINARY_SUBSCR(arg=None, lineno=477)\n", - " 204\tCALL_FUNCTION(arg=4, lineno=477)\n", - " 206\tUNPACK_SEQUENCE(arg=3, lineno=477)\n", - " 208\tSTORE_FAST(arg=2, lineno=477)\n", - " 210\tSTORE_FAST(arg=3, lineno=477)\n", - " 212\tSTORE_FAST(arg=4, lineno=477)\n", - " 214\tLOAD_FAST(arg=5, lineno=479)\n", - " 216\tLOAD_CONST(arg=2, lineno=479)\n", - " 218\tINPLACE_ADD(arg=None, lineno=479)\n", - " 220\tSTORE_FAST(arg=5, lineno=479)\n", - " 222\tLOAD_FAST(arg=5, lineno=462)\n", - " 224\tLOAD_GLOBAL(arg=9, lineno=462)\n", - " 226\tLOAD_FAST(arg=1, lineno=462)\n", - " 228\tCALL_FUNCTION(arg=1, lineno=462)\n", - " 230\tCOMPARE_OP(arg=0, lineno=462)\n", - " 232\tPOP_JUMP_IF_TRUE(arg=49, lineno=462)\n", - "> 234\tLOAD_GLOBAL(arg=14, lineno=482)\n", - " 236\tLOAD_FAST(arg=2, lineno=482)\n", - " 238\tLOAD_FAST(arg=3, lineno=482)\n", - " 240\tCALL_FUNCTION(arg=2, lineno=482)\n", - " 242\tUNPACK_SEQUENCE(arg=2, lineno=482)\n", - " 244\tSTORE_FAST(arg=2, lineno=482)\n", - " 246\tSTORE_FAST(arg=3, lineno=482)\n", - " 248\tLOAD_FAST(arg=5, lineno=485)\n", - " 250\tLOAD_GLOBAL(arg=9, lineno=485)\n", - " 252\tLOAD_FAST(arg=1, lineno=485)\n", - " 254\tCALL_FUNCTION(arg=1, lineno=485)\n", - " 256\tCOMPARE_OP(arg=2, lineno=485)\n", - " 258\tPOP_JUMP_IF_FALSE(arg=150, lineno=485)\n", - " 260\tLOAD_GLOBAL(arg=9, lineno=485)\n", - " 262\tLOAD_FAST(arg=2, lineno=485)\n", - " 264\tCALL_FUNCTION(arg=1, lineno=485)\n", - " 266\tLOAD_CONST(arg=2, lineno=485)\n", - " 268\tCOMPARE_OP(arg=2, lineno=485)\n", - " 270\tPOP_JUMP_IF_FALSE(arg=150, lineno=485)\n", - " 272\tLOAD_GLOBAL(arg=8, lineno=486)\n", - " 274\tLOAD_METHOD(arg=15, lineno=486)\n", - " 276\tLOAD_FAST(arg=2, lineno=486)\n", - " 278\tLOAD_CONST(arg=1, lineno=486)\n", - " 280\tBINARY_SUBSCR(arg=None, lineno=486)\n", - " 282\tLOAD_FAST(arg=3, lineno=486)\n", - " 284\tLOAD_CONST(arg=1, lineno=486)\n", - " 286\tBINARY_SUBSCR(arg=None, lineno=486)\n", - " 288\tBUILD_LIST(arg=2, lineno=486)\n", - " 290\tCALL_METHOD(arg=1, lineno=486)\n", - " 292\tLOAD_CONST(arg=4, lineno=486)\n", - " 294\tBUILD_TUPLE(arg=2, lineno=486)\n", - " 296\tRETURN_VALUE(arg=None, lineno=486)\n", - "> 298\tLOAD_GLOBAL(arg=16, lineno=490)\n", - " 300\tLOAD_FAST(arg=2, lineno=490)\n", - " 302\tLOAD_FAST(arg=3, lineno=490)\n", - " 304\tLOAD_FAST(arg=0, lineno=490)\n", - " 306\tLOAD_FAST(arg=5, lineno=490)\n", - " 308\tLOAD_CONST(arg=5, lineno=490)\n", - " 310\tBUILD_SLICE(arg=2, lineno=490)\n", - " 312\tBINARY_SUBSCR(arg=None, lineno=490)\n", - " 314\tLOAD_FAST(arg=1, lineno=490)\n", - " 316\tLOAD_FAST(arg=5, lineno=490)\n", - " 318\tLOAD_CONST(arg=5, lineno=490)\n", - " 320\tBUILD_SLICE(arg=2, lineno=490)\n", - " 322\tBINARY_SUBSCR(arg=None, lineno=490)\n", - " 324\tCALL_FUNCTION(arg=4, lineno=490)\n", - " 326\tSTORE_FAST(arg=8, lineno=490)\n", - " 328\tLOAD_GLOBAL(arg=17, lineno=491)\n", - " 330\tLOAD_FAST(arg=8, lineno=491)\n", - " 332\tCALL_FUNCTION(arg=1, lineno=491)\n", - " 334\tLOAD_CONST(arg=6, lineno=491)\n", - " 336\tBUILD_TUPLE(arg=2, lineno=491)\n", - " 338\tRETURN_VALUE(arg=None, lineno=491)\n", - "2024-09-12 10:50:37,018 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:37,019 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:37,020 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:37,020 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=398)\n", - "2024-09-12 10:50:37,021 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,022 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=455)\n", - "2024-09-12 10:50:37,022 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,023 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=455)\n", - "2024-09-12 10:50:37,024 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:37,024 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_ATTR(arg=2, lineno=455)\n", - "2024-09-12 10:50:37,025 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-09-12 10:50:37,026 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=3, lineno=455)\n", - "2024-09-12 10:50:37,026 - numba.core.byteflow - DEBUG - stack ['$6load_attr.2']\n", - "2024-09-12 10:50:37,027 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=0, lineno=455)\n", - "2024-09-12 10:50:37,028 - numba.core.byteflow - DEBUG - stack ['$8load_method.3']\n", - "2024-09-12 10:50:37,028 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=4, lineno=455)\n", - "2024-09-12 10:50:37,029 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$10load_global.4']\n", - "2024-09-12 10:50:37,030 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_ATTR(arg=5, lineno=455)\n", - "2024-09-12 10:50:37,030 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$12load_attr.5']\n", - "2024-09-12 10:50:37,031 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=CALL_METHOD(arg=1, lineno=455)\n", - "2024-09-12 10:50:37,031 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$14load_attr.6']\n", - "2024-09-12 10:50:37,032 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=STORE_FAST(arg=2, lineno=455)\n", - "2024-09-12 10:50:37,033 - numba.core.byteflow - DEBUG - stack ['$16call_method.7']\n", - "2024-09-12 10:50:37,033 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=2, lineno=456)\n", - "2024-09-12 10:50:37,034 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,035 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_METHOD(arg=6, lineno=456)\n", - "2024-09-12 10:50:37,035 - numba.core.byteflow - DEBUG - stack ['$starts20.8']\n", - "2024-09-12 10:50:37,036 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_CONST(arg=1, lineno=456)\n", - "2024-09-12 10:50:37,037 - numba.core.byteflow - DEBUG - stack ['$22load_method.9']\n", - "2024-09-12 10:50:37,037 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=CALL_METHOD(arg=1, lineno=456)\n", - "2024-09-12 10:50:37,038 - numba.core.byteflow - DEBUG - stack ['$22load_method.9', '$const24.10']\n", - "2024-09-12 10:50:37,039 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=POP_TOP(arg=None, lineno=456)\n", - "2024-09-12 10:50:37,040 - numba.core.byteflow - DEBUG - stack ['$26call_method.11']\n", - "2024-09-12 10:50:37,050 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_GLOBAL(arg=0, lineno=457)\n", - "2024-09-12 10:50:37,050 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,051 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_ATTR(arg=1, lineno=457)\n", - "2024-09-12 10:50:37,052 - numba.core.byteflow - DEBUG - stack ['$30load_global.12']\n", - "2024-09-12 10:50:37,053 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_ATTR(arg=2, lineno=457)\n", - "2024-09-12 10:50:37,055 - numba.core.byteflow - DEBUG - stack ['$32load_attr.13']\n", - "2024-09-12 10:50:37,055 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_METHOD(arg=3, lineno=457)\n", - "2024-09-12 10:50:37,056 - numba.core.byteflow - DEBUG - stack ['$34load_attr.14']\n", - "2024-09-12 10:50:37,057 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_GLOBAL(arg=0, lineno=457)\n", - "2024-09-12 10:50:37,058 - numba.core.byteflow - DEBUG - stack ['$36load_method.15']\n", - "2024-09-12 10:50:37,059 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_ATTR(arg=4, lineno=457)\n", - "2024-09-12 10:50:37,059 - numba.core.byteflow - DEBUG - stack ['$36load_method.15', '$38load_global.16']\n", - "2024-09-12 10:50:37,060 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_ATTR(arg=5, lineno=457)\n", - "2024-09-12 10:50:37,061 - numba.core.byteflow - DEBUG - stack ['$36load_method.15', '$40load_attr.17']\n", - "2024-09-12 10:50:37,062 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=CALL_METHOD(arg=1, lineno=457)\n", - "2024-09-12 10:50:37,063 - numba.core.byteflow - DEBUG - stack ['$36load_method.15', '$42load_attr.18']\n", - "2024-09-12 10:50:37,063 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=STORE_FAST(arg=3, lineno=457)\n", - "2024-09-12 10:50:37,064 - numba.core.byteflow - DEBUG - stack ['$44call_method.19']\n", - "2024-09-12 10:50:37,065 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_FAST(arg=3, lineno=458)\n", - "2024-09-12 10:50:37,066 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,066 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_METHOD(arg=6, lineno=458)\n", - "2024-09-12 10:50:37,067 - numba.core.byteflow - DEBUG - stack ['$stops48.20']\n", - "2024-09-12 10:50:37,068 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=LOAD_FAST(arg=0, lineno=458)\n", - "2024-09-12 10:50:37,069 - numba.core.byteflow - DEBUG - stack ['$50load_method.21']\n", - "2024-09-12 10:50:37,070 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=LOAD_ATTR(arg=7, lineno=458)\n", - "2024-09-12 10:50:37,071 - numba.core.byteflow - DEBUG - stack ['$50load_method.21', '$coords52.22']\n", - "2024-09-12 10:50:37,071 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_CONST(arg=2, lineno=458)\n", - "2024-09-12 10:50:37,072 - numba.core.byteflow - DEBUG - stack ['$50load_method.21', '$54load_attr.23']\n", - "2024-09-12 10:50:37,073 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=BINARY_SUBSCR(arg=None, lineno=458)\n", - "2024-09-12 10:50:37,074 - numba.core.byteflow - DEBUG - stack ['$50load_method.21', '$54load_attr.23', '$const56.24']\n", - "2024-09-12 10:50:37,075 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=CALL_METHOD(arg=1, lineno=458)\n", - "2024-09-12 10:50:37,076 - numba.core.byteflow - DEBUG - stack ['$50load_method.21', '$58binary_subscr.25']\n", - "2024-09-12 10:50:37,076 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=POP_TOP(arg=None, lineno=458)\n", - "2024-09-12 10:50:37,077 - numba.core.byteflow - DEBUG - stack ['$60call_method.26']\n", - "2024-09-12 10:50:37,078 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_GLOBAL(arg=8, lineno=459)\n", - "2024-09-12 10:50:37,079 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,080 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_METHOD(arg=5, lineno=459)\n", - "2024-09-12 10:50:37,080 - numba.core.byteflow - DEBUG - stack ['$64load_global.27']\n", - "2024-09-12 10:50:37,081 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_FAST(arg=0, lineno=459)\n", - "2024-09-12 10:50:37,082 - numba.core.byteflow - DEBUG - stack ['$66load_method.28']\n", - "2024-09-12 10:50:37,083 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=LOAD_ATTR(arg=7, lineno=459)\n", - "2024-09-12 10:50:37,084 - numba.core.byteflow - DEBUG - stack ['$66load_method.28', '$coords68.29']\n", - "2024-09-12 10:50:37,084 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=LOAD_CONST(arg=2, lineno=459)\n", - "2024-09-12 10:50:37,085 - numba.core.byteflow - DEBUG - stack ['$66load_method.28', '$70load_attr.30']\n", - "2024-09-12 10:50:37,086 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=BINARY_SUBSCR(arg=None, lineno=459)\n", - "2024-09-12 10:50:37,087 - numba.core.byteflow - DEBUG - stack ['$66load_method.28', '$70load_attr.30', '$const72.31']\n", - "2024-09-12 10:50:37,088 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=CALL_METHOD(arg=1, lineno=459)\n", - "2024-09-12 10:50:37,088 - numba.core.byteflow - DEBUG - stack ['$66load_method.28', '$74binary_subscr.32']\n", - "2024-09-12 10:50:37,089 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=STORE_FAST(arg=4, lineno=459)\n", - "2024-09-12 10:50:37,090 - numba.core.byteflow - DEBUG - stack ['$76call_method.33']\n", - "2024-09-12 10:50:37,091 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_CONST(arg=1, lineno=461)\n", - "2024-09-12 10:50:37,092 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,092 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=STORE_FAST(arg=5, lineno=461)\n", - "2024-09-12 10:50:37,093 - numba.core.byteflow - DEBUG - stack ['$const80.34']\n", - "2024-09-12 10:50:37,094 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=LOAD_FAST(arg=5, lineno=462)\n", - "2024-09-12 10:50:37,095 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,096 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_GLOBAL(arg=9, lineno=462)\n", - "2024-09-12 10:50:37,096 - numba.core.byteflow - DEBUG - stack ['$i84.35']\n", - "2024-09-12 10:50:37,097 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_FAST(arg=1, lineno=462)\n", - "2024-09-12 10:50:37,098 - numba.core.byteflow - DEBUG - stack ['$i84.35', '$86load_global.36']\n", - "2024-09-12 10:50:37,099 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=CALL_FUNCTION(arg=1, lineno=462)\n", - "2024-09-12 10:50:37,100 - numba.core.byteflow - DEBUG - stack ['$i84.35', '$86load_global.36', '$indices88.37']\n", - "2024-09-12 10:50:37,100 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=COMPARE_OP(arg=0, lineno=462)\n", - "2024-09-12 10:50:37,101 - numba.core.byteflow - DEBUG - stack ['$i84.35', '$90call_function.38']\n", - "2024-09-12 10:50:37,102 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=POP_JUMP_IF_FALSE(arg=118, lineno=462)\n", - "2024-09-12 10:50:37,103 - numba.core.byteflow - DEBUG - stack ['$92compare_op.39']\n", - "2024-09-12 10:50:37,104 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=(), blockstack=(), npush=0), Edge(pc=234, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:37,105 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=0), State(pc_initial=234 nstack_initial=0)])\n", - "2024-09-12 10:50:37,105 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:37,106 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=96 nstack_initial=0)\n", - "2024-09-12 10:50:37,107 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=LOAD_GLOBAL(arg=9, lineno=468)\n", - "2024-09-12 10:50:37,108 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,108 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=2, lineno=468)\n", - "2024-09-12 10:50:37,109 - numba.core.byteflow - DEBUG - stack ['$96load_global.0']\n", - "2024-09-12 10:50:37,110 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=CALL_FUNCTION(arg=1, lineno=468)\n", - "2024-09-12 10:50:37,111 - numba.core.byteflow - DEBUG - stack ['$96load_global.0', '$starts98.1']\n", - "2024-09-12 10:50:37,111 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=STORE_FAST(arg=6, lineno=468)\n", - "2024-09-12 10:50:37,112 - numba.core.byteflow - DEBUG - stack ['$100call_function.2']\n", - "2024-09-12 10:50:37,113 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=LOAD_GLOBAL(arg=9, lineno=469)\n", - "2024-09-12 10:50:37,114 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,115 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_GLOBAL(arg=10, lineno=469)\n", - "2024-09-12 10:50:37,115 - numba.core.byteflow - DEBUG - stack ['$104load_global.3']\n", - "2024-09-12 10:50:37,116 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_FAST(arg=1, lineno=469)\n", - "2024-09-12 10:50:37,117 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4']\n", - "2024-09-12 10:50:37,118 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=LOAD_FAST(arg=5, lineno=469)\n", - "2024-09-12 10:50:37,119 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$indices108.5']\n", - "2024-09-12 10:50:37,119 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=1, lineno=469)\n", - "2024-09-12 10:50:37,120 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$indices108.5', '$i110.6']\n", - "2024-09-12 10:50:37,121 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BUILD_TUPLE(arg=2, lineno=469)\n", - "2024-09-12 10:50:37,122 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$indices108.5', '$i110.6', '$const112.7']\n", - "2024-09-12 10:50:37,122 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=BINARY_SUBSCR(arg=None, lineno=469)\n", - "2024-09-12 10:50:37,123 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$indices108.5', '$114build_tuple.8']\n", - "2024-09-12 10:50:37,124 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_FAST(arg=1, lineno=469)\n", - "2024-09-12 10:50:37,125 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9']\n", - "2024-09-12 10:50:37,126 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=5, lineno=469)\n", - "2024-09-12 10:50:37,126 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$indices118.10']\n", - "2024-09-12 10:50:37,127 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_CONST(arg=2, lineno=469)\n", - "2024-09-12 10:50:37,128 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$indices118.10', '$i120.11']\n", - "2024-09-12 10:50:37,129 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=BUILD_TUPLE(arg=2, lineno=469)\n", - "2024-09-12 10:50:37,129 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$indices118.10', '$i120.11', '$const122.12']\n", - "2024-09-12 10:50:37,130 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=BINARY_SUBSCR(arg=None, lineno=469)\n", - "2024-09-12 10:50:37,131 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$indices118.10', '$124build_tuple.13']\n", - "2024-09-12 10:50:37,131 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=LOAD_FAST(arg=1, lineno=469)\n", - "2024-09-12 10:50:37,132 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14']\n", - "2024-09-12 10:50:37,133 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=LOAD_FAST(arg=5, lineno=469)\n", - "2024-09-12 10:50:37,134 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$indices128.15']\n", - "2024-09-12 10:50:37,134 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_CONST(arg=3, lineno=469)\n", - "2024-09-12 10:50:37,135 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$indices128.15', '$i130.16']\n", - "2024-09-12 10:50:37,136 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=BUILD_TUPLE(arg=2, lineno=469)\n", - "2024-09-12 10:50:37,137 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$indices128.15', '$i130.16', '$const132.17']\n", - "2024-09-12 10:50:37,137 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BINARY_SUBSCR(arg=None, lineno=469)\n", - "2024-09-12 10:50:37,138 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$indices128.15', '$134build_tuple.18']\n", - "2024-09-12 10:50:37,139 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=CALL_FUNCTION(arg=3, lineno=469)\n", - "2024-09-12 10:50:37,140 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$136binary_subscr.19']\n", - "2024-09-12 10:50:37,140 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=CALL_FUNCTION(arg=1, lineno=469)\n", - "2024-09-12 10:50:37,141 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$138call_function.20']\n", - "2024-09-12 10:50:37,142 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=6, lineno=469)\n", - "2024-09-12 10:50:37,143 - numba.core.byteflow - DEBUG - stack ['$140call_function.21']\n", - "2024-09-12 10:50:37,143 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=BINARY_MULTIPLY(arg=None, lineno=469)\n", - "2024-09-12 10:50:37,144 - numba.core.byteflow - DEBUG - stack ['$140call_function.21', '$n_pairs142.22']\n", - "2024-09-12 10:50:37,145 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_CONST(arg=3, lineno=469)\n", - "2024-09-12 10:50:37,145 - numba.core.byteflow - DEBUG - stack ['$144binary_multiply.23']\n", - "2024-09-12 10:50:37,146 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=BINARY_ADD(arg=None, lineno=469)\n", - "2024-09-12 10:50:37,147 - numba.core.byteflow - DEBUG - stack ['$144binary_multiply.23', '$const146.24']\n", - "2024-09-12 10:50:37,148 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=STORE_FAST(arg=7, lineno=469)\n", - "2024-09-12 10:50:37,148 - numba.core.byteflow - DEBUG - stack ['$148binary_add.25']\n", - "2024-09-12 10:50:37,149 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=LOAD_FAST(arg=7, lineno=470)\n", - "2024-09-12 10:50:37,150 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,151 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_GLOBAL(arg=8, lineno=470)\n", - "2024-09-12 10:50:37,151 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26']\n", - "2024-09-12 10:50:37,152 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=LOAD_METHOD(arg=11, lineno=470)\n", - "2024-09-12 10:50:37,153 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$154load_global.27']\n", - "2024-09-12 10:50:37,154 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=LOAD_FAST(arg=7, lineno=470)\n", - "2024-09-12 10:50:37,154 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28']\n", - "2024-09-12 10:50:37,155 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=LOAD_GLOBAL(arg=12, lineno=470)\n", - "2024-09-12 10:50:37,156 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29']\n", - "2024-09-12 10:50:37,156 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=LOAD_FAST(arg=6, lineno=470)\n", - "2024-09-12 10:50:37,157 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29', '$160load_global.30']\n", - "2024-09-12 10:50:37,158 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=LOAD_CONST(arg=2, lineno=470)\n", - "2024-09-12 10:50:37,158 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29', '$160load_global.30', '$n_pairs162.31']\n", - "2024-09-12 10:50:37,159 - numba.core.byteflow - DEBUG - dispatch pc=166, inst=CALL_FUNCTION(arg=2, lineno=470)\n", - "2024-09-12 10:50:37,160 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29', '$160load_global.30', '$n_pairs162.31', '$const164.32']\n", - "2024-09-12 10:50:37,161 - numba.core.byteflow - DEBUG - dispatch pc=168, inst=BINARY_TRUE_DIVIDE(arg=None, lineno=470)\n", - "2024-09-12 10:50:37,161 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29', '$166call_function.33']\n", - "2024-09-12 10:50:37,162 - numba.core.byteflow - DEBUG - dispatch pc=170, inst=CALL_METHOD(arg=1, lineno=470)\n", - "2024-09-12 10:50:37,163 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$168binary_true_divide.34']\n", - "2024-09-12 10:50:37,163 - numba.core.byteflow - DEBUG - dispatch pc=172, inst=BINARY_MULTIPLY(arg=None, lineno=470)\n", - "2024-09-12 10:50:37,164 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$170call_method.35']\n", - "2024-09-12 10:50:37,165 - numba.core.byteflow - DEBUG - dispatch pc=174, inst=LOAD_FAST(arg=4, lineno=470)\n", - "2024-09-12 10:50:37,166 - numba.core.byteflow - DEBUG - stack ['$172binary_multiply.36']\n", - "2024-09-12 10:50:37,166 - numba.core.byteflow - DEBUG - dispatch pc=176, inst=LOAD_FAST(arg=6, lineno=470)\n", - "2024-09-12 10:50:37,167 - numba.core.byteflow - DEBUG - stack ['$172binary_multiply.36', '$n_matches174.37']\n", - "2024-09-12 10:50:37,168 - numba.core.byteflow - DEBUG - dispatch pc=178, inst=BINARY_ADD(arg=None, lineno=470)\n", - "2024-09-12 10:50:37,168 - numba.core.byteflow - DEBUG - stack ['$172binary_multiply.36', '$n_matches174.37', '$n_pairs176.38']\n", - "2024-09-12 10:50:37,169 - numba.core.byteflow - DEBUG - dispatch pc=180, inst=COMPARE_OP(arg=4, lineno=470)\n", - "2024-09-12 10:50:37,170 - numba.core.byteflow - DEBUG - stack ['$172binary_multiply.36', '$178binary_add.39']\n", - "2024-09-12 10:50:37,170 - numba.core.byteflow - DEBUG - dispatch pc=182, inst=POP_JUMP_IF_FALSE(arg=94, lineno=470)\n", - "2024-09-12 10:50:37,171 - numba.core.byteflow - DEBUG - stack ['$180compare_op.40']\n", - "2024-09-12 10:50:37,172 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=184, stack=(), blockstack=(), npush=0), Edge(pc=186, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:37,173 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=234 nstack_initial=0), State(pc_initial=184 nstack_initial=0), State(pc_initial=186 nstack_initial=0)])\n", - "2024-09-12 10:50:37,173 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:37,174 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=234 nstack_initial=0)\n", - "2024-09-12 10:50:37,175 - numba.core.byteflow - DEBUG - dispatch pc=234, inst=LOAD_GLOBAL(arg=14, lineno=482)\n", - "2024-09-12 10:50:37,175 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,176 - numba.core.byteflow - DEBUG - dispatch pc=236, inst=LOAD_FAST(arg=2, lineno=482)\n", - "2024-09-12 10:50:37,177 - numba.core.byteflow - DEBUG - stack ['$234load_global.0']\n", - "2024-09-12 10:50:37,177 - numba.core.byteflow - DEBUG - dispatch pc=238, inst=LOAD_FAST(arg=3, lineno=482)\n", - "2024-09-12 10:50:37,178 - numba.core.byteflow - DEBUG - stack ['$234load_global.0', '$starts236.1']\n", - "2024-09-12 10:50:37,179 - numba.core.byteflow - DEBUG - dispatch pc=240, inst=CALL_FUNCTION(arg=2, lineno=482)\n", - "2024-09-12 10:50:37,179 - numba.core.byteflow - DEBUG - stack ['$234load_global.0', '$starts236.1', '$stops238.2']\n", - "2024-09-12 10:50:37,180 - numba.core.byteflow - DEBUG - dispatch pc=242, inst=UNPACK_SEQUENCE(arg=2, lineno=482)\n", - "2024-09-12 10:50:37,181 - numba.core.byteflow - DEBUG - stack ['$240call_function.3']\n", - "2024-09-12 10:50:37,182 - numba.core.byteflow - DEBUG - dispatch pc=244, inst=STORE_FAST(arg=2, lineno=482)\n", - "2024-09-12 10:50:37,182 - numba.core.byteflow - DEBUG - stack ['$242unpack_sequence.5', '$242unpack_sequence.4']\n", - "2024-09-12 10:50:37,183 - numba.core.byteflow - DEBUG - dispatch pc=246, inst=STORE_FAST(arg=3, lineno=482)\n", - "2024-09-12 10:50:37,184 - numba.core.byteflow - DEBUG - stack ['$242unpack_sequence.5']\n", - "2024-09-12 10:50:37,184 - numba.core.byteflow - DEBUG - dispatch pc=248, inst=LOAD_FAST(arg=5, lineno=485)\n", - "2024-09-12 10:50:37,185 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,185 - numba.core.byteflow - DEBUG - dispatch pc=250, inst=LOAD_GLOBAL(arg=9, lineno=485)\n", - "2024-09-12 10:50:37,186 - numba.core.byteflow - DEBUG - stack ['$i248.7']\n", - "2024-09-12 10:50:37,187 - numba.core.byteflow - DEBUG - dispatch pc=252, inst=LOAD_FAST(arg=1, lineno=485)\n", - "2024-09-12 10:50:37,188 - numba.core.byteflow - DEBUG - stack ['$i248.7', '$250load_global.8']\n", - "2024-09-12 10:50:37,188 - numba.core.byteflow - DEBUG - dispatch pc=254, inst=CALL_FUNCTION(arg=1, lineno=485)\n", - "2024-09-12 10:50:37,189 - numba.core.byteflow - DEBUG - stack ['$i248.7', '$250load_global.8', '$indices252.9']\n", - "2024-09-12 10:50:37,190 - numba.core.byteflow - DEBUG - dispatch pc=256, inst=COMPARE_OP(arg=2, lineno=485)\n", - "2024-09-12 10:50:37,190 - numba.core.byteflow - DEBUG - stack ['$i248.7', '$254call_function.10']\n", - "2024-09-12 10:50:37,191 - numba.core.byteflow - DEBUG - dispatch pc=258, inst=POP_JUMP_IF_FALSE(arg=150, lineno=485)\n", - "2024-09-12 10:50:37,192 - numba.core.byteflow - DEBUG - stack ['$256compare_op.11']\n", - "2024-09-12 10:50:37,192 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=260, stack=(), blockstack=(), npush=0), Edge(pc=298, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:37,193 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=184 nstack_initial=0), State(pc_initial=186 nstack_initial=0), State(pc_initial=260 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:37,194 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:37,194 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=184 nstack_initial=0)\n", - "2024-09-12 10:50:37,195 - numba.core.byteflow - DEBUG - dispatch pc=184, inst=JUMP_FORWARD(arg=24, lineno=471)\n", - "2024-09-12 10:50:37,196 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,196 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=234, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:37,197 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=186 nstack_initial=0), State(pc_initial=260 nstack_initial=0), State(pc_initial=298 nstack_initial=0), State(pc_initial=234 nstack_initial=0)])\n", - "2024-09-12 10:50:37,198 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:37,198 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=186 nstack_initial=0)\n", - "2024-09-12 10:50:37,199 - numba.core.byteflow - DEBUG - dispatch pc=186, inst=LOAD_GLOBAL(arg=13, lineno=477)\n", - "2024-09-12 10:50:37,200 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,200 - numba.core.byteflow - DEBUG - dispatch pc=188, inst=LOAD_FAST(arg=2, lineno=477)\n", - "2024-09-12 10:50:37,201 - numba.core.byteflow - DEBUG - stack ['$186load_global.0']\n", - "2024-09-12 10:50:37,202 - numba.core.byteflow - DEBUG - dispatch pc=190, inst=LOAD_FAST(arg=3, lineno=477)\n", - "2024-09-12 10:50:37,202 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1']\n", - "2024-09-12 10:50:37,203 - numba.core.byteflow - DEBUG - dispatch pc=192, inst=LOAD_FAST(arg=0, lineno=477)\n", - "2024-09-12 10:50:37,204 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2']\n", - "2024-09-12 10:50:37,204 - numba.core.byteflow - DEBUG - dispatch pc=194, inst=LOAD_FAST(arg=5, lineno=477)\n", - "2024-09-12 10:50:37,205 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$coords192.3']\n", - "2024-09-12 10:50:37,206 - numba.core.byteflow - DEBUG - dispatch pc=196, inst=BINARY_SUBSCR(arg=None, lineno=477)\n", - "2024-09-12 10:50:37,206 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$coords192.3', '$i194.4']\n", - "2024-09-12 10:50:37,207 - numba.core.byteflow - DEBUG - dispatch pc=198, inst=LOAD_FAST(arg=1, lineno=477)\n", - "2024-09-12 10:50:37,208 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$196binary_subscr.5']\n", - "2024-09-12 10:50:37,208 - numba.core.byteflow - DEBUG - dispatch pc=200, inst=LOAD_FAST(arg=5, lineno=477)\n", - "2024-09-12 10:50:37,209 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$196binary_subscr.5', '$indices198.6']\n", - "2024-09-12 10:50:37,210 - numba.core.byteflow - DEBUG - dispatch pc=202, inst=BINARY_SUBSCR(arg=None, lineno=477)\n", - "2024-09-12 10:50:37,210 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$196binary_subscr.5', '$indices198.6', '$i200.7']\n", - "2024-09-12 10:50:37,211 - numba.core.byteflow - DEBUG - dispatch pc=204, inst=CALL_FUNCTION(arg=4, lineno=477)\n", - "2024-09-12 10:50:37,212 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$196binary_subscr.5', '$202binary_subscr.8']\n", - "2024-09-12 10:50:37,212 - numba.core.byteflow - DEBUG - dispatch pc=206, inst=UNPACK_SEQUENCE(arg=3, lineno=477)\n", - "2024-09-12 10:50:37,213 - numba.core.byteflow - DEBUG - stack ['$204call_function.9']\n", - "2024-09-12 10:50:37,214 - numba.core.byteflow - DEBUG - dispatch pc=208, inst=STORE_FAST(arg=2, lineno=477)\n", - "2024-09-12 10:50:37,214 - numba.core.byteflow - DEBUG - stack ['$206unpack_sequence.12', '$206unpack_sequence.11', '$206unpack_sequence.10']\n", - "2024-09-12 10:50:37,215 - numba.core.byteflow - DEBUG - dispatch pc=210, inst=STORE_FAST(arg=3, lineno=477)\n", - "2024-09-12 10:50:37,216 - numba.core.byteflow - DEBUG - stack ['$206unpack_sequence.12', '$206unpack_sequence.11']\n", - "2024-09-12 10:50:37,216 - numba.core.byteflow - DEBUG - dispatch pc=212, inst=STORE_FAST(arg=4, lineno=477)\n", - "2024-09-12 10:50:37,217 - numba.core.byteflow - DEBUG - stack ['$206unpack_sequence.12']\n", - "2024-09-12 10:50:37,217 - numba.core.byteflow - DEBUG - dispatch pc=214, inst=LOAD_FAST(arg=5, lineno=479)\n", - "2024-09-12 10:50:37,218 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,219 - numba.core.byteflow - DEBUG - dispatch pc=216, inst=LOAD_CONST(arg=2, lineno=479)\n", - "2024-09-12 10:50:37,219 - numba.core.byteflow - DEBUG - stack ['$i214.14']\n", - "2024-09-12 10:50:37,220 - numba.core.byteflow - DEBUG - dispatch pc=218, inst=INPLACE_ADD(arg=None, lineno=479)\n", - "2024-09-12 10:50:37,221 - numba.core.byteflow - DEBUG - stack ['$i214.14', '$const216.15']\n", - "2024-09-12 10:50:37,221 - numba.core.byteflow - DEBUG - dispatch pc=220, inst=STORE_FAST(arg=5, lineno=479)\n", - "2024-09-12 10:50:37,222 - numba.core.byteflow - DEBUG - stack ['$218inplace_add.16']\n", - "2024-09-12 10:50:37,223 - numba.core.byteflow - DEBUG - dispatch pc=222, inst=LOAD_FAST(arg=5, lineno=462)\n", - "2024-09-12 10:50:37,223 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,224 - numba.core.byteflow - DEBUG - dispatch pc=224, inst=LOAD_GLOBAL(arg=9, lineno=462)\n", - "2024-09-12 10:50:37,225 - numba.core.byteflow - DEBUG - stack ['$i222.17']\n", - "2024-09-12 10:50:37,225 - numba.core.byteflow - DEBUG - dispatch pc=226, inst=LOAD_FAST(arg=1, lineno=462)\n", - "2024-09-12 10:50:37,226 - numba.core.byteflow - DEBUG - stack ['$i222.17', '$224load_global.18']\n", - "2024-09-12 10:50:37,226 - numba.core.byteflow - DEBUG - dispatch pc=228, inst=CALL_FUNCTION(arg=1, lineno=462)\n", - "2024-09-12 10:50:37,227 - numba.core.byteflow - DEBUG - stack ['$i222.17', '$224load_global.18', '$indices226.19']\n", - "2024-09-12 10:50:37,228 - numba.core.byteflow - DEBUG - dispatch pc=230, inst=COMPARE_OP(arg=0, lineno=462)\n", - "2024-09-12 10:50:37,228 - numba.core.byteflow - DEBUG - stack ['$i222.17', '$228call_function.20']\n", - "2024-09-12 10:50:37,229 - numba.core.byteflow - DEBUG - dispatch pc=232, inst=POP_JUMP_IF_TRUE(arg=49, lineno=462)\n", - "2024-09-12 10:50:37,229 - numba.core.byteflow - DEBUG - stack ['$230compare_op.21']\n", - "2024-09-12 10:50:37,230 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=234, stack=(), blockstack=(), npush=0), Edge(pc=96, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:37,231 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=260 nstack_initial=0), State(pc_initial=298 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=96 nstack_initial=0)])\n", - "2024-09-12 10:50:37,231 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:37,232 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=260 nstack_initial=0)\n", - "2024-09-12 10:50:37,232 - numba.core.byteflow - DEBUG - dispatch pc=260, inst=LOAD_GLOBAL(arg=9, lineno=485)\n", - "2024-09-12 10:50:37,233 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,234 - numba.core.byteflow - DEBUG - dispatch pc=262, inst=LOAD_FAST(arg=2, lineno=485)\n", - "2024-09-12 10:50:37,234 - numba.core.byteflow - DEBUG - stack ['$260load_global.0']\n", - "2024-09-12 10:50:37,235 - numba.core.byteflow - DEBUG - dispatch pc=264, inst=CALL_FUNCTION(arg=1, lineno=485)\n", - "2024-09-12 10:50:37,236 - numba.core.byteflow - DEBUG - stack ['$260load_global.0', '$starts262.1']\n", - "2024-09-12 10:50:37,236 - numba.core.byteflow - DEBUG - dispatch pc=266, inst=LOAD_CONST(arg=2, lineno=485)\n", - "2024-09-12 10:50:37,237 - numba.core.byteflow - DEBUG - stack ['$264call_function.2']\n", - "2024-09-12 10:50:37,238 - numba.core.byteflow - DEBUG - dispatch pc=268, inst=COMPARE_OP(arg=2, lineno=485)\n", - "2024-09-12 10:50:37,238 - numba.core.byteflow - DEBUG - stack ['$264call_function.2', '$const266.3']\n", - "2024-09-12 10:50:37,239 - numba.core.byteflow - DEBUG - dispatch pc=270, inst=POP_JUMP_IF_FALSE(arg=150, lineno=485)\n", - "2024-09-12 10:50:37,240 - numba.core.byteflow - DEBUG - stack ['$268compare_op.4']\n", - "2024-09-12 10:50:37,240 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=272, stack=(), blockstack=(), npush=0), Edge(pc=298, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:37,241 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=298 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=96 nstack_initial=0), State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:37,242 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:37,243 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=298 nstack_initial=0)\n", - "2024-09-12 10:50:37,244 - numba.core.byteflow - DEBUG - dispatch pc=298, inst=LOAD_GLOBAL(arg=16, lineno=490)\n", - "2024-09-12 10:50:37,244 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,245 - numba.core.byteflow - DEBUG - dispatch pc=300, inst=LOAD_FAST(arg=2, lineno=490)\n", - "2024-09-12 10:50:37,245 - numba.core.byteflow - DEBUG - stack ['$298load_global.0']\n", - "2024-09-12 10:50:37,246 - numba.core.byteflow - DEBUG - dispatch pc=302, inst=LOAD_FAST(arg=3, lineno=490)\n", - "2024-09-12 10:50:37,247 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1']\n", - "2024-09-12 10:50:37,247 - numba.core.byteflow - DEBUG - dispatch pc=304, inst=LOAD_FAST(arg=0, lineno=490)\n", - "2024-09-12 10:50:37,248 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2']\n", - "2024-09-12 10:50:37,249 - numba.core.byteflow - DEBUG - dispatch pc=306, inst=LOAD_FAST(arg=5, lineno=490)\n", - "2024-09-12 10:50:37,249 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$coords304.3']\n", - "2024-09-12 10:50:37,250 - numba.core.byteflow - DEBUG - dispatch pc=308, inst=LOAD_CONST(arg=5, lineno=490)\n", - "2024-09-12 10:50:37,251 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$coords304.3', '$i306.4']\n", - "2024-09-12 10:50:37,251 - numba.core.byteflow - DEBUG - dispatch pc=310, inst=BUILD_SLICE(arg=2, lineno=490)\n", - "2024-09-12 10:50:37,252 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$coords304.3', '$i306.4', '$const308.5']\n", - "2024-09-12 10:50:37,252 - numba.core.byteflow - DEBUG - dispatch pc=312, inst=BINARY_SUBSCR(arg=None, lineno=490)\n", - "2024-09-12 10:50:37,253 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$coords304.3', '$310build_slice.7']\n", - "2024-09-12 10:50:37,254 - numba.core.byteflow - DEBUG - dispatch pc=314, inst=LOAD_FAST(arg=1, lineno=490)\n", - "2024-09-12 10:50:37,254 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8']\n", - "2024-09-12 10:50:37,255 - numba.core.byteflow - DEBUG - dispatch pc=316, inst=LOAD_FAST(arg=5, lineno=490)\n", - "2024-09-12 10:50:37,256 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$indices314.9']\n", - "2024-09-12 10:50:37,256 - numba.core.byteflow - DEBUG - dispatch pc=318, inst=LOAD_CONST(arg=5, lineno=490)\n", - "2024-09-12 10:50:37,257 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$indices314.9', '$i316.10']\n", - "2024-09-12 10:50:37,257 - numba.core.byteflow - DEBUG - dispatch pc=320, inst=BUILD_SLICE(arg=2, lineno=490)\n", - "2024-09-12 10:50:37,258 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$indices314.9', '$i316.10', '$const318.11']\n", - "2024-09-12 10:50:37,259 - numba.core.byteflow - DEBUG - dispatch pc=322, inst=BINARY_SUBSCR(arg=None, lineno=490)\n", - "2024-09-12 10:50:37,259 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$indices314.9', '$320build_slice.13']\n", - "2024-09-12 10:50:37,260 - numba.core.byteflow - DEBUG - dispatch pc=324, inst=CALL_FUNCTION(arg=4, lineno=490)\n", - "2024-09-12 10:50:37,260 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$322binary_subscr.14']\n", - "2024-09-12 10:50:37,261 - numba.core.byteflow - DEBUG - dispatch pc=326, inst=STORE_FAST(arg=8, lineno=490)\n", - "2024-09-12 10:50:37,262 - numba.core.byteflow - DEBUG - stack ['$324call_function.15']\n", - "2024-09-12 10:50:37,262 - numba.core.byteflow - DEBUG - dispatch pc=328, inst=LOAD_GLOBAL(arg=17, lineno=491)\n", - "2024-09-12 10:50:37,263 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,263 - numba.core.byteflow - DEBUG - dispatch pc=330, inst=LOAD_FAST(arg=8, lineno=491)\n", - "2024-09-12 10:50:37,264 - numba.core.byteflow - DEBUG - stack ['$328load_global.16']\n", - "2024-09-12 10:50:37,265 - numba.core.byteflow - DEBUG - dispatch pc=332, inst=CALL_FUNCTION(arg=1, lineno=491)\n", - "2024-09-12 10:50:37,265 - numba.core.byteflow - DEBUG - stack ['$328load_global.16', '$mask330.17']\n", - "2024-09-12 10:50:37,270 - numba.core.byteflow - DEBUG - dispatch pc=334, inst=LOAD_CONST(arg=6, lineno=491)\n", - "2024-09-12 10:50:37,271 - numba.core.byteflow - DEBUG - stack ['$332call_function.18']\n", - "2024-09-12 10:50:37,272 - numba.core.byteflow - DEBUG - dispatch pc=336, inst=BUILD_TUPLE(arg=2, lineno=491)\n", - "2024-09-12 10:50:37,272 - numba.core.byteflow - DEBUG - stack ['$332call_function.18', '$const334.19']\n", - "2024-09-12 10:50:37,300 - numba.core.byteflow - DEBUG - dispatch pc=338, inst=RETURN_VALUE(arg=None, lineno=491)\n", - "2024-09-12 10:50:37,301 - numba.core.byteflow - DEBUG - stack ['$336build_tuple.20']\n", - "2024-09-12 10:50:37,301 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:37,302 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=234 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=96 nstack_initial=0), State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:37,303 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=234 nstack_initial=0), State(pc_initial=96 nstack_initial=0), State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:37,303 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=0), State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:37,304 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:37,304 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:37,305 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=272 nstack_initial=0)\n", - "2024-09-12 10:50:37,306 - numba.core.byteflow - DEBUG - dispatch pc=272, inst=LOAD_GLOBAL(arg=8, lineno=486)\n", - "2024-09-12 10:50:37,306 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:37,307 - numba.core.byteflow - DEBUG - dispatch pc=274, inst=LOAD_METHOD(arg=15, lineno=486)\n", - "2024-09-12 10:50:37,307 - numba.core.byteflow - DEBUG - stack ['$272load_global.0']\n", - "2024-09-12 10:50:37,307 - numba.core.byteflow - DEBUG - dispatch pc=276, inst=LOAD_FAST(arg=2, lineno=486)\n", - "2024-09-12 10:50:37,308 - numba.core.byteflow - DEBUG - stack ['$274load_method.1']\n", - "2024-09-12 10:50:37,308 - numba.core.byteflow - DEBUG - dispatch pc=278, inst=LOAD_CONST(arg=1, lineno=486)\n", - "2024-09-12 10:50:37,309 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$starts276.2']\n", - "2024-09-12 10:50:37,309 - numba.core.byteflow - DEBUG - dispatch pc=280, inst=BINARY_SUBSCR(arg=None, lineno=486)\n", - "2024-09-12 10:50:37,310 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$starts276.2', '$const278.3']\n", - "2024-09-12 10:50:37,310 - numba.core.byteflow - DEBUG - dispatch pc=282, inst=LOAD_FAST(arg=3, lineno=486)\n", - "2024-09-12 10:50:37,311 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$280binary_subscr.4']\n", - "2024-09-12 10:50:37,311 - numba.core.byteflow - DEBUG - dispatch pc=284, inst=LOAD_CONST(arg=1, lineno=486)\n", - "2024-09-12 10:50:37,312 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$280binary_subscr.4', '$stops282.5']\n", - "2024-09-12 10:50:37,314 - numba.core.byteflow - DEBUG - dispatch pc=286, inst=BINARY_SUBSCR(arg=None, lineno=486)\n", - "2024-09-12 10:50:37,314 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$280binary_subscr.4', '$stops282.5', '$const284.6']\n", - "2024-09-12 10:50:37,315 - numba.core.byteflow - DEBUG - dispatch pc=288, inst=BUILD_LIST(arg=2, lineno=486)\n", - "2024-09-12 10:50:37,315 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$280binary_subscr.4', '$286binary_subscr.7']\n", - "2024-09-12 10:50:37,316 - numba.core.byteflow - DEBUG - dispatch pc=290, inst=CALL_METHOD(arg=1, lineno=486)\n", - "2024-09-12 10:50:37,317 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$288build_list.8']\n", - "2024-09-12 10:50:37,317 - numba.core.byteflow - DEBUG - dispatch pc=292, inst=LOAD_CONST(arg=4, lineno=486)\n", - "2024-09-12 10:50:37,318 - numba.core.byteflow - DEBUG - stack ['$290call_method.9']\n", - "2024-09-12 10:50:37,318 - numba.core.byteflow - DEBUG - dispatch pc=294, inst=BUILD_TUPLE(arg=2, lineno=486)\n", - "2024-09-12 10:50:37,318 - numba.core.byteflow - DEBUG - stack ['$290call_method.9', '$const292.10']\n", - "2024-09-12 10:50:37,319 - numba.core.byteflow - DEBUG - dispatch pc=296, inst=RETURN_VALUE(arg=None, lineno=486)\n", - "2024-09-12 10:50:37,319 - numba.core.byteflow - DEBUG - stack ['$294build_tuple.11']\n", - "2024-09-12 10:50:37,321 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:37,321 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:37,322 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:37,322 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=96 nstack_initial=0): set(),\n", - " State(pc_initial=184 nstack_initial=0): set(),\n", - " State(pc_initial=186 nstack_initial=0): set(),\n", - " State(pc_initial=234 nstack_initial=0): set(),\n", - " State(pc_initial=260 nstack_initial=0): set(),\n", - " State(pc_initial=272 nstack_initial=0): set(),\n", - " State(pc_initial=298 nstack_initial=0): set()})\n", - "2024-09-12 10:50:37,324 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:37,324 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:37,325 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:37,325 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:37,326 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:37,327 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:37,327 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'item': '$4load_attr.1', 'res': '$6load_attr.2'}), (8, {'item': '$6load_attr.2', 'res': '$8load_method.3'}), (10, {'res': '$10load_global.4'}), (12, {'item': '$10load_global.4', 'res': '$12load_attr.5'}), (14, {'item': '$12load_attr.5', 'res': '$14load_attr.6'}), (16, {'func': '$8load_method.3', 'args': ['$14load_attr.6'], 'res': '$16call_method.7'}), (18, {'value': '$16call_method.7'}), (20, {'res': '$starts20.8'}), (22, {'item': '$starts20.8', 'res': '$22load_method.9'}), (24, {'res': '$const24.10'}), (26, {'func': '$22load_method.9', 'args': ['$const24.10'], 'res': '$26call_method.11'}), (30, {'res': '$30load_global.12'}), (32, {'item': '$30load_global.12', 'res': '$32load_attr.13'}), (34, {'item': '$32load_attr.13', 'res': '$34load_attr.14'}), (36, {'item': '$34load_attr.14', 'res': '$36load_method.15'}), (38, {'res': '$38load_global.16'}), (40, {'item': '$38load_global.16', 'res': '$40load_attr.17'}), (42, {'item': '$40load_attr.17', 'res': '$42load_attr.18'}), (44, {'func': '$36load_method.15', 'args': ['$42load_attr.18'], 'res': '$44call_method.19'}), (46, {'value': '$44call_method.19'}), (48, {'res': '$stops48.20'}), (50, {'item': '$stops48.20', 'res': '$50load_method.21'}), (52, {'res': '$coords52.22'}), (54, {'item': '$coords52.22', 'res': '$54load_attr.23'}), (56, {'res': '$const56.24'}), (58, {'index': '$const56.24', 'target': '$54load_attr.23', 'res': '$58binary_subscr.25'}), (60, {'func': '$50load_method.21', 'args': ['$58binary_subscr.25'], 'res': '$60call_method.26'}), (64, {'res': '$64load_global.27'}), (66, {'item': '$64load_global.27', 'res': '$66load_method.28'}), (68, {'res': '$coords68.29'}), (70, {'item': '$coords68.29', 'res': '$70load_attr.30'}), (72, {'res': '$const72.31'}), (74, {'index': '$const72.31', 'target': '$70load_attr.30', 'res': '$74binary_subscr.32'}), (76, {'func': '$66load_method.28', 'args': ['$74binary_subscr.32'], 'res': '$76call_method.33'}), (78, {'value': '$76call_method.33'}), (80, {'res': '$const80.34'}), (82, {'value': '$const80.34'}), (84, {'res': '$i84.35'}), (86, {'res': '$86load_global.36'}), (88, {'res': '$indices88.37'}), (90, {'func': '$86load_global.36', 'args': ['$indices88.37'], 'res': '$90call_function.38'}), (92, {'lhs': '$i84.35', 'rhs': '$90call_function.38', 'res': '$92compare_op.39'}), (94, {'pred': '$92compare_op.39'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: (), 234: ()})\n", - "2024-09-12 10:50:37,328 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=96 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((96, {'res': '$96load_global.0'}), (98, {'res': '$starts98.1'}), (100, {'func': '$96load_global.0', 'args': ['$starts98.1'], 'res': '$100call_function.2'}), (102, {'value': '$100call_function.2'}), (104, {'res': '$104load_global.3'}), (106, {'res': '$106load_global.4'}), (108, {'res': '$indices108.5'}), (110, {'res': '$i110.6'}), (112, {'res': '$const112.7'}), (114, {'items': ['$i110.6', '$const112.7'], 'res': '$114build_tuple.8'}), (116, {'index': '$114build_tuple.8', 'target': '$indices108.5', 'res': '$116binary_subscr.9'}), (118, {'res': '$indices118.10'}), (120, {'res': '$i120.11'}), (122, {'res': '$const122.12'}), (124, {'items': ['$i120.11', '$const122.12'], 'res': '$124build_tuple.13'}), (126, {'index': '$124build_tuple.13', 'target': '$indices118.10', 'res': '$126binary_subscr.14'}), (128, {'res': '$indices128.15'}), (130, {'res': '$i130.16'}), (132, {'res': '$const132.17'}), (134, {'items': ['$i130.16', '$const132.17'], 'res': '$134build_tuple.18'}), (136, {'index': '$134build_tuple.18', 'target': '$indices128.15', 'res': '$136binary_subscr.19'}), (138, {'func': '$106load_global.4', 'args': ['$116binary_subscr.9', '$126binary_subscr.14', '$136binary_subscr.19'], 'res': '$138call_function.20'}), (140, {'func': '$104load_global.3', 'args': ['$138call_function.20'], 'res': '$140call_function.21'}), (142, {'res': '$n_pairs142.22'}), (144, {'lhs': '$140call_function.21', 'rhs': '$n_pairs142.22', 'res': '$144binary_multiply.23'}), (146, {'res': '$const146.24'}), (148, {'lhs': '$144binary_multiply.23', 'rhs': '$const146.24', 'res': '$148binary_add.25'}), (150, {'value': '$148binary_add.25'}), (152, {'res': '$n_current_slices152.26'}), (154, {'res': '$154load_global.27'}), (156, {'item': '$154load_global.27', 'res': '$156load_method.28'}), (158, {'res': '$n_current_slices158.29'}), (160, {'res': '$160load_global.30'}), (162, {'res': '$n_pairs162.31'}), (164, {'res': '$const164.32'}), (166, {'func': '$160load_global.30', 'args': ['$n_pairs162.31', '$const164.32'], 'res': '$166call_function.33'}), (168, {'lhs': '$n_current_slices158.29', 'rhs': '$166call_function.33', 'res': '$168binary_true_divide.34'}), (170, {'func': '$156load_method.28', 'args': ['$168binary_true_divide.34'], 'res': '$170call_method.35'}), (172, {'lhs': '$n_current_slices152.26', 'rhs': '$170call_method.35', 'res': '$172binary_multiply.36'}), (174, {'res': '$n_matches174.37'}), (176, {'res': '$n_pairs176.38'}), (178, {'lhs': '$n_matches174.37', 'rhs': '$n_pairs176.38', 'res': '$178binary_add.39'}), (180, {'lhs': '$172binary_multiply.36', 'rhs': '$178binary_add.39', 'res': '$180compare_op.40'}), (182, {'pred': '$180compare_op.40'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={184: (), 186: ()})\n", - "2024-09-12 10:50:37,329 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=184 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((184, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={234: ()})\n", - "2024-09-12 10:50:37,330 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=186 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((186, {'res': '$186load_global.0'}), (188, {'res': '$starts188.1'}), (190, {'res': '$stops190.2'}), (192, {'res': '$coords192.3'}), (194, {'res': '$i194.4'}), (196, {'index': '$i194.4', 'target': '$coords192.3', 'res': '$196binary_subscr.5'}), (198, {'res': '$indices198.6'}), (200, {'res': '$i200.7'}), (202, {'index': '$i200.7', 'target': '$indices198.6', 'res': '$202binary_subscr.8'}), (204, {'func': '$186load_global.0', 'args': ['$starts188.1', '$stops190.2', '$196binary_subscr.5', '$202binary_subscr.8'], 'res': '$204call_function.9'}), (206, {'iterable': '$204call_function.9', 'stores': ['$206unpack_sequence.10', '$206unpack_sequence.11', '$206unpack_sequence.12'], 'tupleobj': '$206unpack_sequence.13'}), (208, {'value': '$206unpack_sequence.10'}), (210, {'value': '$206unpack_sequence.11'}), (212, {'value': '$206unpack_sequence.12'}), (214, {'res': '$i214.14'}), (216, {'res': '$const216.15'}), (218, {'lhs': '$i214.14', 'rhs': '$const216.15', 'res': '$218inplace_add.16'}), (220, {'value': '$218inplace_add.16'}), (222, {'res': '$i222.17'}), (224, {'res': '$224load_global.18'}), (226, {'res': '$indices226.19'}), (228, {'func': '$224load_global.18', 'args': ['$indices226.19'], 'res': '$228call_function.20'}), (230, {'lhs': '$i222.17', 'rhs': '$228call_function.20', 'res': '$230compare_op.21'}), (232, {'pred': '$230compare_op.21'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={234: (), 96: ()})\n", - "2024-09-12 10:50:37,330 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=234 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((234, {'res': '$234load_global.0'}), (236, {'res': '$starts236.1'}), (238, {'res': '$stops238.2'}), (240, {'func': '$234load_global.0', 'args': ['$starts236.1', '$stops238.2'], 'res': '$240call_function.3'}), (242, {'iterable': '$240call_function.3', 'stores': ['$242unpack_sequence.4', '$242unpack_sequence.5'], 'tupleobj': '$242unpack_sequence.6'}), (244, {'value': '$242unpack_sequence.4'}), (246, {'value': '$242unpack_sequence.5'}), (248, {'res': '$i248.7'}), (250, {'res': '$250load_global.8'}), (252, {'res': '$indices252.9'}), (254, {'func': '$250load_global.8', 'args': ['$indices252.9'], 'res': '$254call_function.10'}), (256, {'lhs': '$i248.7', 'rhs': '$254call_function.10', 'res': '$256compare_op.11'}), (258, {'pred': '$256compare_op.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={260: (), 298: ()})\n", - "2024-09-12 10:50:37,331 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=260 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((260, {'res': '$260load_global.0'}), (262, {'res': '$starts262.1'}), (264, {'func': '$260load_global.0', 'args': ['$starts262.1'], 'res': '$264call_function.2'}), (266, {'res': '$const266.3'}), (268, {'lhs': '$264call_function.2', 'rhs': '$const266.3', 'res': '$268compare_op.4'}), (270, {'pred': '$268compare_op.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={272: (), 298: ()})\n", - "2024-09-12 10:50:37,331 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=272 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((272, {'res': '$272load_global.0'}), (274, {'item': '$272load_global.0', 'res': '$274load_method.1'}), (276, {'res': '$starts276.2'}), (278, {'res': '$const278.3'}), (280, {'index': '$const278.3', 'target': '$starts276.2', 'res': '$280binary_subscr.4'}), (282, {'res': '$stops282.5'}), (284, {'res': '$const284.6'}), (286, {'index': '$const284.6', 'target': '$stops282.5', 'res': '$286binary_subscr.7'}), (288, {'items': ['$280binary_subscr.4', '$286binary_subscr.7'], 'res': '$288build_list.8'}), (290, {'func': '$274load_method.1', 'args': ['$288build_list.8'], 'res': '$290call_method.9'}), (292, {'res': '$const292.10'}), (294, {'items': ['$290call_method.9', '$const292.10'], 'res': '$294build_tuple.11'}), (296, {'retval': '$294build_tuple.11', 'castval': '$296return_value.12'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:37,332 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=298 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((298, {'res': '$298load_global.0'}), (300, {'res': '$starts300.1'}), (302, {'res': '$stops302.2'}), (304, {'res': '$coords304.3'}), (306, {'res': '$i306.4'}), (308, {'res': '$const308.5'}), (310, {'start': '$i306.4', 'stop': '$const308.5', 'step': None, 'res': '$310build_slice.7', 'slicevar': '$310build_slice.6'}), (312, {'index': '$310build_slice.7', 'target': '$coords304.3', 'res': '$312binary_subscr.8'}), (314, {'res': '$indices314.9'}), (316, {'res': '$i316.10'}), (318, {'res': '$const318.11'}), (320, {'start': '$i316.10', 'stop': '$const318.11', 'step': None, 'res': '$320build_slice.13', 'slicevar': '$320build_slice.12'}), (322, {'index': '$320build_slice.13', 'target': '$indices314.9', 'res': '$322binary_subscr.14'}), (324, {'func': '$298load_global.0', 'args': ['$starts300.1', '$stops302.2', '$312binary_subscr.8', '$322binary_subscr.14'], 'res': '$324call_function.15'}), (326, {'value': '$324call_function.15'}), (328, {'res': '$328load_global.16'}), (330, {'res': '$mask330.17'}), (332, {'func': '$328load_global.16', 'args': ['$mask330.17'], 'res': '$332call_function.18'}), (334, {'res': '$const334.19'}), (336, {'items': ['$332call_function.18', '$const334.19'], 'res': '$336build_tuple.20'}), (338, {'retval': '$336build_tuple.20', 'castval': '$338return_value.21'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:37,344 - numba.core.interpreter - DEBUG - label 0:\n", - " coords = arg(0, name=coords) ['coords']\n", - " indices = arg(1, name=indices) ['indices']\n", - " $2load_global.0 = global(numba: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=typed) ['$2load_global.0', '$4load_attr.1']\n", - " $6load_attr.2 = getattr(value=$4load_attr.1, attr=List) ['$4load_attr.1', '$6load_attr.2']\n", - " $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list) ['$6load_attr.2', '$8load_method.3']\n", - " $10load_global.4 = global(numba: ) ['$10load_global.4']\n", - " $12load_attr.5 = getattr(value=$10load_global.4, attr=types) ['$10load_global.4', '$12load_attr.5']\n", - " $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp) ['$12load_attr.5', '$14load_attr.6']\n", - " starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None) ['$14load_attr.6', '$8load_method.3', 'starts']\n", - " $22load_method.9 = getattr(value=starts, attr=append) ['$22load_method.9', 'starts']\n", - " $const24.10 = const(int, 0) ['$const24.10']\n", - " $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None) ['$22load_method.9', '$26call_method.11', '$const24.10']\n", - " $30load_global.12 = global(numba: ) ['$30load_global.12']\n", - " $32load_attr.13 = getattr(value=$30load_global.12, attr=typed) ['$30load_global.12', '$32load_attr.13']\n", - " $34load_attr.14 = getattr(value=$32load_attr.13, attr=List) ['$32load_attr.13', '$34load_attr.14']\n", - " $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list) ['$34load_attr.14', '$36load_method.15']\n", - " $38load_global.16 = global(numba: ) ['$38load_global.16']\n", - " $40load_attr.17 = getattr(value=$38load_global.16, attr=types) ['$38load_global.16', '$40load_attr.17']\n", - " $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp) ['$40load_attr.17', '$42load_attr.18']\n", - " stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None) ['$36load_method.15', '$42load_attr.18', 'stops']\n", - " $50load_method.21 = getattr(value=stops, attr=append) ['$50load_method.21', 'stops']\n", - " $54load_attr.23 = getattr(value=coords, attr=shape) ['$54load_attr.23', 'coords']\n", - " $const56.24 = const(int, 1) ['$const56.24']\n", - " $58binary_subscr.25 = getitem(value=$54load_attr.23, index=$const56.24, fn=) ['$54load_attr.23', '$58binary_subscr.25', '$const56.24']\n", - " $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None) ['$50load_method.21', '$58binary_subscr.25', '$60call_method.26']\n", - " $64load_global.27 = global(np: ) ['$64load_global.27']\n", - " $66load_method.28 = getattr(value=$64load_global.27, attr=intp) ['$64load_global.27', '$66load_method.28']\n", - " $70load_attr.30 = getattr(value=coords, attr=shape) ['$70load_attr.30', 'coords']\n", - " $const72.31 = const(int, 1) ['$const72.31']\n", - " $74binary_subscr.32 = getitem(value=$70load_attr.30, index=$const72.31, fn=) ['$70load_attr.30', '$74binary_subscr.32', '$const72.31']\n", - " n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None) ['$66load_method.28', '$74binary_subscr.32', 'n_matches']\n", - " i = const(int, 0) ['i']\n", - " $86load_global.36 = global(len: ) ['$86load_global.36']\n", - " $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None) ['$86load_global.36', '$90call_function.38', 'indices']\n", - " $92compare_op.39 = i < $90call_function.38 ['$90call_function.38', '$92compare_op.39', 'i']\n", - " bool94 = global(bool: ) ['bool94']\n", - " $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None) ['$92compare_op.39', '$94pred', 'bool94']\n", - " branch $94pred, 96, 234 ['$94pred']\n", - "label 96:\n", - " $96load_global.0 = global(len: ) ['$96load_global.0']\n", - " n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None) ['$96load_global.0', 'n_pairs', 'starts']\n", - " $104load_global.3 = global(len: ) ['$104load_global.3']\n", - " $106load_global.4 = global(range: ) ['$106load_global.4']\n", - " $const112.7 = const(int, 0) ['$const112.7']\n", - " $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)]) ['$114build_tuple.8', '$const112.7', 'i']\n", - " $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=) ['$114build_tuple.8', '$116binary_subscr.9', 'indices']\n", - " $const122.12 = const(int, 1) ['$const122.12']\n", - " $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)]) ['$124build_tuple.13', '$const122.12', 'i']\n", - " $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=) ['$124build_tuple.13', '$126binary_subscr.14', 'indices']\n", - " $const132.17 = const(int, 2) ['$const132.17']\n", - " $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)]) ['$134build_tuple.18', '$const132.17', 'i']\n", - " $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=) ['$134build_tuple.18', '$136binary_subscr.19', 'indices']\n", - " $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None) ['$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$136binary_subscr.19', '$138call_function.20']\n", - " $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None) ['$104load_global.3', '$138call_function.20', '$140call_function.21']\n", - " $144binary_multiply.23 = $140call_function.21 * n_pairs ['$140call_function.21', '$144binary_multiply.23', 'n_pairs']\n", - " $const146.24 = const(int, 2) ['$const146.24']\n", - " n_current_slices = $144binary_multiply.23 + $const146.24 ['$144binary_multiply.23', '$const146.24', 'n_current_slices']\n", - " $154load_global.27 = global(np: ) ['$154load_global.27']\n", - " $156load_method.28 = getattr(value=$154load_global.27, attr=log) ['$154load_global.27', '$156load_method.28']\n", - " $160load_global.30 = global(max: ) ['$160load_global.30']\n", - " $const164.32 = const(int, 1) ['$const164.32']\n", - " $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None) ['$160load_global.30', '$166call_function.33', '$const164.32', 'n_pairs']\n", - " $168binary_true_divide.34 = n_current_slices / $166call_function.33 ['$166call_function.33', '$168binary_true_divide.34', 'n_current_slices']\n", - " $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None) ['$156load_method.28', '$168binary_true_divide.34', '$170call_method.35']\n", - " $172binary_multiply.36 = n_current_slices * $170call_method.35 ['$170call_method.35', '$172binary_multiply.36', 'n_current_slices']\n", - " $178binary_add.39 = n_matches + n_pairs ['$178binary_add.39', 'n_matches', 'n_pairs']\n", - " $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39 ['$172binary_multiply.36', '$178binary_add.39', '$180compare_op.40']\n", - " bool182 = global(bool: ) ['bool182']\n", - " $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None) ['$180compare_op.40', '$182pred', 'bool182']\n", - " branch $182pred, 184, 186 ['$182pred']\n", - "label 184:\n", - " jump 234 []\n", - "label 186:\n", - " $186load_global.0 = global(_get_mask_pairs: CPUDispatcher()) ['$186load_global.0']\n", - " $196binary_subscr.5 = getitem(value=coords, index=i, fn=) ['$196binary_subscr.5', 'coords', 'i']\n", - " $202binary_subscr.8 = getitem(value=indices, index=i, fn=) ['$202binary_subscr.8', 'i', 'indices']\n", - " $204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None) ['$186load_global.0', '$196binary_subscr.5', '$202binary_subscr.8', '$204call_function.9', 'starts', 'stops']\n", - " $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3) ['$204call_function.9', '$206unpack_sequence.13']\n", - " $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=) ['$206unpack_sequence.10', '$206unpack_sequence.13']\n", - " $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=) ['$206unpack_sequence.11', '$206unpack_sequence.13']\n", - " $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=) ['$206unpack_sequence.12', '$206unpack_sequence.13']\n", - " starts = $206unpack_sequence.10 ['$206unpack_sequence.10', 'starts']\n", - " stops = $206unpack_sequence.11 ['$206unpack_sequence.11', 'stops']\n", - " n_matches = $206unpack_sequence.12 ['$206unpack_sequence.12', 'n_matches']\n", - " $const216.15 = const(int, 1) ['$const216.15']\n", - " $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined) ['$218inplace_add.16', '$const216.15', 'i']\n", - " i = $218inplace_add.16 ['$218inplace_add.16', 'i']\n", - " $224load_global.18 = global(len: ) ['$224load_global.18']\n", - " $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None) ['$224load_global.18', '$228call_function.20', 'indices']\n", - " $230compare_op.21 = i < $228call_function.20 ['$228call_function.20', '$230compare_op.21', 'i']\n", - " bool232 = global(bool: ) ['bool232']\n", - " $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None) ['$230compare_op.21', '$232pred', 'bool232']\n", - " branch $232pred, 96, 234 ['$232pred']\n", - "label 234:\n", - " $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher()) ['$234load_global.0']\n", - " $240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None) ['$234load_global.0', '$240call_function.3', 'starts', 'stops']\n", - " $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2) ['$240call_function.3', '$242unpack_sequence.6']\n", - " $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=) ['$242unpack_sequence.4', '$242unpack_sequence.6']\n", - " $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=) ['$242unpack_sequence.5', '$242unpack_sequence.6']\n", - " starts.1 = $242unpack_sequence.4 ['$242unpack_sequence.4', 'starts.1']\n", - " stops.1 = $242unpack_sequence.5 ['$242unpack_sequence.5', 'stops.1']\n", - " $250load_global.8 = global(len: ) ['$250load_global.8']\n", - " $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None) ['$250load_global.8', '$254call_function.10', 'indices']\n", - " $256compare_op.11 = i == $254call_function.10 ['$254call_function.10', '$256compare_op.11', 'i']\n", - " bool258 = global(bool: ) ['bool258']\n", - " $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None) ['$256compare_op.11', '$258pred', 'bool258']\n", - " branch $258pred, 260, 298 ['$258pred']\n", - "label 260:\n", - " $260load_global.0 = global(len: ) ['$260load_global.0']\n", - " $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None) ['$260load_global.0', '$264call_function.2', 'starts.1']\n", - " $const266.3 = const(int, 1) ['$const266.3']\n", - " $268compare_op.4 = $264call_function.2 == $const266.3 ['$264call_function.2', '$268compare_op.4', '$const266.3']\n", - " bool270 = global(bool: ) ['bool270']\n", - " $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None) ['$268compare_op.4', '$270pred', 'bool270']\n", - " branch $270pred, 272, 298 ['$270pred']\n", - "label 272:\n", - " $272load_global.0 = global(np: ) ['$272load_global.0']\n", - " $274load_method.1 = getattr(value=$272load_global.0, attr=array) ['$272load_global.0', '$274load_method.1']\n", - " $const278.3 = const(int, 0) ['$const278.3']\n", - " $280binary_subscr.4 = getitem(value=starts.1, index=$const278.3, fn=) ['$280binary_subscr.4', '$const278.3', 'starts.1']\n", - " $const284.6 = const(int, 0) ['$const284.6']\n", - " $286binary_subscr.7 = getitem(value=stops.1, index=$const284.6, fn=) ['$286binary_subscr.7', '$const284.6', 'stops.1']\n", - " $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)]) ['$280binary_subscr.4', '$286binary_subscr.7', '$288build_list.8']\n", - " $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None) ['$274load_method.1', '$288build_list.8', '$290call_method.9']\n", - " $const292.10 = const(bool, True) ['$const292.10']\n", - " $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)]) ['$290call_method.9', '$294build_tuple.11', '$const292.10']\n", - " $296return_value.12 = cast(value=$294build_tuple.11) ['$294build_tuple.11', '$296return_value.12']\n", - " return $296return_value.12 ['$296return_value.12']\n", - "label 298:\n", - " $298load_global.0 = global(_filter_pairs: CPUDispatcher()) ['$298load_global.0']\n", - " $const308.5 = const(NoneType, None) ['$const308.5']\n", - " $310build_slice.6 = global(slice: ) ['$310build_slice.6']\n", - " $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None) ['$310build_slice.6', '$310build_slice.7', '$const308.5', 'i']\n", - " $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=) ['$310build_slice.7', '$312binary_subscr.8', 'coords']\n", - " $const318.11 = const(NoneType, None) ['$const318.11']\n", - " $320build_slice.12 = global(slice: ) ['$320build_slice.12']\n", - " $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None) ['$320build_slice.12', '$320build_slice.13', '$const318.11', 'i']\n", - " $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=) ['$320build_slice.13', '$322binary_subscr.14', 'indices']\n", - " mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None) ['$298load_global.0', '$312binary_subscr.8', '$322binary_subscr.14', 'mask', 'starts.1', 'stops.1']\n", - " $328load_global.16 = global(array_from_list_intp: CPUDispatcher()) ['$328load_global.16']\n", - " $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None) ['$328load_global.16', '$332call_function.18', 'mask']\n", - " $const334.19 = const(bool, False) ['$const334.19']\n", - " $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)]) ['$332call_function.18', '$336build_tuple.20', '$const334.19']\n", - " $338return_value.21 = cast(value=$336build_tuple.20) ['$336build_tuple.20', '$338return_value.21']\n", - " return $338return_value.21 ['$338return_value.21']\n", - "\n", - "2024-09-12 10:50:37,394 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:37,395 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,396 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:37,397 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:37,398 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:37,398 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:37,399 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:37,400 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:37,400 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:37,401 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:37,402 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:37,403 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,403 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:37,404 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:37,405 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,405 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:37,406 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:37,407 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:37,408 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:37,408 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:37,409 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:37,410 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:37,410 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,411 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:37,412 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,413 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:37,414 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:37,414 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,415 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,416 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:37,416 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,426 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:37,427 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:37,427 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,428 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:37,429 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:37,429 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,430 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:37,431 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:37,432 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,432 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:37,433 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 96\n", - "2024-09-12 10:50:37,434 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,434 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,435 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,436 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:37,436 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:37,437 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:37,438 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:37,438 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:37,439 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:37,440 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:37,441 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:37,441 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:37,442 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:37,443 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:37,443 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,444 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,445 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:37,445 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:37,446 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:37,447 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,448 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:37,448 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:37,449 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:37,450 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,450 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:37,451 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,452 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:37,452 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:37,453 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:37,454 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:37,454 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,455 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:37,456 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 184\n", - "2024-09-12 10:50:37,456 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,457 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:37,458 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 186\n", - "2024-09-12 10:50:37,458 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,459 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,460 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:37,461 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:37,461 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,462 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:37,463 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,464 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,464 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:37,465 - numba.core.ssa - DEBUG - on stmt: starts = $206unpack_sequence.10\n", - "2024-09-12 10:50:37,466 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:37,466 - numba.core.ssa - DEBUG - on stmt: n_matches = $206unpack_sequence.12\n", - "2024-09-12 10:50:37,467 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:37,468 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:37,468 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:37,469 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:37,470 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,471 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:37,472 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:37,472 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,473 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:37,474 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 234\n", - "2024-09-12 10:50:37,474 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,475 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,476 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,477 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:37,477 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,478 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,479 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:37,480 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:37,480 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:37,481 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,482 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:37,482 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:37,483 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,484 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:37,485 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 260\n", - "2024-09-12 10:50:37,485 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,486 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,487 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,487 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:37,488 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:37,489 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:37,490 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,490 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:37,491 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 272\n", - "2024-09-12 10:50:37,492 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,492 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:37,493 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:37,494 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:37,495 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:37,495 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:37,496 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:37,497 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:37,497 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,498 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:37,499 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:37,500 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:37,500 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:37,501 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 298\n", - "2024-09-12 10:50:37,502 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,502 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,503 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:37,504 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:37,504 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,505 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:37,506 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:37,506 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:37,507 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,508 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:37,508 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,509 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:37,510 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,510 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:37,511 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:37,512 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:37,512 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:37,516 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$104load_global.3': [],\n", - " '$106load_global.4': [],\n", - " '$10load_global.4': [],\n", - " '$114build_tuple.8': [],\n", - " '$116binary_subscr.9': [],\n", - " '$124build_tuple.13': [],\n", - " '$126binary_subscr.14': [],\n", - " '$12load_attr.5': [],\n", - " '$134build_tuple.18': [],\n", - " '$136binary_subscr.19': [],\n", - " '$138call_function.20': [],\n", - " '$140call_function.21': [],\n", - " '$144binary_multiply.23': [],\n", - " '$14load_attr.6': [],\n", - " '$154load_global.27': [],\n", - " '$156load_method.28': [],\n", - " '$160load_global.30': [],\n", - " '$166call_function.33': [],\n", - " '$168binary_true_divide.34': [],\n", - " '$170call_method.35': [],\n", - " '$172binary_multiply.36': [],\n", - " '$178binary_add.39': [],\n", - " '$180compare_op.40': [],\n", - " '$182pred': [],\n", - " '$186load_global.0': [],\n", - " '$196binary_subscr.5': [],\n", - " '$202binary_subscr.8': [],\n", - " '$204call_function.9': [],\n", - " '$206unpack_sequence.10': [],\n", - " '$206unpack_sequence.11': [],\n", - " '$206unpack_sequence.12': [],\n", - " '$206unpack_sequence.13': [],\n", - " '$218inplace_add.16': [],\n", - " '$224load_global.18': [],\n", - " '$228call_function.20': [],\n", - " '$22load_method.9': [],\n", - " '$230compare_op.21': [],\n", - " '$232pred': [],\n", - " '$234load_global.0': [],\n", - " '$240call_function.3': [],\n", - " '$242unpack_sequence.4': [],\n", - " '$242unpack_sequence.5': [],\n", - " '$242unpack_sequence.6': [],\n", - " '$250load_global.8': [],\n", - " '$254call_function.10': [],\n", - " '$256compare_op.11': [],\n", - " '$258pred': [],\n", - " '$260load_global.0': [],\n", - " '$264call_function.2': [],\n", - " '$268compare_op.4': [],\n", - " '$26call_method.11': [],\n", - " '$270pred': [],\n", - " '$272load_global.0': [],\n", - " '$274load_method.1': [],\n", - " '$280binary_subscr.4': [],\n", - " '$286binary_subscr.7': [],\n", - " '$288build_list.8': [],\n", - " '$290call_method.9': [],\n", - " '$294build_tuple.11': [],\n", - " '$296return_value.12': [],\n", - " '$298load_global.0': [],\n", - " '$2load_global.0': [],\n", - " '$30load_global.12': [],\n", - " '$310build_slice.6': [],\n", - " '$310build_slice.7': [],\n", - " '$312binary_subscr.8': [],\n", - " '$320build_slice.12': [],\n", - " '$320build_slice.13': [],\n", - " '$322binary_subscr.14': [],\n", - " '$328load_global.16': [],\n", - " '$32load_attr.13': [],\n", - " '$332call_function.18': [],\n", - " '$336build_tuple.20': [],\n", - " '$338return_value.21': [],\n", - " '$34load_attr.14': [],\n", - " '$36load_method.15': [],\n", - " '$38load_global.16': [],\n", - " '$40load_attr.17': [],\n", - " '$42load_attr.18': [],\n", - " '$4load_attr.1': [],\n", - " '$50load_method.21': [],\n", - " '$54load_attr.23': [],\n", - " '$58binary_subscr.25': [],\n", - " '$60call_method.26': [],\n", - " '$64load_global.27': [],\n", - " '$66load_method.28': [],\n", - " '$6load_attr.2': [],\n", - " '$70load_attr.30': [],\n", - " '$74binary_subscr.32': [],\n", - " '$86load_global.36': [],\n", - " '$8load_method.3': [],\n", - " '$90call_function.38': [],\n", - " '$92compare_op.39': [],\n", - " '$94pred': [],\n", - " '$96load_global.0': [],\n", - " '$const112.7': [],\n", - " '$const122.12': [],\n", - " '$const132.17': [],\n", - " '$const146.24': [],\n", - " '$const164.32': [],\n", - " '$const216.15': [],\n", - " '$const24.10': [],\n", - " '$const266.3': [],\n", - " '$const278.3': [],\n", - " '$const284.6': [],\n", - " '$const292.10': [],\n", - " '$const308.5': [],\n", - " '$const318.11': [],\n", - " '$const334.19': [],\n", - " '$const56.24': [],\n", - " '$const72.31': [],\n", - " 'bool182': [],\n", - " 'bool232': [],\n", - " 'bool258': [],\n", - " 'bool270': [],\n", - " 'bool94': [],\n", - " 'coords': [],\n", - " 'i': [,\n", - " ],\n", - " 'indices': [],\n", - " 'mask': [],\n", - " 'n_current_slices': [],\n", - " 'n_matches': [,\n", - " ],\n", - " 'n_pairs': [],\n", - " 'starts': [,\n", - " ],\n", - " 'starts.1': [],\n", - " 'stops': [,\n", - " ],\n", - " 'stops.1': []})\n", - "2024-09-12 10:50:37,517 - numba.core.ssa - DEBUG - SSA violators {'starts', 'n_matches', 'i', 'stops'}\n", - "2024-09-12 10:50:37,518 - numba.core.ssa - DEBUG - Fix SSA violator on var starts\n", - "2024-09-12 10:50:37,518 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:37,519 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,520 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:37,520 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:37,521 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:37,522 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:37,522 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:37,523 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:37,524 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:37,524 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:37,525 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:37,526 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,526 - numba.core.ssa - DEBUG - first assign: starts\n", - "2024-09-12 10:50:37,527 - numba.core.ssa - DEBUG - replaced with: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,528 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:37,528 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:37,529 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,530 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:37,530 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:37,531 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:37,532 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:37,532 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:37,533 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:37,534 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:37,535 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,535 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:37,536 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,537 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:37,537 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:37,538 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,539 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,539 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:37,540 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,541 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:37,541 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:37,542 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,543 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:37,544 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:37,544 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,545 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:37,546 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:37,546 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,547 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:37,548 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:37,548 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,549 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,550 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,551 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:37,551 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:37,552 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:37,553 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:37,553 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:37,554 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:37,555 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:37,555 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:37,556 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:37,557 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:37,557 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:37,558 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,559 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,560 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:37,560 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:37,561 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:37,562 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,562 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:37,563 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:37,564 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:37,564 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,565 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:37,566 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,595 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:37,596 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:37,596 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:37,597 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:37,598 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,599 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:37,599 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:37,600 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,601 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:37,601 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:37,601 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,602 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,603 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:37,604 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:37,604 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,605 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:37,605 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,606 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,606 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:37,608 - numba.core.ssa - DEBUG - on stmt: starts = $206unpack_sequence.10\n", - "2024-09-12 10:50:37,608 - numba.core.ssa - DEBUG - replaced with: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:37,609 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:37,609 - numba.core.ssa - DEBUG - on stmt: n_matches = $206unpack_sequence.12\n", - "2024-09-12 10:50:37,610 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:37,610 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:37,611 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:37,612 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:37,613 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,613 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:37,614 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:37,614 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,615 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:37,615 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:37,616 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,616 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,617 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,618 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:37,619 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,619 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,620 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:37,621 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:37,621 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:37,622 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,622 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:37,623 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:37,624 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,624 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:37,625 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:37,625 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,626 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,626 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,628 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:37,628 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:37,629 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:37,629 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,630 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:37,631 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:37,631 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,632 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:37,633 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:37,633 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:37,634 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:37,634 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:37,635 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:37,635 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:37,636 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,636 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:37,637 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:37,639 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:37,639 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:37,640 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:37,640 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,641 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,641 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:37,642 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:37,642 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,643 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:37,643 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:37,644 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:37,644 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,645 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:37,645 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,646 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:37,646 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,647 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:37,647 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:37,650 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:37,651 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:37,651 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 186: []})\n", - "2024-09-12 10:50:37,652 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:37,653 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,654 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:37,654 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:37,655 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:37,656 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:37,656 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:37,657 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:37,657 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:37,658 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:37,658 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:37,659 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,660 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:37,661 - numba.core.ssa - DEBUG - find_def var='starts' stmt=$22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:37,661 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:37,662 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,662 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:37,663 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:37,663 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:37,665 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:37,665 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:37,666 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:37,666 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:37,667 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,668 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:37,668 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,669 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:37,669 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:37,670 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,670 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,671 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:37,671 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,673 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:37,674 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:37,674 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,675 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:37,675 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:37,676 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,676 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:37,678 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:37,678 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,679 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:37,680 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:37,680 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,681 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,681 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,682 - numba.core.ssa - DEBUG - find_def var='starts' stmt=n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,683 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:37,684 - numba.core.ssa - DEBUG - insert phi node starts.3 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:37,684 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:37,685 - numba.core.ssa - DEBUG - incoming_def starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,686 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:37,686 - numba.core.ssa - DEBUG - incoming_def starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:37,687 - numba.core.ssa - DEBUG - replaced with: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,687 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:37,688 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:37,688 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:37,690 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:37,690 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:37,691 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:37,691 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:37,692 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:37,692 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:37,693 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:37,694 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:37,695 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,696 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,696 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:37,697 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:37,697 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:37,698 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,699 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:37,700 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:37,700 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:37,701 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,702 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:37,702 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,703 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:37,703 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:37,704 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:37,704 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:37,705 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,705 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:37,707 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:37,708 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,708 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:37,709 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:37,710 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,710 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,711 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:37,711 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:37,712 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,712 - numba.core.ssa - DEBUG - find_def var='starts' stmt=$204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,713 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:37,714 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:37,715 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:37,715 - numba.core.ssa - DEBUG - replaced with: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,716 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:37,716 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,717 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,717 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:37,719 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:37,719 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:37,720 - numba.core.ssa - DEBUG - on stmt: n_matches = $206unpack_sequence.12\n", - "2024-09-12 10:50:37,720 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:37,721 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:37,721 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:37,722 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:37,723 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,724 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:37,724 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:37,725 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,726 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:37,726 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:37,727 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,727 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,728 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,729 - numba.core.ssa - DEBUG - find_def var='starts' stmt=$240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,730 - numba.core.ssa - DEBUG - find_def_from_top label 234\n", - "2024-09-12 10:50:37,730 - numba.core.ssa - DEBUG - insert phi node starts.4 = phi(incoming_values=[], incoming_blocks=[]) at 234\n", - "2024-09-12 10:50:37,731 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:37,732 - numba.core.ssa - DEBUG - incoming_def starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,732 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:37,733 - numba.core.ssa - DEBUG - incoming_def starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:37,733 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-09-12 10:50:37,734 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-09-12 10:50:37,735 - numba.core.ssa - DEBUG - idom 96 from label 184\n", - "2024-09-12 10:50:37,735 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:37,736 - numba.core.ssa - DEBUG - incoming_def starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:37,736 - numba.core.ssa - DEBUG - replaced with: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,737 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:37,738 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,739 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,739 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:37,740 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:37,741 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:37,741 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,742 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:37,742 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:37,743 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,743 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:37,744 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:37,744 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,746 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,746 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,747 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:37,747 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:37,748 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:37,749 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,750 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:37,750 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:37,751 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,751 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:37,752 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:37,752 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:37,753 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:37,753 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:37,755 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:37,755 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:37,756 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,756 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:37,757 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:37,757 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:37,758 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:37,759 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:37,760 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,760 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,761 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:37,762 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:37,762 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,763 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:37,764 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:37,764 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:37,765 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,765 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:37,766 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,767 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:37,767 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,768 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:37,769 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:37,769 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:37,770 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:37,771 - numba.core.ssa - DEBUG - Fix SSA violator on var n_matches\n", - "2024-09-12 10:50:37,771 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:37,772 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,772 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:37,773 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:37,773 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:37,774 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:37,775 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:37,776 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:37,776 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:37,777 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:37,777 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:37,778 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,779 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:37,779 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:37,780 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,780 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:37,781 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:37,782 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:37,782 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:37,782 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:37,783 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:37,783 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:37,785 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,786 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:37,786 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,787 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:37,787 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:37,788 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,789 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,789 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:37,790 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,791 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:37,791 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:37,792 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,792 - numba.core.ssa - DEBUG - first assign: n_matches\n", - "2024-09-12 10:50:37,793 - numba.core.ssa - DEBUG - replaced with: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,794 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:37,794 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:37,795 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,795 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:37,796 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:37,797 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,798 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:37,798 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:37,799 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,799 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:37,800 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,801 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,801 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:37,802 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:37,803 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:37,803 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:37,804 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:37,804 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:37,805 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:37,806 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:37,806 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:37,807 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:37,807 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:37,808 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,808 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,809 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:37,810 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:37,811 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:37,811 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,812 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:37,813 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:37,813 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:37,814 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,814 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:37,815 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,815 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:37,816 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:37,816 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:37,817 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:37,817 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,819 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:37,819 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:37,820 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,820 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:37,821 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:37,822 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,822 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,823 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:37,824 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:37,824 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,825 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:37,825 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,826 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,827 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:37,827 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:37,828 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:37,828 - numba.core.ssa - DEBUG - on stmt: n_matches = $206unpack_sequence.12\n", - "2024-09-12 10:50:37,829 - numba.core.ssa - DEBUG - replaced with: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:37,830 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:37,831 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:37,831 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:37,832 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:37,832 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,833 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:37,833 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:37,834 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,835 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:37,835 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:37,836 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,837 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:37,837 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,838 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,838 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:37,839 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,839 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,840 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:37,841 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:37,841 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:37,842 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,843 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:37,843 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:37,844 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,844 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:37,845 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:37,846 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,846 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,847 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,848 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:37,848 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:37,849 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:37,849 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,850 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:37,850 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:37,851 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,852 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:37,852 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:37,853 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:37,853 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:37,854 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:37,854 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:37,855 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:37,855 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,856 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:37,857 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:37,857 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:37,858 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:37,859 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:37,859 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,860 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,860 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:37,861 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:37,861 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,862 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:37,862 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:37,863 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:37,863 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,865 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:37,865 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,866 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:37,866 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,867 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:37,867 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:37,868 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:37,868 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:37,869 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 186: []})\n", - "2024-09-12 10:50:37,870 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:37,871 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,871 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:37,872 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:37,872 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:37,873 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:37,874 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:37,874 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:37,875 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:37,875 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:37,875 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:37,876 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,877 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:37,877 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:37,877 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,878 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:37,878 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:37,880 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:37,881 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:37,881 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:37,881 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:37,882 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:37,882 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,883 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:37,883 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,884 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:37,884 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:37,886 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,886 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,887 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:37,887 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,888 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:37,889 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:37,890 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,890 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:37,891 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:37,891 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,892 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:37,893 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:37,893 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,894 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:37,894 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:37,895 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,895 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:37,896 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,896 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,898 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:37,898 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:37,898 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:37,899 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:37,900 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:37,900 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:37,901 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:37,902 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:37,902 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:37,903 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:37,903 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:37,904 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,904 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,905 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:37,906 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:37,907 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:37,907 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,908 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:37,908 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:37,909 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:37,909 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,910 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:37,910 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,911 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:37,911 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:37,913 - numba.core.ssa - DEBUG - find_def var='n_matches' stmt=$178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:37,913 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:37,914 - numba.core.ssa - DEBUG - insert phi node n_matches.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:37,914 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:37,915 - numba.core.ssa - DEBUG - incoming_def n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,915 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:37,916 - numba.core.ssa - DEBUG - incoming_def n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:37,916 - numba.core.ssa - DEBUG - replaced with: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:37,917 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:37,917 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:37,918 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,918 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:37,920 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:37,920 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,921 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:37,921 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:37,922 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,922 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,922 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:37,923 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:37,923 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,924 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:37,926 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,926 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,927 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:37,927 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:37,928 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:37,928 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:37,929 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:37,929 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:37,930 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:37,933 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:37,934 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,934 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:37,935 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:37,936 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,936 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:37,937 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:37,937 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,938 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:37,939 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,939 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,940 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:37,940 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:37,941 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:37,941 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:37,942 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:37,943 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:37,943 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,944 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:37,944 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:37,945 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,945 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:37,946 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:37,946 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,947 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,947 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,948 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:37,948 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:37,949 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:37,949 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,950 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:37,950 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:37,952 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,953 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:37,953 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:37,954 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:37,954 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:37,955 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:37,955 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:37,956 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:37,956 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,957 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:37,958 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:37,959 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:37,959 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:37,960 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:37,960 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,960 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:37,961 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:37,962 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:37,963 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,963 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:37,964 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:37,965 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:37,965 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,966 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:37,966 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,967 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:37,968 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,968 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:37,969 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:37,969 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:37,970 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:37,970 - numba.core.ssa - DEBUG - Fix SSA violator on var i\n", - "2024-09-12 10:50:37,971 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:37,972 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,972 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:37,973 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:37,973 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:37,974 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:37,974 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:37,975 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:37,975 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:37,976 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:37,976 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:37,978 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,978 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:37,979 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:37,979 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,980 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:37,980 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:37,980 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:37,981 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:37,981 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:37,982 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:37,982 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:37,983 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,983 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:37,984 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,984 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:37,985 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:37,985 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,986 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:37,986 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:37,987 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:37,987 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:37,987 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:37,988 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,988 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:37,989 - numba.core.ssa - DEBUG - first assign: i\n", - "2024-09-12 10:50:37,992 - numba.core.ssa - DEBUG - replaced with: i = const(int, 0)\n", - "2024-09-12 10:50:37,992 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:37,993 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,993 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:37,994 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:37,994 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,995 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:37,995 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:37,996 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:37,996 - numba.core.ssa - DEBUG - on stmt: n_matches.2 = phi(incoming_values=[Var(n_matches, indexing.py:459), Var(n_matches.1, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:37,998 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:37,998 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:37,999 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:37,999 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:38,000 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:38,001 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:38,001 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:38,002 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:38,003 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:38,003 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:38,004 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:38,004 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:38,005 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:38,005 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:38,006 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,006 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,007 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:38,007 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:38,008 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:38,008 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:38,010 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:38,010 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:38,011 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:38,011 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,012 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:38,013 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,013 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:38,014 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:38,015 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:38,015 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:38,016 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,016 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:38,017 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:38,018 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,018 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:38,019 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:38,019 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,020 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,020 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:38,020 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:38,022 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,022 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:38,023 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:38,023 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:38,024 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:38,024 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:38,025 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:38,025 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:38,026 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:38,027 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:38,027 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:38,028 - numba.core.ssa - DEBUG - replaced with: i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:38,028 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:38,029 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,030 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:38,031 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:38,031 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,032 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:38,032 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:38,032 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,033 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:38,033 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,034 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,034 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:38,035 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:38,035 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:38,037 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:38,038 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:38,038 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:38,038 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,039 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:38,040 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:38,040 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,041 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:38,041 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:38,042 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,043 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:38,044 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,044 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:38,045 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:38,045 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:38,046 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,047 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:38,047 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:38,047 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,048 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:38,049 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:38,049 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:38,050 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:38,051 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:38,051 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:38,052 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:38,052 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,053 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:38,054 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:38,054 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:38,055 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:38,056 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:38,056 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,057 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,057 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:38,058 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:38,058 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,059 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:38,060 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:38,060 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:38,061 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,061 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:38,062 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,063 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:38,063 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,064 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:38,064 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:38,065 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:38,065 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:38,067 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 186: []})\n", - "2024-09-12 10:50:38,067 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:38,068 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,068 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:38,069 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:38,069 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:38,069 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:38,070 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:38,070 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:38,071 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:38,072 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:38,073 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:38,073 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,074 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:38,075 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:38,075 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,076 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:38,077 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:38,077 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:38,078 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:38,079 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:38,079 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:38,080 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:38,080 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,081 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:38,081 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:38,082 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:38,083 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:38,083 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,084 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:38,084 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:38,085 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:38,086 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:38,086 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:38,087 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,088 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:38,088 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:38,089 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,089 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:38,090 - numba.core.ssa - DEBUG - find_def var='i' stmt=$92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:38,091 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:38,091 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,092 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:38,093 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:38,093 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,094 - numba.core.ssa - DEBUG - on stmt: n_matches.2 = phi(incoming_values=[Var(n_matches, indexing.py:459), Var(n_matches.1, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,094 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,095 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:38,096 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,096 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:38,096 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:38,099 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:38,099 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:38,100 - numba.core.ssa - DEBUG - find_def var='i' stmt=$114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:38,100 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:38,102 - numba.core.ssa - DEBUG - insert phi node i.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:38,102 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:38,103 - numba.core.ssa - DEBUG - incoming_def i = const(int, 0)\n", - "2024-09-12 10:50:38,103 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:38,104 - numba.core.ssa - DEBUG - incoming_def i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:38,104 - numba.core.ssa - DEBUG - replaced with: $114build_tuple.8 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:38,105 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:38,106 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:38,106 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:38,107 - numba.core.ssa - DEBUG - find_def var='i' stmt=$124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:38,107 - numba.core.ssa - DEBUG - replaced with: $124build_tuple.13 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:38,108 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:38,109 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:38,110 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:38,110 - numba.core.ssa - DEBUG - find_def var='i' stmt=$134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:38,111 - numba.core.ssa - DEBUG - replaced with: $134build_tuple.18 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:38,112 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:38,112 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,113 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,114 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:38,114 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:38,115 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:38,115 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:38,116 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:38,117 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:38,117 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:38,118 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,118 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:38,119 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,119 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:38,122 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:38,122 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:38,123 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:38,123 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,124 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:38,124 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:38,125 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,125 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:38,126 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:38,126 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,127 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,127 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:38,127 - numba.core.ssa - DEBUG - find_def var='i' stmt=$196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:38,128 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:38,128 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:38,129 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:38,129 - numba.core.ssa - DEBUG - replaced with: $196binary_subscr.5 = getitem(value=coords, index=i.2, fn=)\n", - "2024-09-12 10:50:38,130 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:38,130 - numba.core.ssa - DEBUG - find_def var='i' stmt=$202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:38,131 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:38,131 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:38,132 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:38,135 - numba.core.ssa - DEBUG - replaced with: $202binary_subscr.8 = getitem(value=indices, index=i.2, fn=)\n", - "2024-09-12 10:50:38,136 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,136 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:38,137 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:38,138 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:38,139 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:38,139 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:38,140 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:38,140 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:38,141 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:38,141 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:38,142 - numba.core.ssa - DEBUG - find_def var='i' stmt=$218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:38,143 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:38,143 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:38,144 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:38,145 - numba.core.ssa - DEBUG - replaced with: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i.2, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:38,145 - numba.core.ssa - DEBUG - on stmt: i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:38,146 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:38,146 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,147 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:38,148 - numba.core.ssa - DEBUG - find_def var='i' stmt=$230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:38,148 - numba.core.ssa - DEBUG - replaced with: $230compare_op.21 = i.1 < $228call_function.20\n", - "2024-09-12 10:50:38,149 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:38,150 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,150 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:38,151 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:38,151 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,152 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:38,156 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,156 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,157 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:38,157 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:38,158 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:38,159 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:38,159 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:38,159 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:38,160 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,161 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:38,162 - numba.core.ssa - DEBUG - find_def var='i' stmt=$256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:38,162 - numba.core.ssa - DEBUG - find_def_from_top label 234\n", - "2024-09-12 10:50:38,163 - numba.core.ssa - DEBUG - insert phi node i.3 = phi(incoming_values=[], incoming_blocks=[]) at 234\n", - "2024-09-12 10:50:38,163 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:38,164 - numba.core.ssa - DEBUG - incoming_def i = const(int, 0)\n", - "2024-09-12 10:50:38,165 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:38,165 - numba.core.ssa - DEBUG - incoming_def i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:38,166 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-09-12 10:50:38,166 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-09-12 10:50:38,167 - numba.core.ssa - DEBUG - idom 96 from label 184\n", - "2024-09-12 10:50:38,167 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:38,168 - numba.core.ssa - DEBUG - incoming_def i.2 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,168 - numba.core.ssa - DEBUG - replaced with: $256compare_op.11 = i.3 == $254call_function.10\n", - "2024-09-12 10:50:38,169 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:38,169 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,171 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:38,171 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:38,172 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,172 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:38,173 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,173 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:38,174 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:38,174 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:38,175 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,175 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:38,177 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:38,177 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,177 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:38,178 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:38,178 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:38,179 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:38,179 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:38,180 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:38,180 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:38,181 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,181 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:38,182 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:38,182 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:38,183 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:38,183 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:38,184 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,186 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,186 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:38,187 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:38,187 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,188 - numba.core.ssa - DEBUG - find_def var='i' stmt=$310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,189 - numba.core.ssa - DEBUG - find_def_from_top label 298\n", - "2024-09-12 10:50:38,189 - numba.core.ssa - DEBUG - idom 234 from label 298\n", - "2024-09-12 10:50:38,190 - numba.core.ssa - DEBUG - find_def_from_bottom label 234\n", - "2024-09-12 10:50:38,190 - numba.core.ssa - DEBUG - replaced with: $310build_slice.7 = call $310build_slice.6(i.3, $const308.5, func=$310build_slice.6, args=(Var(i.3, indexing.py:482), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,191 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:38,192 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:38,192 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:38,193 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,193 - numba.core.ssa - DEBUG - find_def var='i' stmt=$320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,194 - numba.core.ssa - DEBUG - find_def_from_top label 298\n", - "2024-09-12 10:50:38,195 - numba.core.ssa - DEBUG - idom 234 from label 298\n", - "2024-09-12 10:50:38,195 - numba.core.ssa - DEBUG - find_def_from_bottom label 234\n", - "2024-09-12 10:50:38,196 - numba.core.ssa - DEBUG - replaced with: $320build_slice.13 = call $320build_slice.12(i.3, $const318.11, func=$320build_slice.12, args=(Var(i.3, indexing.py:482), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,197 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:38,197 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,198 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:38,199 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,200 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:38,200 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:38,201 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:38,201 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:38,202 - numba.core.ssa - DEBUG - Fix SSA violator on var stops\n", - "2024-09-12 10:50:38,202 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:38,203 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,204 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:38,204 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:38,205 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:38,206 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:38,206 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:38,207 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:38,207 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:38,208 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:38,208 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:38,209 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,210 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:38,210 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:38,211 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,211 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:38,212 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:38,212 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:38,213 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:38,214 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:38,214 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:38,215 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:38,216 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,216 - numba.core.ssa - DEBUG - first assign: stops\n", - "2024-09-12 10:50:38,217 - numba.core.ssa - DEBUG - replaced with: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,217 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:38,218 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:38,218 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:38,219 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:38,220 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,220 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:38,221 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:38,222 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:38,222 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:38,222 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:38,223 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,224 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:38,224 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:38,225 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,226 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:38,226 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:38,226 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,227 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:38,227 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:38,228 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,229 - numba.core.ssa - DEBUG - on stmt: i.2 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,230 - numba.core.ssa - DEBUG - on stmt: n_matches.2 = phi(incoming_values=[Var(n_matches, indexing.py:459), Var(n_matches.1, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,230 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,231 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:38,232 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,232 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:38,233 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:38,233 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:38,234 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:38,235 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:38,235 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:38,236 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:38,236 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:38,237 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:38,237 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:38,238 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:38,238 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,239 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,240 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:38,241 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:38,241 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:38,242 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:38,242 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:38,243 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:38,244 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:38,244 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,245 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:38,245 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,245 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:38,247 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:38,247 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:38,247 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:38,248 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,249 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:38,249 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:38,250 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,250 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:38,251 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:38,251 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,251 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,252 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i.2, fn=)\n", - "2024-09-12 10:50:38,253 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i.2, fn=)\n", - "2024-09-12 10:50:38,254 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,254 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:38,255 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:38,256 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:38,256 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:38,257 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:38,257 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:38,258 - numba.core.ssa - DEBUG - replaced with: stops.2 = $206unpack_sequence.11\n", - "2024-09-12 10:50:38,258 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:38,259 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:38,260 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i.2, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:38,260 - numba.core.ssa - DEBUG - on stmt: i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:38,261 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:38,261 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,262 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i.1 < $228call_function.20\n", - "2024-09-12 10:50:38,263 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:38,263 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,264 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:38,264 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:38,265 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,265 - numba.core.ssa - DEBUG - on stmt: i.3 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479), Var(i.2, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:38,266 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:38,266 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,267 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,267 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:38,269 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:38,269 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:38,270 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:38,270 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:38,271 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:38,271 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,272 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i.3 == $254call_function.10\n", - "2024-09-12 10:50:38,272 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:38,273 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,273 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:38,274 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:38,274 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,276 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:38,276 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,277 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:38,277 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:38,278 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:38,278 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,279 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:38,280 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:38,280 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,281 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:38,281 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:38,282 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:38,283 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:38,283 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:38,284 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:38,285 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:38,285 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,286 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:38,286 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:38,287 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:38,288 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:38,288 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:38,289 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,290 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,290 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:38,291 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:38,291 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i.3, $const308.5, func=$310build_slice.6, args=(Var(i.3, indexing.py:482), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,292 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:38,293 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:38,293 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:38,294 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i.3, $const318.11, func=$320build_slice.12, args=(Var(i.3, indexing.py:482), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,294 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:38,295 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,296 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:38,296 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,297 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:38,297 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:38,298 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:38,298 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:38,299 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 186: []})\n", - "2024-09-12 10:50:38,300 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:38,301 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,301 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:38,301 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:38,302 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:38,302 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:38,303 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:38,304 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:38,304 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:38,305 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:38,305 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:38,306 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,307 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:38,307 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:38,308 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,308 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:38,309 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:38,310 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:38,310 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:38,311 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:38,312 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:38,312 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:38,313 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,314 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:38,314 - numba.core.ssa - DEBUG - find_def var='stops' stmt=$50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:38,315 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:38,316 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:38,316 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:38,317 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,317 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:38,318 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:38,318 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:38,319 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:38,319 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:38,320 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,320 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:38,321 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:38,322 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,322 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:38,323 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:38,324 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,325 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:38,325 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:38,326 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,326 - numba.core.ssa - DEBUG - on stmt: i.2 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,327 - numba.core.ssa - DEBUG - on stmt: n_matches.2 = phi(incoming_values=[Var(n_matches, indexing.py:459), Var(n_matches.1, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,328 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,328 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:38,329 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,330 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:38,330 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:38,331 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:38,331 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:38,332 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:38,332 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:38,333 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:38,334 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:38,334 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:38,335 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:38,335 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:38,336 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,337 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,337 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:38,338 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:38,339 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:38,339 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:38,340 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:38,340 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:38,341 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:38,342 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,342 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:38,343 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,344 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:38,344 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:38,345 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:38,345 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:38,346 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,347 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:38,347 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:38,348 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,348 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:38,349 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:38,350 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,350 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,351 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i.2, fn=)\n", - "2024-09-12 10:50:38,351 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i.2, fn=)\n", - "2024-09-12 10:50:38,352 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,353 - numba.core.ssa - DEBUG - find_def var='stops' stmt=$204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,353 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:38,354 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:38,355 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:38,355 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:38,356 - numba.core.ssa - DEBUG - insert phi node stops.3 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:38,356 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:38,356 - numba.core.ssa - DEBUG - incoming_def stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,357 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:38,357 - numba.core.ssa - DEBUG - incoming_def stops.2 = $206unpack_sequence.11\n", - "2024-09-12 10:50:38,358 - numba.core.ssa - DEBUG - replaced with: $204call_function.9 = call $186load_global.0(starts.3, stops.3, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops.3, indexing.py:477), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,359 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:38,359 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:38,360 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:38,361 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:38,362 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:38,362 - numba.core.ssa - DEBUG - on stmt: stops.2 = $206unpack_sequence.11\n", - "2024-09-12 10:50:38,363 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:38,363 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:38,364 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i.2, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:38,365 - numba.core.ssa - DEBUG - on stmt: i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:38,365 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:38,366 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,366 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i.1 < $228call_function.20\n", - "2024-09-12 10:50:38,367 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:38,368 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,368 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:38,369 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:38,369 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,370 - numba.core.ssa - DEBUG - on stmt: i.3 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479), Var(i.2, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:38,371 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:38,371 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,372 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,373 - numba.core.ssa - DEBUG - find_def var='stops' stmt=$240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,373 - numba.core.ssa - DEBUG - find_def_from_top label 234\n", - "2024-09-12 10:50:38,374 - numba.core.ssa - DEBUG - insert phi node stops.4 = phi(incoming_values=[], incoming_blocks=[]) at 234\n", - "2024-09-12 10:50:38,374 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:38,375 - numba.core.ssa - DEBUG - incoming_def stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,375 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:38,376 - numba.core.ssa - DEBUG - incoming_def stops.2 = $206unpack_sequence.11\n", - "2024-09-12 10:50:38,376 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-09-12 10:50:38,376 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-09-12 10:50:38,377 - numba.core.ssa - DEBUG - idom 96 from label 184\n", - "2024-09-12 10:50:38,378 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:38,379 - numba.core.ssa - DEBUG - incoming_def stops.3 = phi(incoming_values=[Var(stops, indexing.py:457), Var(stops.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:38,379 - numba.core.ssa - DEBUG - replaced with: $240call_function.3 = call $234load_global.0(starts.4, stops.4, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops.4, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,380 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:38,381 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:38,381 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:38,382 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:38,382 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:38,383 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:38,384 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,384 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i.3 == $254call_function.10\n", - "2024-09-12 10:50:38,385 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:38,386 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,386 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:38,387 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:38,387 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,388 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:38,388 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,389 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:38,390 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:38,390 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:38,391 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,392 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:38,392 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:38,393 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,393 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:38,393 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:38,395 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:38,395 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:38,395 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:38,396 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:38,397 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:38,397 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,398 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:38,399 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:38,399 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:38,400 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:38,401 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:38,401 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,402 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:38,402 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:38,403 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:38,404 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i.3, $const308.5, func=$310build_slice.6, args=(Var(i.3, indexing.py:482), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,404 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:38,405 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:38,405 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:38,406 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i.3, $const318.11, func=$320build_slice.12, args=(Var(i.3, indexing.py:482), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,406 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:38,407 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,408 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:38,408 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,409 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:38,410 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:38,410 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:38,411 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:38,438 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=451)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=452)\n", - " 4\tLOAD_ATTR(arg=1, lineno=452)\n", - " 6\tLOAD_FAST(arg=1, lineno=452)\n", - " 8\tLOAD_FAST(arg=2, lineno=452)\n", - " 10\tLOAD_CONST(arg=1, lineno=452)\n", - " 12\tCALL_FUNCTION_KW(arg=2, lineno=452)\n", - " 14\tRETURN_VALUE(arg=None, lineno=452)\n", - "2024-09-12 10:50:38,439 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:38,440 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,440 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:38,441 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=451)\n", - "2024-09-12 10:50:38,442 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,442 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=452)\n", - "2024-09-12 10:50:38,443 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,443 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=452)\n", - "2024-09-12 10:50:38,444 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:38,445 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=452)\n", - "2024-09-12 10:50:38,446 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-09-12 10:50:38,446 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_FAST(arg=2, lineno=452)\n", - "2024-09-12 10:50:38,447 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$item_type6.2']\n", - "2024-09-12 10:50:38,447 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_CONST(arg=1, lineno=452)\n", - "2024-09-12 10:50:38,448 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$item_type6.2', '$allocated8.3']\n", - "2024-09-12 10:50:38,449 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=CALL_FUNCTION_KW(arg=2, lineno=452)\n", - "2024-09-12 10:50:38,449 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$item_type6.2', '$allocated8.3', '$const10.4']\n", - "2024-09-12 10:50:38,450 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=RETURN_VALUE(arg=None, lineno=452)\n", - "2024-09-12 10:50:38,451 - numba.core.byteflow - DEBUG - stack ['$12call_function_kw.5']\n", - "2024-09-12 10:50:38,451 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:38,452 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:38,453 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:38,453 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:38,454 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:38,455 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:38,455 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:38,456 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:38,456 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:38,457 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'res': '$item_type6.2'}), (8, {'res': '$allocated8.3'}), (10, {'res': '$const10.4'}), (12, {'func': '$4load_attr.1', 'args': ['$item_type6.2', '$allocated8.3'], 'names': '$const10.4', 'res': '$12call_function_kw.5'}), (14, {'retval': '$12call_function_kw.5', 'castval': '$14return_value.6'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:38,459 - numba.core.interpreter - DEBUG - label 0:\n", - " cls = arg(0, name=cls) ['cls']\n", - " item_type = arg(1, name=item_type) ['item_type']\n", - " allocated = arg(2, name=allocated) ['allocated']\n", - " $2load_global.0 = global(listobject: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=new_list) ['$2load_global.0', '$4load_attr.1']\n", - " $12call_function_kw.5 = call $4load_attr.1(item_type, func=$4load_attr.1, args=[Var(item_type, typedlist.py:451)], kws=[('allocated', Var(allocated, typedlist.py:451))], vararg=None, varkwarg=None, target=None) ['$12call_function_kw.5', '$4load_attr.1', 'allocated', 'item_type']\n", - " $14return_value.6 = cast(value=$12call_function_kw.5) ['$12call_function_kw.5', '$14return_value.6']\n", - " return $14return_value.6 ['$14return_value.6']\n", - "\n", - "2024-09-12 10:50:38,473 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:38,474 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,475 - numba.core.ssa - DEBUG - on stmt: cls = arg(0, name=cls)\n", - "2024-09-12 10:50:38,475 - numba.core.ssa - DEBUG - on stmt: item_type = arg(1, name=item_type)\n", - "2024-09-12 10:50:38,476 - numba.core.ssa - DEBUG - on stmt: allocated = arg(2, name=allocated)\n", - "2024-09-12 10:50:38,476 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(listobject: )\n", - "2024-09-12 10:50:38,477 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=new_list)\n", - "2024-09-12 10:50:38,478 - numba.core.ssa - DEBUG - on stmt: $12call_function_kw.5 = call $4load_attr.1(item_type, func=$4load_attr.1, args=[Var(item_type, typedlist.py:451)], kws=[('allocated', Var(allocated, typedlist.py:451))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,478 - numba.core.ssa - DEBUG - on stmt: $14return_value.6 = cast(value=$12call_function_kw.5)\n", - "2024-09-12 10:50:38,479 - numba.core.ssa - DEBUG - on stmt: return $14return_value.6\n", - "2024-09-12 10:50:38,480 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12call_function_kw.5': [],\n", - " '$14return_value.6': [],\n", - " '$2load_global.0': [],\n", - " '$4load_attr.1': [],\n", - " 'allocated': [],\n", - " 'cls': [],\n", - " 'item_type': []})\n", - "2024-09-12 10:50:38,481 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:38,488 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=391)\n", - " 2\tLOAD_FAST(arg=1, lineno=392)\n", - " 4\tLOAD_CONST(arg=1, lineno=392)\n", - " 6\tCOMPARE_OP(arg=0, lineno=392)\n", - " 8\tPOP_JUMP_IF_FALSE(arg=10, lineno=392)\n", - " 10\tLOAD_GLOBAL(arg=0, lineno=393)\n", - " 12\tLOAD_CONST(arg=2, lineno=393)\n", - " 14\tCALL_FUNCTION(arg=1, lineno=393)\n", - " 16\tRAISE_VARARGS(arg=1, lineno=393)\n", - "> 18\tLOAD_GLOBAL(arg=1, lineno=394)\n", - " 20\tLOAD_DEREF(arg=0, lineno=394)\n", - " 22\tLOAD_FAST(arg=1, lineno=394)\n", - " 24\tCALL_FUNCTION(arg=2, lineno=394)\n", - " 26\tSTORE_FAST(arg=2, lineno=394)\n", - " 28\tLOAD_GLOBAL(arg=2, lineno=395)\n", - " 30\tLOAD_FAST(arg=2, lineno=395)\n", - " 32\tLOAD_DEREF(arg=0, lineno=395)\n", - " 34\tCALL_FUNCTION(arg=2, lineno=395)\n", - " 36\tPOP_TOP(arg=None, lineno=395)\n", - " 38\tLOAD_GLOBAL(arg=3, lineno=396)\n", - " 40\tLOAD_DEREF(arg=0, lineno=396)\n", - " 42\tLOAD_FAST(arg=2, lineno=396)\n", - " 44\tCALL_FUNCTION(arg=2, lineno=396)\n", - " 46\tSTORE_FAST(arg=3, lineno=396)\n", - " 48\tLOAD_FAST(arg=3, lineno=397)\n", - " 50\tRETURN_VALUE(arg=None, lineno=397)\n", - "2024-09-12 10:50:38,489 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:38,490 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,491 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:38,491 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=391)\n", - "2024-09-12 10:50:38,492 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,492 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=1, lineno=392)\n", - "2024-09-12 10:50:38,493 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,493 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_CONST(arg=1, lineno=392)\n", - "2024-09-12 10:50:38,494 - numba.core.byteflow - DEBUG - stack ['$allocated2.0']\n", - "2024-09-12 10:50:38,495 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=COMPARE_OP(arg=0, lineno=392)\n", - "2024-09-12 10:50:38,495 - numba.core.byteflow - DEBUG - stack ['$allocated2.0', '$const4.1']\n", - "2024-09-12 10:50:38,496 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=POP_JUMP_IF_FALSE(arg=10, lineno=392)\n", - "2024-09-12 10:50:38,496 - numba.core.byteflow - DEBUG - stack ['$6compare_op.2']\n", - "2024-09-12 10:50:38,497 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=10, stack=(), blockstack=(), npush=0), Edge(pc=18, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:38,497 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=10 nstack_initial=0), State(pc_initial=18 nstack_initial=0)])\n", - "2024-09-12 10:50:38,498 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,499 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=10 nstack_initial=0)\n", - "2024-09-12 10:50:38,500 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=0, lineno=393)\n", - "2024-09-12 10:50:38,500 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,501 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_CONST(arg=2, lineno=393)\n", - "2024-09-12 10:50:38,502 - numba.core.byteflow - DEBUG - stack ['$10load_global.0']\n", - "2024-09-12 10:50:38,502 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=CALL_FUNCTION(arg=1, lineno=393)\n", - "2024-09-12 10:50:38,503 - numba.core.byteflow - DEBUG - stack ['$10load_global.0', '$const12.1']\n", - "2024-09-12 10:50:38,503 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=RAISE_VARARGS(arg=1, lineno=393)\n", - "2024-09-12 10:50:38,504 - numba.core.byteflow - DEBUG - stack ['$14call_function.2']\n", - "2024-09-12 10:50:38,504 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:38,505 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=18 nstack_initial=0)])\n", - "2024-09-12 10:50:38,505 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,506 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=18 nstack_initial=0)\n", - "2024-09-12 10:50:38,506 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_GLOBAL(arg=1, lineno=394)\n", - "2024-09-12 10:50:38,507 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,508 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_DEREF(arg=0, lineno=394)\n", - "2024-09-12 10:50:38,509 - numba.core.byteflow - DEBUG - stack ['$18load_global.0']\n", - "2024-09-12 10:50:38,509 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=1, lineno=394)\n", - "2024-09-12 10:50:38,510 - numba.core.byteflow - DEBUG - stack ['$18load_global.0', '$20load_deref.1']\n", - "2024-09-12 10:50:38,510 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=CALL_FUNCTION(arg=2, lineno=394)\n", - "2024-09-12 10:50:38,511 - numba.core.byteflow - DEBUG - stack ['$18load_global.0', '$20load_deref.1', '$allocated22.2']\n", - "2024-09-12 10:50:38,512 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=STORE_FAST(arg=2, lineno=394)\n", - "2024-09-12 10:50:38,512 - numba.core.byteflow - DEBUG - stack ['$24call_function.3']\n", - "2024-09-12 10:50:38,513 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_GLOBAL(arg=2, lineno=395)\n", - "2024-09-12 10:50:38,513 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,514 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_FAST(arg=2, lineno=395)\n", - "2024-09-12 10:50:38,515 - numba.core.byteflow - DEBUG - stack ['$28load_global.4']\n", - "2024-09-12 10:50:38,516 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_DEREF(arg=0, lineno=395)\n", - "2024-09-12 10:50:38,516 - numba.core.byteflow - DEBUG - stack ['$28load_global.4', '$lp30.5']\n", - "2024-09-12 10:50:38,517 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=CALL_FUNCTION(arg=2, lineno=395)\n", - "2024-09-12 10:50:38,517 - numba.core.byteflow - DEBUG - stack ['$28load_global.4', '$lp30.5', '$32load_deref.6']\n", - "2024-09-12 10:50:38,518 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=POP_TOP(arg=None, lineno=395)\n", - "2024-09-12 10:50:38,519 - numba.core.byteflow - DEBUG - stack ['$34call_function.7']\n", - "2024-09-12 10:50:38,519 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_GLOBAL(arg=3, lineno=396)\n", - "2024-09-12 10:50:38,520 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,520 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_DEREF(arg=0, lineno=396)\n", - "2024-09-12 10:50:38,521 - numba.core.byteflow - DEBUG - stack ['$38load_global.8']\n", - "2024-09-12 10:50:38,522 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_FAST(arg=2, lineno=396)\n", - "2024-09-12 10:50:38,522 - numba.core.byteflow - DEBUG - stack ['$38load_global.8', '$40load_deref.9']\n", - "2024-09-12 10:50:38,523 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=CALL_FUNCTION(arg=2, lineno=396)\n", - "2024-09-12 10:50:38,524 - numba.core.byteflow - DEBUG - stack ['$38load_global.8', '$40load_deref.9', '$lp42.10']\n", - "2024-09-12 10:50:38,524 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=STORE_FAST(arg=3, lineno=396)\n", - "2024-09-12 10:50:38,525 - numba.core.byteflow - DEBUG - stack ['$44call_function.11']\n", - "2024-09-12 10:50:38,525 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_FAST(arg=3, lineno=397)\n", - "2024-09-12 10:50:38,526 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,526 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=RETURN_VALUE(arg=None, lineno=397)\n", - "2024-09-12 10:50:38,527 - numba.core.byteflow - DEBUG - stack ['$l48.12']\n", - "2024-09-12 10:50:38,527 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:38,528 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:38,528 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=10 nstack_initial=0): set(),\n", - " State(pc_initial=18 nstack_initial=0): set()})\n", - "2024-09-12 10:50:38,529 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:38,529 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:38,530 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:38,532 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:38,532 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:38,533 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:38,533 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$allocated2.0'}), (4, {'res': '$const4.1'}), (6, {'lhs': '$allocated2.0', 'rhs': '$const4.1', 'res': '$6compare_op.2'}), (8, {'pred': '$6compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={10: (), 18: ()})\n", - "2024-09-12 10:50:38,534 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=10 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((10, {'res': '$10load_global.0'}), (12, {'res': '$const12.1'}), (14, {'func': '$10load_global.0', 'args': ['$const12.1'], 'res': '$14call_function.2'}), (16, {'exc': '$14call_function.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:38,534 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=18 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((18, {'res': '$18load_global.0'}), (20, {'res': '$20load_deref.1'}), (22, {'res': '$allocated22.2'}), (24, {'func': '$18load_global.0', 'args': ['$20load_deref.1', '$allocated22.2'], 'res': '$24call_function.3'}), (26, {'value': '$24call_function.3'}), (28, {'res': '$28load_global.4'}), (30, {'res': '$lp30.5'}), (32, {'res': '$32load_deref.6'}), (34, {'func': '$28load_global.4', 'args': ['$lp30.5', '$32load_deref.6'], 'res': '$34call_function.7'}), (38, {'res': '$38load_global.8'}), (40, {'res': '$40load_deref.9'}), (42, {'res': '$lp42.10'}), (44, {'func': '$38load_global.8', 'args': ['$40load_deref.9', '$lp42.10'], 'res': '$44call_function.11'}), (46, {'value': '$44call_function.11'}), (48, {'res': '$l48.12'}), (50, {'retval': '$l48.12', 'castval': '$50return_value.13'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:38,537 - numba.core.interpreter - DEBUG - label 0:\n", - " item = arg(0, name=item) ['item']\n", - " allocated = arg(1, name=allocated) ['allocated']\n", - " $const4.1 = const(int, 0) ['$const4.1']\n", - " $6compare_op.2 = allocated < $const4.1 ['$6compare_op.2', '$const4.1', 'allocated']\n", - " bool8 = global(bool: ) ['bool8']\n", - " $8pred = call bool8($6compare_op.2, func=bool8, args=(Var($6compare_op.2, listobject.py:392),), kws=(), vararg=None, varkwarg=None, target=None) ['$6compare_op.2', '$8pred', 'bool8']\n", - " branch $8pred, 10, 18 ['$8pred']\n", - "label 10:\n", - " $10load_global.0 = global(RuntimeError: ) ['$10load_global.0']\n", - " $const12.1 = const(str, expecting *allocated* to be >= 0) ['$const12.1']\n", - " $14call_function.2 = call $10load_global.0($const12.1, func=$10load_global.0, args=[Var($const12.1, listobject.py:393)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_global.0', '$14call_function.2', '$const12.1']\n", - " raise $14call_function.2 ['$14call_function.2']\n", - "label 18:\n", - " $18load_global.0 = global(_list_new: ) ['$18load_global.0']\n", - " $20load_deref.1 = freevar(itemty: class(int64)) ['$20load_deref.1']\n", - " lp = call $18load_global.0($20load_deref.1, allocated, func=$18load_global.0, args=[Var($20load_deref.1, listobject.py:394), Var(allocated, listobject.py:391)], kws=(), vararg=None, varkwarg=None, target=None) ['$18load_global.0', '$20load_deref.1', 'allocated', 'lp']\n", - " $28load_global.4 = global(_list_set_method_table: ) ['$28load_global.4']\n", - " $32load_deref.6 = freevar(itemty: class(int64)) ['$32load_deref.6']\n", - " $34call_function.7 = call $28load_global.4(lp, $32load_deref.6, func=$28load_global.4, args=[Var(lp, listobject.py:394), Var($32load_deref.6, listobject.py:395)], kws=(), vararg=None, varkwarg=None, target=None) ['$28load_global.4', '$32load_deref.6', '$34call_function.7', 'lp']\n", - " $38load_global.8 = global(_make_list: ) ['$38load_global.8']\n", - " $40load_deref.9 = freevar(itemty: class(int64)) ['$40load_deref.9']\n", - " l = call $38load_global.8($40load_deref.9, lp, func=$38load_global.8, args=[Var($40load_deref.9, listobject.py:396), Var(lp, listobject.py:394)], kws=(), vararg=None, varkwarg=None, target=None) ['$38load_global.8', '$40load_deref.9', 'l', 'lp']\n", - " $50return_value.13 = cast(value=l) ['$50return_value.13', 'l']\n", - " return $50return_value.13 ['$50return_value.13']\n", - "\n", - "2024-09-12 10:50:38,555 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:38,556 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,557 - numba.core.ssa - DEBUG - on stmt: item = arg(0, name=item)\n", - "2024-09-12 10:50:38,557 - numba.core.ssa - DEBUG - on stmt: allocated = arg(1, name=allocated)\n", - "2024-09-12 10:50:38,558 - numba.core.ssa - DEBUG - on stmt: $const4.1 = const(int, 0)\n", - "2024-09-12 10:50:38,558 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = allocated < $const4.1\n", - "2024-09-12 10:50:38,559 - numba.core.ssa - DEBUG - on stmt: bool8 = global(bool: )\n", - "2024-09-12 10:50:38,559 - numba.core.ssa - DEBUG - on stmt: $8pred = call bool8($6compare_op.2, func=bool8, args=(Var($6compare_op.2, listobject.py:392),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,560 - numba.core.ssa - DEBUG - on stmt: branch $8pred, 10, 18\n", - "2024-09-12 10:50:38,560 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 10\n", - "2024-09-12 10:50:38,561 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,562 - numba.core.ssa - DEBUG - on stmt: $10load_global.0 = global(RuntimeError: )\n", - "2024-09-12 10:50:38,562 - numba.core.ssa - DEBUG - on stmt: $const12.1 = const(str, expecting *allocated* to be >= 0)\n", - "2024-09-12 10:50:38,563 - numba.core.ssa - DEBUG - on stmt: $14call_function.2 = call $10load_global.0($const12.1, func=$10load_global.0, args=[Var($const12.1, listobject.py:393)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,563 - numba.core.ssa - DEBUG - on stmt: raise ('expecting *allocated* to be >= 0')\n", - "2024-09-12 10:50:38,564 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 18\n", - "2024-09-12 10:50:38,564 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,565 - numba.core.ssa - DEBUG - on stmt: $18load_global.0 = global(_list_new: )\n", - "2024-09-12 10:50:38,566 - numba.core.ssa - DEBUG - on stmt: $20load_deref.1 = freevar(itemty: class(int64))\n", - "2024-09-12 10:50:38,566 - numba.core.ssa - DEBUG - on stmt: lp = call $18load_global.0($20load_deref.1, allocated, func=$18load_global.0, args=[Var($20load_deref.1, listobject.py:394), Var(allocated, listobject.py:391)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,567 - numba.core.ssa - DEBUG - on stmt: $28load_global.4 = global(_list_set_method_table: )\n", - "2024-09-12 10:50:38,567 - numba.core.ssa - DEBUG - on stmt: $32load_deref.6 = freevar(itemty: class(int64))\n", - "2024-09-12 10:50:38,568 - numba.core.ssa - DEBUG - on stmt: $34call_function.7 = call $28load_global.4(lp, $32load_deref.6, func=$28load_global.4, args=[Var(lp, listobject.py:394), Var($32load_deref.6, listobject.py:395)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,569 - numba.core.ssa - DEBUG - on stmt: $38load_global.8 = global(_make_list: )\n", - "2024-09-12 10:50:38,569 - numba.core.ssa - DEBUG - on stmt: $40load_deref.9 = freevar(itemty: class(int64))\n", - "2024-09-12 10:50:38,570 - numba.core.ssa - DEBUG - on stmt: l = call $38load_global.8($40load_deref.9, lp, func=$38load_global.8, args=[Var($40load_deref.9, listobject.py:396), Var(lp, listobject.py:394)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,570 - numba.core.ssa - DEBUG - on stmt: $50return_value.13 = cast(value=l)\n", - "2024-09-12 10:50:38,571 - numba.core.ssa - DEBUG - on stmt: return $50return_value.13\n", - "2024-09-12 10:50:38,572 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_global.0': [],\n", - " '$14call_function.2': [],\n", - " '$18load_global.0': [],\n", - " '$20load_deref.1': [],\n", - " '$28load_global.4': [],\n", - " '$32load_deref.6': [],\n", - " '$34call_function.7': [],\n", - " '$38load_global.8': [],\n", - " '$40load_deref.9': [],\n", - " '$50return_value.13': [],\n", - " '$6compare_op.2': [],\n", - " '$8pred': [],\n", - " '$const12.1': [],\n", - " '$const4.1': [],\n", - " 'allocated': [],\n", - " 'bool8': [],\n", - " 'item': [],\n", - " 'l': [],\n", - " 'lp': []})\n", - "2024-09-12 10:50:38,573 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:38,704 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=599)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=600)\n", - " 4\tLOAD_FAST(arg=1, lineno=600)\n", - " 6\tLOAD_DEREF(arg=0, lineno=600)\n", - " 8\tCALL_FUNCTION(arg=2, lineno=600)\n", - " 10\tSTORE_FAST(arg=2, lineno=600)\n", - " 12\tLOAD_GLOBAL(arg=1, lineno=601)\n", - " 14\tLOAD_FAST(arg=0, lineno=601)\n", - " 16\tLOAD_FAST(arg=2, lineno=601)\n", - " 18\tCALL_FUNCTION(arg=2, lineno=601)\n", - " 20\tSTORE_FAST(arg=3, lineno=601)\n", - " 22\tLOAD_FAST(arg=3, lineno=602)\n", - " 24\tLOAD_GLOBAL(arg=2, lineno=602)\n", - " 26\tLOAD_ATTR(arg=3, lineno=602)\n", - " 28\tCOMPARE_OP(arg=2, lineno=602)\n", - " 30\tPOP_JUMP_IF_FALSE(arg=19, lineno=602)\n", - " 32\tLOAD_CONST(arg=0, lineno=603)\n", - " 34\tRETURN_VALUE(arg=None, lineno=603)\n", - "> 36\tLOAD_FAST(arg=3, lineno=604)\n", - " 38\tLOAD_GLOBAL(arg=2, lineno=604)\n", - " 40\tLOAD_ATTR(arg=4, lineno=604)\n", - " 42\tCOMPARE_OP(arg=2, lineno=604)\n", - " 44\tPOP_JUMP_IF_FALSE(arg=28, lineno=604)\n", - " 46\tLOAD_GLOBAL(arg=5, lineno=605)\n", - " 48\tLOAD_CONST(arg=1, lineno=605)\n", - " 50\tCALL_FUNCTION(arg=1, lineno=605)\n", - " 52\tRAISE_VARARGS(arg=1, lineno=605)\n", - "> 54\tLOAD_FAST(arg=3, lineno=606)\n", - " 56\tLOAD_GLOBAL(arg=2, lineno=606)\n", - " 58\tLOAD_ATTR(arg=6, lineno=606)\n", - " 60\tCOMPARE_OP(arg=2, lineno=606)\n", - " 62\tPOP_JUMP_IF_FALSE(arg=37, lineno=606)\n", - " 64\tLOAD_GLOBAL(arg=7, lineno=607)\n", - " 66\tLOAD_CONST(arg=2, lineno=607)\n", - " 68\tCALL_FUNCTION(arg=1, lineno=607)\n", - " 70\tRAISE_VARARGS(arg=1, lineno=607)\n", - "> 72\tLOAD_GLOBAL(arg=8, lineno=609)\n", - " 74\tLOAD_CONST(arg=3, lineno=609)\n", - " 76\tCALL_FUNCTION(arg=1, lineno=609)\n", - " 78\tRAISE_VARARGS(arg=1, lineno=609)\n", - "2024-09-12 10:50:38,705 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:38,706 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,707 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:38,707 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=599)\n", - "2024-09-12 10:50:38,708 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,709 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=600)\n", - "2024-09-12 10:50:38,709 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,710 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=1, lineno=600)\n", - "2024-09-12 10:50:38,710 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:38,711 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_DEREF(arg=0, lineno=600)\n", - "2024-09-12 10:50:38,712 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$item4.1']\n", - "2024-09-12 10:50:38,712 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_FUNCTION(arg=2, lineno=600)\n", - "2024-09-12 10:50:38,713 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$item4.1', '$6load_deref.2']\n", - "2024-09-12 10:50:38,714 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=STORE_FAST(arg=2, lineno=600)\n", - "2024-09-12 10:50:38,714 - numba.core.byteflow - DEBUG - stack ['$8call_function.3']\n", - "2024-09-12 10:50:38,715 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_GLOBAL(arg=1, lineno=601)\n", - "2024-09-12 10:50:38,715 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,716 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=0, lineno=601)\n", - "2024-09-12 10:50:38,717 - numba.core.byteflow - DEBUG - stack ['$12load_global.4']\n", - "2024-09-12 10:50:38,717 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=2, lineno=601)\n", - "2024-09-12 10:50:38,718 - numba.core.byteflow - DEBUG - stack ['$12load_global.4', '$l14.5']\n", - "2024-09-12 10:50:38,719 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=CALL_FUNCTION(arg=2, lineno=601)\n", - "2024-09-12 10:50:38,719 - numba.core.byteflow - DEBUG - stack ['$12load_global.4', '$l14.5', '$casteditem16.6']\n", - "2024-09-12 10:50:38,720 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=STORE_FAST(arg=3, lineno=601)\n", - "2024-09-12 10:50:38,720 - numba.core.byteflow - DEBUG - stack ['$18call_function.7']\n", - "2024-09-12 10:50:38,721 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=3, lineno=602)\n", - "2024-09-12 10:50:38,722 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,722 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_GLOBAL(arg=2, lineno=602)\n", - "2024-09-12 10:50:38,723 - numba.core.byteflow - DEBUG - stack ['$status22.8']\n", - "2024-09-12 10:50:38,723 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_ATTR(arg=3, lineno=602)\n", - "2024-09-12 10:50:38,724 - numba.core.byteflow - DEBUG - stack ['$status22.8', '$24load_global.9']\n", - "2024-09-12 10:50:38,725 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=COMPARE_OP(arg=2, lineno=602)\n", - "2024-09-12 10:50:38,728 - numba.core.byteflow - DEBUG - stack ['$status22.8', '$26load_attr.10']\n", - "2024-09-12 10:50:38,728 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=POP_JUMP_IF_FALSE(arg=19, lineno=602)\n", - "2024-09-12 10:50:38,729 - numba.core.byteflow - DEBUG - stack ['$28compare_op.11']\n", - "2024-09-12 10:50:38,730 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=32, stack=(), blockstack=(), npush=0), Edge(pc=36, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:38,730 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=0), State(pc_initial=36 nstack_initial=0)])\n", - "2024-09-12 10:50:38,740 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,740 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=32 nstack_initial=0)\n", - "2024-09-12 10:50:38,741 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_CONST(arg=0, lineno=603)\n", - "2024-09-12 10:50:38,742 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,743 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=RETURN_VALUE(arg=None, lineno=603)\n", - "2024-09-12 10:50:38,743 - numba.core.byteflow - DEBUG - stack ['$const32.0']\n", - "2024-09-12 10:50:38,744 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:38,745 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=36 nstack_initial=0)])\n", - "2024-09-12 10:50:38,746 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,746 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=36 nstack_initial=0)\n", - "2024-09-12 10:50:38,747 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_FAST(arg=3, lineno=604)\n", - "2024-09-12 10:50:38,748 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,749 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_GLOBAL(arg=2, lineno=604)\n", - "2024-09-12 10:50:38,749 - numba.core.byteflow - DEBUG - stack ['$status36.0']\n", - "2024-09-12 10:50:38,750 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_ATTR(arg=4, lineno=604)\n", - "2024-09-12 10:50:38,751 - numba.core.byteflow - DEBUG - stack ['$status36.0', '$38load_global.1']\n", - "2024-09-12 10:50:38,752 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=COMPARE_OP(arg=2, lineno=604)\n", - "2024-09-12 10:50:38,752 - numba.core.byteflow - DEBUG - stack ['$status36.0', '$40load_attr.2']\n", - "2024-09-12 10:50:38,753 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_FALSE(arg=28, lineno=604)\n", - "2024-09-12 10:50:38,754 - numba.core.byteflow - DEBUG - stack ['$42compare_op.3']\n", - "2024-09-12 10:50:38,755 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=(), blockstack=(), npush=0), Edge(pc=54, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:38,756 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=0), State(pc_initial=54 nstack_initial=0)])\n", - "2024-09-12 10:50:38,756 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,757 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=0)\n", - "2024-09-12 10:50:38,758 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_GLOBAL(arg=5, lineno=605)\n", - "2024-09-12 10:50:38,758 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,759 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_CONST(arg=1, lineno=605)\n", - "2024-09-12 10:50:38,760 - numba.core.byteflow - DEBUG - stack ['$46load_global.0']\n", - "2024-09-12 10:50:38,760 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=CALL_FUNCTION(arg=1, lineno=605)\n", - "2024-09-12 10:50:38,761 - numba.core.byteflow - DEBUG - stack ['$46load_global.0', '$const48.1']\n", - "2024-09-12 10:50:38,762 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=RAISE_VARARGS(arg=1, lineno=605)\n", - "2024-09-12 10:50:38,762 - numba.core.byteflow - DEBUG - stack ['$50call_function.2']\n", - "2024-09-12 10:50:38,763 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:38,764 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=0)])\n", - "2024-09-12 10:50:38,764 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,765 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=0)\n", - "2024-09-12 10:50:38,766 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=LOAD_FAST(arg=3, lineno=606)\n", - "2024-09-12 10:50:38,766 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,767 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_GLOBAL(arg=2, lineno=606)\n", - "2024-09-12 10:50:38,768 - numba.core.byteflow - DEBUG - stack ['$status54.0']\n", - "2024-09-12 10:50:38,769 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_ATTR(arg=6, lineno=606)\n", - "2024-09-12 10:50:38,769 - numba.core.byteflow - DEBUG - stack ['$status54.0', '$56load_global.1']\n", - "2024-09-12 10:50:38,770 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=COMPARE_OP(arg=2, lineno=606)\n", - "2024-09-12 10:50:38,771 - numba.core.byteflow - DEBUG - stack ['$status54.0', '$58load_attr.2']\n", - "2024-09-12 10:50:38,771 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=POP_JUMP_IF_FALSE(arg=37, lineno=606)\n", - "2024-09-12 10:50:38,772 - numba.core.byteflow - DEBUG - stack ['$60compare_op.3']\n", - "2024-09-12 10:50:38,773 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=64, stack=(), blockstack=(), npush=0), Edge(pc=72, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:38,773 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=64 nstack_initial=0), State(pc_initial=72 nstack_initial=0)])\n", - "2024-09-12 10:50:38,774 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,775 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=64 nstack_initial=0)\n", - "2024-09-12 10:50:38,786 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_GLOBAL(arg=7, lineno=607)\n", - "2024-09-12 10:50:38,787 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,788 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_CONST(arg=2, lineno=607)\n", - "2024-09-12 10:50:38,789 - numba.core.byteflow - DEBUG - stack ['$64load_global.0']\n", - "2024-09-12 10:50:38,789 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=CALL_FUNCTION(arg=1, lineno=607)\n", - "2024-09-12 10:50:38,790 - numba.core.byteflow - DEBUG - stack ['$64load_global.0', '$const66.1']\n", - "2024-09-12 10:50:38,791 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=RAISE_VARARGS(arg=1, lineno=607)\n", - "2024-09-12 10:50:38,791 - numba.core.byteflow - DEBUG - stack ['$68call_function.2']\n", - "2024-09-12 10:50:38,792 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:38,793 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=72 nstack_initial=0)])\n", - "2024-09-12 10:50:38,794 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,794 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=72 nstack_initial=0)\n", - "2024-09-12 10:50:38,795 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=LOAD_GLOBAL(arg=8, lineno=609)\n", - "2024-09-12 10:50:38,796 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,796 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=3, lineno=609)\n", - "2024-09-12 10:50:38,797 - numba.core.byteflow - DEBUG - stack ['$72load_global.0']\n", - "2024-09-12 10:50:38,798 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=CALL_FUNCTION(arg=1, lineno=609)\n", - "2024-09-12 10:50:38,798 - numba.core.byteflow - DEBUG - stack ['$72load_global.0', '$const74.1']\n", - "2024-09-12 10:50:38,799 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=RAISE_VARARGS(arg=1, lineno=609)\n", - "2024-09-12 10:50:38,800 - numba.core.byteflow - DEBUG - stack ['$76call_function.2']\n", - "2024-09-12 10:50:38,800 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:38,801 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:38,802 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=32 nstack_initial=0): set(),\n", - " State(pc_initial=36 nstack_initial=0): set(),\n", - " State(pc_initial=46 nstack_initial=0): set(),\n", - " State(pc_initial=54 nstack_initial=0): set(),\n", - " State(pc_initial=64 nstack_initial=0): set(),\n", - " State(pc_initial=72 nstack_initial=0): set()})\n", - "2024-09-12 10:50:38,806 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:38,807 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:38,808 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:38,809 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:38,809 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:38,810 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:38,811 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$item4.1'}), (6, {'res': '$6load_deref.2'}), (8, {'func': '$2load_global.0', 'args': ['$item4.1', '$6load_deref.2'], 'res': '$8call_function.3'}), (10, {'value': '$8call_function.3'}), (12, {'res': '$12load_global.4'}), (14, {'res': '$l14.5'}), (16, {'res': '$casteditem16.6'}), (18, {'func': '$12load_global.4', 'args': ['$l14.5', '$casteditem16.6'], 'res': '$18call_function.7'}), (20, {'value': '$18call_function.7'}), (22, {'res': '$status22.8'}), (24, {'res': '$24load_global.9'}), (26, {'item': '$24load_global.9', 'res': '$26load_attr.10'}), (28, {'lhs': '$status22.8', 'rhs': '$26load_attr.10', 'res': '$28compare_op.11'}), (30, {'pred': '$28compare_op.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={32: (), 36: ()})\n", - "2024-09-12 10:50:38,812 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=32 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((32, {'res': '$const32.0'}), (34, {'retval': '$const32.0', 'castval': '$34return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:38,812 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=36 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((36, {'res': '$status36.0'}), (38, {'res': '$38load_global.1'}), (40, {'item': '$38load_global.1', 'res': '$40load_attr.2'}), (42, {'lhs': '$status36.0', 'rhs': '$40load_attr.2', 'res': '$42compare_op.3'}), (44, {'pred': '$42compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: (), 54: ()})\n", - "2024-09-12 10:50:38,813 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((46, {'res': '$46load_global.0'}), (48, {'res': '$const48.1'}), (50, {'func': '$46load_global.0', 'args': ['$const48.1'], 'res': '$50call_function.2'}), (52, {'exc': '$50call_function.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:38,814 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((54, {'res': '$status54.0'}), (56, {'res': '$56load_global.1'}), (58, {'item': '$56load_global.1', 'res': '$58load_attr.2'}), (60, {'lhs': '$status54.0', 'rhs': '$58load_attr.2', 'res': '$60compare_op.3'}), (62, {'pred': '$60compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={64: (), 72: ()})\n", - "2024-09-12 10:50:38,814 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=64 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((64, {'res': '$64load_global.0'}), (66, {'res': '$const66.1'}), (68, {'func': '$64load_global.0', 'args': ['$const66.1'], 'res': '$68call_function.2'}), (70, {'exc': '$68call_function.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:38,815 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=72 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((72, {'res': '$72load_global.0'}), (74, {'res': '$const74.1'}), (76, {'func': '$72load_global.0', 'args': ['$const74.1'], 'res': '$76call_function.2'}), (78, {'exc': '$76call_function.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:38,819 - numba.core.interpreter - DEBUG - label 0:\n", - " l = arg(0, name=l) ['l']\n", - " item = arg(1, name=item) ['item']\n", - " $2load_global.0 = global(_cast: ) ['$2load_global.0']\n", - " $6load_deref.2 = freevar(itemty: int64) ['$6load_deref.2']\n", - " casteditem = call $2load_global.0(item, $6load_deref.2, func=$2load_global.0, args=[Var(item, listobject.py:599), Var($6load_deref.2, listobject.py:600)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', '$6load_deref.2', 'casteditem', 'item']\n", - " $12load_global.4 = global(_list_append: ) ['$12load_global.4']\n", - " status = call $12load_global.4(l, casteditem, func=$12load_global.4, args=[Var(l, listobject.py:599), Var(casteditem, listobject.py:600)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_global.4', 'casteditem', 'l', 'status']\n", - " $24load_global.9 = global(ListStatus: ) ['$24load_global.9']\n", - " $26load_attr.10 = getattr(value=$24load_global.9, attr=LIST_OK) ['$24load_global.9', '$26load_attr.10']\n", - " $28compare_op.11 = status == $26load_attr.10 ['$26load_attr.10', '$28compare_op.11', 'status']\n", - " bool30 = global(bool: ) ['bool30']\n", - " $30pred = call bool30($28compare_op.11, func=bool30, args=(Var($28compare_op.11, listobject.py:602),), kws=(), vararg=None, varkwarg=None, target=None) ['$28compare_op.11', '$30pred', 'bool30']\n", - " branch $30pred, 32, 36 ['$30pred']\n", - "label 32:\n", - " $const32.0 = const(NoneType, None) ['$const32.0']\n", - " $34return_value.1 = cast(value=$const32.0) ['$34return_value.1', '$const32.0']\n", - " return $34return_value.1 ['$34return_value.1']\n", - "label 36:\n", - " $38load_global.1 = global(ListStatus: ) ['$38load_global.1']\n", - " $40load_attr.2 = getattr(value=$38load_global.1, attr=LIST_ERR_IMMUTABLE) ['$38load_global.1', '$40load_attr.2']\n", - " $42compare_op.3 = status == $40load_attr.2 ['$40load_attr.2', '$42compare_op.3', 'status']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42compare_op.3, func=bool44, args=(Var($42compare_op.3, listobject.py:604),), kws=(), vararg=None, varkwarg=None, target=None) ['$42compare_op.3', '$44pred', 'bool44']\n", - " branch $44pred, 46, 54 ['$44pred']\n", - "label 46:\n", - " $46load_global.0 = global(ValueError: ) ['$46load_global.0']\n", - " $const48.1 = const(str, list is immutable) ['$const48.1']\n", - " $50call_function.2 = call $46load_global.0($const48.1, func=$46load_global.0, args=[Var($const48.1, listobject.py:605)], kws=(), vararg=None, varkwarg=None, target=None) ['$46load_global.0', '$50call_function.2', '$const48.1']\n", - " raise $50call_function.2 ['$50call_function.2']\n", - "label 54:\n", - " $56load_global.1 = global(ListStatus: ) ['$56load_global.1']\n", - " $58load_attr.2 = getattr(value=$56load_global.1, attr=LIST_ERR_NO_MEMORY) ['$56load_global.1', '$58load_attr.2']\n", - " $60compare_op.3 = status == $58load_attr.2 ['$58load_attr.2', '$60compare_op.3', 'status']\n", - " bool62 = global(bool: ) ['bool62']\n", - " $62pred = call bool62($60compare_op.3, func=bool62, args=(Var($60compare_op.3, listobject.py:606),), kws=(), vararg=None, varkwarg=None, target=None) ['$60compare_op.3', '$62pred', 'bool62']\n", - " branch $62pred, 64, 72 ['$62pred']\n", - "label 64:\n", - " $64load_global.0 = global(MemoryError: ) ['$64load_global.0']\n", - " $const66.1 = const(str, Unable to allocate memory to append item) ['$const66.1']\n", - " $68call_function.2 = call $64load_global.0($const66.1, func=$64load_global.0, args=[Var($const66.1, listobject.py:607)], kws=(), vararg=None, varkwarg=None, target=None) ['$64load_global.0', '$68call_function.2', '$const66.1']\n", - " raise $68call_function.2 ['$68call_function.2']\n", - "label 72:\n", - " $72load_global.0 = global(RuntimeError: ) ['$72load_global.0']\n", - " $const74.1 = const(str, list.append failed unexpectedly) ['$const74.1']\n", - " $76call_function.2 = call $72load_global.0($const74.1, func=$72load_global.0, args=[Var($const74.1, listobject.py:609)], kws=(), vararg=None, varkwarg=None, target=None) ['$72load_global.0', '$76call_function.2', '$const74.1']\n", - " raise $76call_function.2 ['$76call_function.2']\n", - "\n", - "2024-09-12 10:50:38,844 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:38,845 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,845 - numba.core.ssa - DEBUG - on stmt: l = arg(0, name=l)\n", - "2024-09-12 10:50:38,846 - numba.core.ssa - DEBUG - on stmt: item = arg(1, name=item)\n", - "2024-09-12 10:50:38,847 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(_cast: )\n", - "2024-09-12 10:50:38,848 - numba.core.ssa - DEBUG - on stmt: $6load_deref.2 = freevar(itemty: int64)\n", - "2024-09-12 10:50:38,849 - numba.core.ssa - DEBUG - on stmt: casteditem = call $2load_global.0(item, $6load_deref.2, func=$2load_global.0, args=[Var(item, listobject.py:599), Var($6load_deref.2, listobject.py:600)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,849 - numba.core.ssa - DEBUG - on stmt: $12load_global.4 = global(_list_append: )\n", - "2024-09-12 10:50:38,850 - numba.core.ssa - DEBUG - on stmt: status = call $12load_global.4(l, casteditem, func=$12load_global.4, args=[Var(l, listobject.py:599), Var(casteditem, listobject.py:600)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,851 - numba.core.ssa - DEBUG - on stmt: $24load_global.9 = global(ListStatus: )\n", - "2024-09-12 10:50:38,852 - numba.core.ssa - DEBUG - on stmt: $26load_attr.10 = getattr(value=$24load_global.9, attr=LIST_OK)\n", - "2024-09-12 10:50:38,852 - numba.core.ssa - DEBUG - on stmt: $28compare_op.11 = status == $26load_attr.10\n", - "2024-09-12 10:50:38,853 - numba.core.ssa - DEBUG - on stmt: bool30 = global(bool: )\n", - "2024-09-12 10:50:38,854 - numba.core.ssa - DEBUG - on stmt: $30pred = call bool30($28compare_op.11, func=bool30, args=(Var($28compare_op.11, listobject.py:602),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,855 - numba.core.ssa - DEBUG - on stmt: branch $30pred, 32, 36\n", - "2024-09-12 10:50:38,856 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 32\n", - "2024-09-12 10:50:38,856 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,857 - numba.core.ssa - DEBUG - on stmt: $const32.0 = const(NoneType, None)\n", - "2024-09-12 10:50:38,858 - numba.core.ssa - DEBUG - on stmt: $34return_value.1 = cast(value=$const32.0)\n", - "2024-09-12 10:50:38,859 - numba.core.ssa - DEBUG - on stmt: return $34return_value.1\n", - "2024-09-12 10:50:38,859 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 36\n", - "2024-09-12 10:50:38,860 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,861 - numba.core.ssa - DEBUG - on stmt: $38load_global.1 = global(ListStatus: )\n", - "2024-09-12 10:50:38,862 - numba.core.ssa - DEBUG - on stmt: $40load_attr.2 = getattr(value=$38load_global.1, attr=LIST_ERR_IMMUTABLE)\n", - "2024-09-12 10:50:38,862 - numba.core.ssa - DEBUG - on stmt: $42compare_op.3 = status == $40load_attr.2\n", - "2024-09-12 10:50:38,863 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:38,864 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42compare_op.3, func=bool44, args=(Var($42compare_op.3, listobject.py:604),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,865 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 46, 54\n", - "2024-09-12 10:50:38,865 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-09-12 10:50:38,866 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,867 - numba.core.ssa - DEBUG - on stmt: $46load_global.0 = global(ValueError: )\n", - "2024-09-12 10:50:38,868 - numba.core.ssa - DEBUG - on stmt: $const48.1 = const(str, list is immutable)\n", - "2024-09-12 10:50:38,868 - numba.core.ssa - DEBUG - on stmt: $50call_function.2 = call $46load_global.0($const48.1, func=$46load_global.0, args=[Var($const48.1, listobject.py:605)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,869 - numba.core.ssa - DEBUG - on stmt: raise ('list is immutable')\n", - "2024-09-12 10:50:38,870 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-09-12 10:50:38,871 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,872 - numba.core.ssa - DEBUG - on stmt: $56load_global.1 = global(ListStatus: )\n", - "2024-09-12 10:50:38,872 - numba.core.ssa - DEBUG - on stmt: $58load_attr.2 = getattr(value=$56load_global.1, attr=LIST_ERR_NO_MEMORY)\n", - "2024-09-12 10:50:38,873 - numba.core.ssa - DEBUG - on stmt: $60compare_op.3 = status == $58load_attr.2\n", - "2024-09-12 10:50:38,874 - numba.core.ssa - DEBUG - on stmt: bool62 = global(bool: )\n", - "2024-09-12 10:50:38,875 - numba.core.ssa - DEBUG - on stmt: $62pred = call bool62($60compare_op.3, func=bool62, args=(Var($60compare_op.3, listobject.py:606),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,875 - numba.core.ssa - DEBUG - on stmt: branch $62pred, 64, 72\n", - "2024-09-12 10:50:38,876 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 64\n", - "2024-09-12 10:50:38,877 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,878 - numba.core.ssa - DEBUG - on stmt: $64load_global.0 = global(MemoryError: )\n", - "2024-09-12 10:50:38,878 - numba.core.ssa - DEBUG - on stmt: $const66.1 = const(str, Unable to allocate memory to append item)\n", - "2024-09-12 10:50:38,879 - numba.core.ssa - DEBUG - on stmt: $68call_function.2 = call $64load_global.0($const66.1, func=$64load_global.0, args=[Var($const66.1, listobject.py:607)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,880 - numba.core.ssa - DEBUG - on stmt: raise ('Unable to allocate memory to append item')\n", - "2024-09-12 10:50:38,881 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 72\n", - "2024-09-12 10:50:38,881 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:38,882 - numba.core.ssa - DEBUG - on stmt: $72load_global.0 = global(RuntimeError: )\n", - "2024-09-12 10:50:38,883 - numba.core.ssa - DEBUG - on stmt: $const74.1 = const(str, list.append failed unexpectedly)\n", - "2024-09-12 10:50:38,884 - numba.core.ssa - DEBUG - on stmt: $76call_function.2 = call $72load_global.0($const74.1, func=$72load_global.0, args=[Var($const74.1, listobject.py:609)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:38,884 - numba.core.ssa - DEBUG - on stmt: raise ('list.append failed unexpectedly')\n", - "2024-09-12 10:50:38,886 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12load_global.4': [],\n", - " '$24load_global.9': [],\n", - " '$26load_attr.10': [],\n", - " '$28compare_op.11': [],\n", - " '$2load_global.0': [],\n", - " '$30pred': [],\n", - " '$34return_value.1': [],\n", - " '$38load_global.1': [],\n", - " '$40load_attr.2': [],\n", - " '$42compare_op.3': [],\n", - " '$44pred': [],\n", - " '$46load_global.0': [],\n", - " '$50call_function.2': [],\n", - " '$56load_global.1': [],\n", - " '$58load_attr.2': [],\n", - " '$60compare_op.3': [],\n", - " '$62pred': [],\n", - " '$64load_global.0': [],\n", - " '$68call_function.2': [],\n", - " '$6load_deref.2': [],\n", - " '$72load_global.0': [],\n", - " '$76call_function.2': [],\n", - " '$const32.0': [],\n", - " '$const48.1': [],\n", - " '$const66.1': [],\n", - " '$const74.1': [],\n", - " 'bool30': [],\n", - " 'bool44': [],\n", - " 'bool62': [],\n", - " 'casteditem': [],\n", - " 'item': [],\n", - " 'l': [],\n", - " 'status': []})\n", - "2024-09-12 10:50:38,887 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:38,990 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=407)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=408)\n", - " 4\tLOAD_FAST(arg=0, lineno=408)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=408)\n", - " 8\tRETURN_VALUE(arg=None, lineno=408)\n", - "2024-09-12 10:50:38,991 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:38,992 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:38,992 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:38,993 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=407)\n", - "2024-09-12 10:50:38,993 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,994 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=408)\n", - "2024-09-12 10:50:38,995 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:38,995 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=408)\n", - "2024-09-12 10:50:38,996 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:38,997 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=408)\n", - "2024-09-12 10:50:38,997 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$l4.1']\n", - "2024-09-12 10:50:38,998 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=408)\n", - "2024-09-12 10:50:38,999 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-09-12 10:50:38,999 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:39,000 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:39,000 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:39,001 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:39,002 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:39,002 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:39,003 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:39,004 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:39,004 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:39,005 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$l4.1'}), (6, {'func': '$2load_global.0', 'args': ['$l4.1'], 'res': '$6call_function.2'}), (8, {'retval': '$6call_function.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:39,006 - numba.core.interpreter - DEBUG - label 0:\n", - " l = arg(0, name=l) ['l']\n", - " $2load_global.0 = global(_list_length: ) ['$2load_global.0']\n", - " $6call_function.2 = call $2load_global.0(l, func=$2load_global.0, args=[Var(l, listobject.py:407)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', '$6call_function.2', 'l']\n", - " $8return_value.3 = cast(value=$6call_function.2) ['$6call_function.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-09-12 10:50:39,012 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:39,013 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,013 - numba.core.ssa - DEBUG - on stmt: l = arg(0, name=l)\n", - "2024-09-12 10:50:39,014 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(_list_length: )\n", - "2024-09-12 10:50:39,014 - numba.core.ssa - DEBUG - on stmt: $6call_function.2 = call $2load_global.0(l, func=$2load_global.0, args=[Var(l, listobject.py:407)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,015 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6call_function.2)\n", - "2024-09-12 10:50:39,016 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-09-12 10:50:39,016 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$2load_global.0': [],\n", - " '$6call_function.2': [],\n", - " '$8return_value.3': [],\n", - " 'l': []})\n", - "2024-09-12 10:50:39,017 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:39,052 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=494)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=534)\n", - " 4\tLOAD_ATTR(arg=1, lineno=534)\n", - " 6\tLOAD_ATTR(arg=2, lineno=534)\n", - " 8\tLOAD_METHOD(arg=3, lineno=534)\n", - " 10\tLOAD_GLOBAL(arg=0, lineno=534)\n", - " 12\tLOAD_ATTR(arg=4, lineno=534)\n", - " 14\tLOAD_ATTR(arg=5, lineno=534)\n", - " 16\tCALL_METHOD(arg=1, lineno=534)\n", - " 18\tSTORE_FAST(arg=4, lineno=534)\n", - " 20\tLOAD_GLOBAL(arg=0, lineno=535)\n", - " 22\tLOAD_ATTR(arg=1, lineno=535)\n", - " 24\tLOAD_ATTR(arg=2, lineno=535)\n", - " 26\tLOAD_METHOD(arg=3, lineno=535)\n", - " 28\tLOAD_GLOBAL(arg=0, lineno=535)\n", - " 30\tLOAD_ATTR(arg=4, lineno=535)\n", - " 32\tLOAD_ATTR(arg=5, lineno=535)\n", - " 34\tCALL_METHOD(arg=1, lineno=535)\n", - " 36\tSTORE_FAST(arg=5, lineno=535)\n", - " 38\tLOAD_GLOBAL(arg=6, lineno=536)\n", - " 40\tLOAD_METHOD(arg=5, lineno=536)\n", - " 42\tLOAD_CONST(arg=1, lineno=536)\n", - " 44\tCALL_METHOD(arg=1, lineno=536)\n", - " 46\tSTORE_FAST(arg=6, lineno=536)\n", - " 48\tLOAD_GLOBAL(arg=7, lineno=538)\n", - " 50\tLOAD_GLOBAL(arg=8, lineno=538)\n", - " 52\tLOAD_FAST(arg=0, lineno=538)\n", - " 54\tCALL_FUNCTION(arg=1, lineno=538)\n", - " 56\tCALL_FUNCTION(arg=1, lineno=538)\n", - " 58\tGET_ITER(arg=None, lineno=538)\n", - "> 60\tFOR_ITER(arg=77, lineno=538)\n", - " 62\tSTORE_FAST(arg=7, lineno=538)\n", - " 64\tLOAD_GLOBAL(arg=7, lineno=541)\n", - " 66\tLOAD_FAST(arg=3, lineno=541)\n", - " 68\tLOAD_CONST(arg=1, lineno=541)\n", - " 70\tBINARY_SUBSCR(arg=None, lineno=541)\n", - " 72\tLOAD_FAST(arg=3, lineno=541)\n", - " 74\tLOAD_CONST(arg=2, lineno=541)\n", - " 76\tBINARY_SUBSCR(arg=None, lineno=541)\n", - " 78\tLOAD_FAST(arg=3, lineno=541)\n", - " 80\tLOAD_CONST(arg=3, lineno=541)\n", - " 82\tBINARY_SUBSCR(arg=None, lineno=541)\n", - " 84\tCALL_FUNCTION(arg=3, lineno=541)\n", - " 86\tGET_ITER(arg=None, lineno=541)\n", - "> 88\tFOR_ITER(arg=62, lineno=541)\n", - " 90\tSTORE_FAST(arg=8, lineno=541)\n", - " 92\tLOAD_GLOBAL(arg=6, lineno=542)\n", - " 94\tLOAD_ATTR(arg=9, lineno=542)\n", - " 96\tLOAD_FAST(arg=2, lineno=542)\n", - " 98\tLOAD_FAST(arg=0, lineno=542)\n", - " 100\tLOAD_FAST(arg=7, lineno=542)\n", - " 102\tBINARY_SUBSCR(arg=None, lineno=542)\n", - " 104\tLOAD_FAST(arg=1, lineno=542)\n", - " 106\tLOAD_FAST(arg=7, lineno=542)\n", - " 108\tBINARY_SUBSCR(arg=None, lineno=542)\n", - " 110\tBUILD_SLICE(arg=2, lineno=542)\n", - " 112\tBINARY_SUBSCR(arg=None, lineno=542)\n", - " 114\tLOAD_FAST(arg=8, lineno=542)\n", - " 116\tLOAD_CONST(arg=4, lineno=542)\n", - " 118\tLOAD_CONST(arg=5, lineno=542)\n", - " 120\tCALL_FUNCTION_KW(arg=3, lineno=542)\n", - " 122\tLOAD_FAST(arg=0, lineno=542)\n", - " 124\tLOAD_FAST(arg=7, lineno=542)\n", - " 126\tBINARY_SUBSCR(arg=None, lineno=542)\n", - " 128\tBINARY_ADD(arg=None, lineno=542)\n", - " 130\tSTORE_FAST(arg=9, lineno=542)\n", - " 132\tLOAD_GLOBAL(arg=6, lineno=543)\n", - " 134\tLOAD_ATTR(arg=9, lineno=543)\n", - " 136\tLOAD_FAST(arg=2, lineno=543)\n", - " 138\tLOAD_FAST(arg=0, lineno=543)\n", - " 140\tLOAD_FAST(arg=7, lineno=543)\n", - " 142\tBINARY_SUBSCR(arg=None, lineno=543)\n", - " 144\tLOAD_FAST(arg=1, lineno=543)\n", - " 146\tLOAD_FAST(arg=7, lineno=543)\n", - " 148\tBINARY_SUBSCR(arg=None, lineno=543)\n", - " 150\tBUILD_SLICE(arg=2, lineno=543)\n", - " 152\tBINARY_SUBSCR(arg=None, lineno=543)\n", - " 154\tLOAD_FAST(arg=8, lineno=543)\n", - " 156\tLOAD_CONST(arg=6, lineno=543)\n", - " 158\tLOAD_CONST(arg=5, lineno=543)\n", - " 160\tCALL_FUNCTION_KW(arg=3, lineno=543)\n", - " 162\tLOAD_FAST(arg=0, lineno=543)\n", - " 164\tLOAD_FAST(arg=7, lineno=543)\n", - " 166\tBINARY_SUBSCR(arg=None, lineno=543)\n", - " 168\tBINARY_ADD(arg=None, lineno=543)\n", - " 170\tSTORE_FAST(arg=10, lineno=543)\n", - " 172\tLOAD_FAST(arg=9, lineno=545)\n", - " 174\tLOAD_FAST(arg=10, lineno=545)\n", - " 176\tCOMPARE_OP(arg=3, lineno=545)\n", - " 178\tPOP_JUMP_IF_FALSE(arg=107, lineno=545)\n", - " 180\tLOAD_FAST(arg=4, lineno=546)\n", - " 182\tLOAD_METHOD(arg=10, lineno=546)\n", - " 184\tLOAD_FAST(arg=9, lineno=546)\n", - " 186\tCALL_METHOD(arg=1, lineno=546)\n", - " 188\tPOP_TOP(arg=None, lineno=546)\n", - " 190\tLOAD_FAST(arg=5, lineno=547)\n", - " 192\tLOAD_METHOD(arg=10, lineno=547)\n", - " 194\tLOAD_FAST(arg=10, lineno=547)\n", - " 196\tCALL_METHOD(arg=1, lineno=547)\n", - " 198\tPOP_TOP(arg=None, lineno=547)\n", - " 200\tLOAD_FAST(arg=6, lineno=548)\n", - " 202\tLOAD_FAST(arg=10, lineno=548)\n", - " 204\tLOAD_FAST(arg=9, lineno=548)\n", - " 206\tBINARY_SUBTRACT(arg=None, lineno=548)\n", - " 208\tINPLACE_ADD(arg=None, lineno=548)\n", - " 210\tSTORE_FAST(arg=6, lineno=548)\n", - "> 212\tJUMP_ABSOLUTE(arg=45, lineno=548)\n", - "> 214\tJUMP_ABSOLUTE(arg=31, lineno=541)\n", - "> 216\tLOAD_FAST(arg=4, lineno=550)\n", - " 218\tLOAD_FAST(arg=5, lineno=550)\n", - " 220\tLOAD_FAST(arg=6, lineno=550)\n", - " 222\tBUILD_TUPLE(arg=3, lineno=550)\n", - " 224\tRETURN_VALUE(arg=None, lineno=550)\n", - "2024-09-12 10:50:39,053 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:39,053 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,054 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:39,055 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=494)\n", - "2024-09-12 10:50:39,055 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,056 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=534)\n", - "2024-09-12 10:50:39,056 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,057 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=534)\n", - "2024-09-12 10:50:39,058 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:39,058 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_ATTR(arg=2, lineno=534)\n", - "2024-09-12 10:50:39,059 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-09-12 10:50:39,060 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=3, lineno=534)\n", - "2024-09-12 10:50:39,060 - numba.core.byteflow - DEBUG - stack ['$6load_attr.2']\n", - "2024-09-12 10:50:39,061 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=0, lineno=534)\n", - "2024-09-12 10:50:39,062 - numba.core.byteflow - DEBUG - stack ['$8load_method.3']\n", - "2024-09-12 10:50:39,062 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=4, lineno=534)\n", - "2024-09-12 10:50:39,063 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$10load_global.4']\n", - "2024-09-12 10:50:39,063 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_ATTR(arg=5, lineno=534)\n", - "2024-09-12 10:50:39,064 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$12load_attr.5']\n", - "2024-09-12 10:50:39,065 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=CALL_METHOD(arg=1, lineno=534)\n", - "2024-09-12 10:50:39,065 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$14load_attr.6']\n", - "2024-09-12 10:50:39,066 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=STORE_FAST(arg=4, lineno=534)\n", - "2024-09-12 10:50:39,067 - numba.core.byteflow - DEBUG - stack ['$16call_method.7']\n", - "2024-09-12 10:50:39,067 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_GLOBAL(arg=0, lineno=535)\n", - "2024-09-12 10:50:39,068 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,068 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_ATTR(arg=1, lineno=535)\n", - "2024-09-12 10:50:39,069 - numba.core.byteflow - DEBUG - stack ['$20load_global.8']\n", - "2024-09-12 10:50:39,070 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_ATTR(arg=2, lineno=535)\n", - "2024-09-12 10:50:39,070 - numba.core.byteflow - DEBUG - stack ['$22load_attr.9']\n", - "2024-09-12 10:50:39,071 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_METHOD(arg=3, lineno=535)\n", - "2024-09-12 10:50:39,072 - numba.core.byteflow - DEBUG - stack ['$24load_attr.10']\n", - "2024-09-12 10:50:39,072 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_GLOBAL(arg=0, lineno=535)\n", - "2024-09-12 10:50:39,073 - numba.core.byteflow - DEBUG - stack ['$26load_method.11']\n", - "2024-09-12 10:50:39,074 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_ATTR(arg=4, lineno=535)\n", - "2024-09-12 10:50:39,074 - numba.core.byteflow - DEBUG - stack ['$26load_method.11', '$28load_global.12']\n", - "2024-09-12 10:50:39,075 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_ATTR(arg=5, lineno=535)\n", - "2024-09-12 10:50:39,076 - numba.core.byteflow - DEBUG - stack ['$26load_method.11', '$30load_attr.13']\n", - "2024-09-12 10:50:39,076 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=CALL_METHOD(arg=1, lineno=535)\n", - "2024-09-12 10:50:39,077 - numba.core.byteflow - DEBUG - stack ['$26load_method.11', '$32load_attr.14']\n", - "2024-09-12 10:50:39,078 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=STORE_FAST(arg=5, lineno=535)\n", - "2024-09-12 10:50:39,078 - numba.core.byteflow - DEBUG - stack ['$34call_method.15']\n", - "2024-09-12 10:50:39,079 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_GLOBAL(arg=6, lineno=536)\n", - "2024-09-12 10:50:39,080 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,080 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_METHOD(arg=5, lineno=536)\n", - "2024-09-12 10:50:39,086 - numba.core.byteflow - DEBUG - stack ['$38load_global.16']\n", - "2024-09-12 10:50:39,086 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_CONST(arg=1, lineno=536)\n", - "2024-09-12 10:50:39,087 - numba.core.byteflow - DEBUG - stack ['$40load_method.17']\n", - "2024-09-12 10:50:39,088 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=CALL_METHOD(arg=1, lineno=536)\n", - "2024-09-12 10:50:39,088 - numba.core.byteflow - DEBUG - stack ['$40load_method.17', '$const42.18']\n", - "2024-09-12 10:50:39,089 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=STORE_FAST(arg=6, lineno=536)\n", - "2024-09-12 10:50:39,090 - numba.core.byteflow - DEBUG - stack ['$44call_method.19']\n", - "2024-09-12 10:50:39,091 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_GLOBAL(arg=7, lineno=538)\n", - "2024-09-12 10:50:39,091 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,092 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_GLOBAL(arg=8, lineno=538)\n", - "2024-09-12 10:50:39,093 - numba.core.byteflow - DEBUG - stack ['$48load_global.20']\n", - "2024-09-12 10:50:39,094 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=LOAD_FAST(arg=0, lineno=538)\n", - "2024-09-12 10:50:39,094 - numba.core.byteflow - DEBUG - stack ['$48load_global.20', '$50load_global.21']\n", - "2024-09-12 10:50:39,095 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=CALL_FUNCTION(arg=1, lineno=538)\n", - "2024-09-12 10:50:39,096 - numba.core.byteflow - DEBUG - stack ['$48load_global.20', '$50load_global.21', '$starts_old52.22']\n", - "2024-09-12 10:50:39,097 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=CALL_FUNCTION(arg=1, lineno=538)\n", - "2024-09-12 10:50:39,097 - numba.core.byteflow - DEBUG - stack ['$48load_global.20', '$54call_function.23']\n", - "2024-09-12 10:50:39,098 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=GET_ITER(arg=None, lineno=538)\n", - "2024-09-12 10:50:39,099 - numba.core.byteflow - DEBUG - stack ['$56call_function.24']\n", - "2024-09-12 10:50:39,100 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=60, stack=('$58get_iter.25',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,101 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=1)])\n", - "2024-09-12 10:50:39,101 - numba.core.byteflow - DEBUG - stack: ['$phi60.0']\n", - "2024-09-12 10:50:39,102 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=60 nstack_initial=1)\n", - "2024-09-12 10:50:39,103 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=FOR_ITER(arg=77, lineno=538)\n", - "2024-09-12 10:50:39,104 - numba.core.byteflow - DEBUG - stack ['$phi60.0']\n", - "2024-09-12 10:50:39,105 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=216, stack=(), blockstack=(), npush=0), Edge(pc=62, stack=('$phi60.0', '$60for_iter.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,106 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=216 nstack_initial=0), State(pc_initial=62 nstack_initial=2)])\n", - "2024-09-12 10:50:39,107 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,107 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=216 nstack_initial=0)\n", - "2024-09-12 10:50:39,108 - numba.core.byteflow - DEBUG - dispatch pc=216, inst=LOAD_FAST(arg=4, lineno=550)\n", - "2024-09-12 10:50:39,109 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,110 - numba.core.byteflow - DEBUG - dispatch pc=218, inst=LOAD_FAST(arg=5, lineno=550)\n", - "2024-09-12 10:50:39,111 - numba.core.byteflow - DEBUG - stack ['$starts216.0']\n", - "2024-09-12 10:50:39,111 - numba.core.byteflow - DEBUG - dispatch pc=220, inst=LOAD_FAST(arg=6, lineno=550)\n", - "2024-09-12 10:50:39,112 - numba.core.byteflow - DEBUG - stack ['$starts216.0', '$stops218.1']\n", - "2024-09-12 10:50:39,113 - numba.core.byteflow - DEBUG - dispatch pc=222, inst=BUILD_TUPLE(arg=3, lineno=550)\n", - "2024-09-12 10:50:39,114 - numba.core.byteflow - DEBUG - stack ['$starts216.0', '$stops218.1', '$n_matches220.2']\n", - "2024-09-12 10:50:39,115 - numba.core.byteflow - DEBUG - dispatch pc=224, inst=RETURN_VALUE(arg=None, lineno=550)\n", - "2024-09-12 10:50:39,116 - numba.core.byteflow - DEBUG - stack ['$222build_tuple.3']\n", - "2024-09-12 10:50:39,116 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:39,117 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=62 nstack_initial=2)])\n", - "2024-09-12 10:50:39,118 - numba.core.byteflow - DEBUG - stack: ['$phi62.0', '$phi62.1']\n", - "2024-09-12 10:50:39,119 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=62 nstack_initial=2)\n", - "2024-09-12 10:50:39,119 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=STORE_FAST(arg=7, lineno=538)\n", - "2024-09-12 10:50:39,120 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$phi62.1']\n", - "2024-09-12 10:50:39,121 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_GLOBAL(arg=7, lineno=541)\n", - "2024-09-12 10:50:39,122 - numba.core.byteflow - DEBUG - stack ['$phi62.0']\n", - "2024-09-12 10:50:39,122 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_FAST(arg=3, lineno=541)\n", - "2024-09-12 10:50:39,123 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2']\n", - "2024-09-12 10:50:39,124 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_CONST(arg=1, lineno=541)\n", - "2024-09-12 10:50:39,125 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$idx66.3']\n", - "2024-09-12 10:50:39,125 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=BINARY_SUBSCR(arg=None, lineno=541)\n", - "2024-09-12 10:50:39,126 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$idx66.3', '$const68.4']\n", - "2024-09-12 10:50:39,127 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=LOAD_FAST(arg=3, lineno=541)\n", - "2024-09-12 10:50:39,128 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5']\n", - "2024-09-12 10:50:39,129 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=2, lineno=541)\n", - "2024-09-12 10:50:39,129 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$idx72.6']\n", - "2024-09-12 10:50:39,130 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=BINARY_SUBSCR(arg=None, lineno=541)\n", - "2024-09-12 10:50:39,131 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$idx72.6', '$const74.7']\n", - "2024-09-12 10:50:39,132 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=3, lineno=541)\n", - "2024-09-12 10:50:39,132 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8']\n", - "2024-09-12 10:50:39,133 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_CONST(arg=3, lineno=541)\n", - "2024-09-12 10:50:39,134 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8', '$idx78.9']\n", - "2024-09-12 10:50:39,135 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=BINARY_SUBSCR(arg=None, lineno=541)\n", - "2024-09-12 10:50:39,135 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8', '$idx78.9', '$const80.10']\n", - "2024-09-12 10:50:39,136 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=CALL_FUNCTION(arg=3, lineno=541)\n", - "2024-09-12 10:50:39,137 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8', '$82binary_subscr.11']\n", - "2024-09-12 10:50:39,138 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=GET_ITER(arg=None, lineno=541)\n", - "2024-09-12 10:50:39,139 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$84call_function.12']\n", - "2024-09-12 10:50:39,139 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=88, stack=('$phi62.0', '$86get_iter.13'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,140 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=88 nstack_initial=2)])\n", - "2024-09-12 10:50:39,141 - numba.core.byteflow - DEBUG - stack: ['$phi88.0', '$phi88.1']\n", - "2024-09-12 10:50:39,142 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=88 nstack_initial=2)\n", - "2024-09-12 10:50:39,142 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=FOR_ITER(arg=62, lineno=541)\n", - "2024-09-12 10:50:39,143 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$phi88.1']\n", - "2024-09-12 10:50:39,144 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=214, stack=('$phi88.0',), blockstack=(), npush=0), Edge(pc=90, stack=('$phi88.0', '$phi88.1', '$88for_iter.3'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,145 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=214 nstack_initial=1), State(pc_initial=90 nstack_initial=3)])\n", - "2024-09-12 10:50:39,145 - numba.core.byteflow - DEBUG - stack: ['$phi214.0']\n", - "2024-09-12 10:50:39,146 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=214 nstack_initial=1)\n", - "2024-09-12 10:50:39,147 - numba.core.byteflow - DEBUG - dispatch pc=214, inst=JUMP_ABSOLUTE(arg=31, lineno=541)\n", - "2024-09-12 10:50:39,147 - numba.core.byteflow - DEBUG - stack ['$phi214.0']\n", - "2024-09-12 10:50:39,148 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=60, stack=('$phi214.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,149 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=90 nstack_initial=3), State(pc_initial=60 nstack_initial=1)])\n", - "2024-09-12 10:50:39,150 - numba.core.byteflow - DEBUG - stack: ['$phi90.0', '$phi90.1', '$phi90.2']\n", - "2024-09-12 10:50:39,150 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=90 nstack_initial=3)\n", - "2024-09-12 10:50:39,151 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=STORE_FAST(arg=8, lineno=541)\n", - "2024-09-12 10:50:39,152 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$phi90.2']\n", - "2024-09-12 10:50:39,152 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=LOAD_GLOBAL(arg=6, lineno=542)\n", - "2024-09-12 10:50:39,153 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1']\n", - "2024-09-12 10:50:39,154 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_ATTR(arg=9, lineno=542)\n", - "2024-09-12 10:50:39,155 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$92load_global.3']\n", - "2024-09-12 10:50:39,155 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=LOAD_FAST(arg=2, lineno=542)\n", - "2024-09-12 10:50:39,156 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4']\n", - "2024-09-12 10:50:39,157 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=0, lineno=542)\n", - "2024-09-12 10:50:39,157 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5']\n", - "2024-09-12 10:50:39,158 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=7, lineno=542)\n", - "2024-09-12 10:50:39,159 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$starts_old98.6']\n", - "2024-09-12 10:50:39,160 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=BINARY_SUBSCR(arg=None, lineno=542)\n", - "2024-09-12 10:50:39,160 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$starts_old98.6', '$j100.7']\n", - "2024-09-12 10:50:39,161 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=LOAD_FAST(arg=1, lineno=542)\n", - "2024-09-12 10:50:39,162 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$102binary_subscr.8']\n", - "2024-09-12 10:50:39,163 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_FAST(arg=7, lineno=542)\n", - "2024-09-12 10:50:39,163 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$102binary_subscr.8', '$stops_old104.9']\n", - "2024-09-12 10:50:39,164 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=BINARY_SUBSCR(arg=None, lineno=542)\n", - "2024-09-12 10:50:39,165 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$102binary_subscr.8', '$stops_old104.9', '$j106.10']\n", - "2024-09-12 10:50:39,165 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=BUILD_SLICE(arg=2, lineno=542)\n", - "2024-09-12 10:50:39,166 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$102binary_subscr.8', '$108binary_subscr.11']\n", - "2024-09-12 10:50:39,167 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=BINARY_SUBSCR(arg=None, lineno=542)\n", - "2024-09-12 10:50:39,168 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$110build_slice.13']\n", - "2024-09-12 10:50:39,168 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=LOAD_FAST(arg=8, lineno=542)\n", - "2024-09-12 10:50:39,169 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$112binary_subscr.14']\n", - "2024-09-12 10:50:39,170 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=LOAD_CONST(arg=4, lineno=542)\n", - "2024-09-12 10:50:39,170 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$112binary_subscr.14', '$p_match114.15']\n", - "2024-09-12 10:50:39,171 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_CONST(arg=5, lineno=542)\n", - "2024-09-12 10:50:39,172 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$112binary_subscr.14', '$p_match114.15', '$const116.16']\n", - "2024-09-12 10:50:39,172 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=CALL_FUNCTION_KW(arg=3, lineno=542)\n", - "2024-09-12 10:50:39,173 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$112binary_subscr.14', '$p_match114.15', '$const116.16', '$const118.17']\n", - "2024-09-12 10:50:39,174 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_FAST(arg=0, lineno=542)\n", - "2024-09-12 10:50:39,175 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$120call_function_kw.18']\n", - "2024-09-12 10:50:39,175 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=LOAD_FAST(arg=7, lineno=542)\n", - "2024-09-12 10:50:39,176 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$120call_function_kw.18', '$starts_old122.19']\n", - "2024-09-12 10:50:39,177 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=BINARY_SUBSCR(arg=None, lineno=542)\n", - "2024-09-12 10:50:39,177 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$120call_function_kw.18', '$starts_old122.19', '$j124.20']\n", - "2024-09-12 10:50:39,178 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=BINARY_ADD(arg=None, lineno=542)\n", - "2024-09-12 10:50:39,179 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$120call_function_kw.18', '$126binary_subscr.21']\n", - "2024-09-12 10:50:39,179 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=STORE_FAST(arg=9, lineno=542)\n", - "2024-09-12 10:50:39,180 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$128binary_add.22']\n", - "2024-09-12 10:50:39,181 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_GLOBAL(arg=6, lineno=543)\n", - "2024-09-12 10:50:39,182 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1']\n", - "2024-09-12 10:50:39,182 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_ATTR(arg=9, lineno=543)\n", - "2024-09-12 10:50:39,183 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$132load_global.23']\n", - "2024-09-12 10:50:39,184 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=LOAD_FAST(arg=2, lineno=543)\n", - "2024-09-12 10:50:39,184 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24']\n", - "2024-09-12 10:50:39,185 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=LOAD_FAST(arg=0, lineno=543)\n", - "2024-09-12 10:50:39,186 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25']\n", - "2024-09-12 10:50:39,186 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=LOAD_FAST(arg=7, lineno=543)\n", - "2024-09-12 10:50:39,187 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$starts_old138.26']\n", - "2024-09-12 10:50:39,188 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=BINARY_SUBSCR(arg=None, lineno=543)\n", - "2024-09-12 10:50:39,188 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$starts_old138.26', '$j140.27']\n", - "2024-09-12 10:50:39,189 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=LOAD_FAST(arg=1, lineno=543)\n", - "2024-09-12 10:50:39,190 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$142binary_subscr.28']\n", - "2024-09-12 10:50:39,191 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_FAST(arg=7, lineno=543)\n", - "2024-09-12 10:50:39,191 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$142binary_subscr.28', '$stops_old144.29']\n", - "2024-09-12 10:50:39,192 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=BINARY_SUBSCR(arg=None, lineno=543)\n", - "2024-09-12 10:50:39,193 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$142binary_subscr.28', '$stops_old144.29', '$j146.30']\n", - "2024-09-12 10:50:39,193 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=BUILD_SLICE(arg=2, lineno=543)\n", - "2024-09-12 10:50:39,194 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$142binary_subscr.28', '$148binary_subscr.31']\n", - "2024-09-12 10:50:39,195 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=BINARY_SUBSCR(arg=None, lineno=543)\n", - "2024-09-12 10:50:39,195 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$150build_slice.33']\n", - "2024-09-12 10:50:39,196 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_FAST(arg=8, lineno=543)\n", - "2024-09-12 10:50:39,197 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$152binary_subscr.34']\n", - "2024-09-12 10:50:39,197 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=LOAD_CONST(arg=6, lineno=543)\n", - "2024-09-12 10:50:39,198 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$152binary_subscr.34', '$p_match154.35']\n", - "2024-09-12 10:50:39,198 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=LOAD_CONST(arg=5, lineno=543)\n", - "2024-09-12 10:50:39,199 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$152binary_subscr.34', '$p_match154.35', '$const156.36']\n", - "2024-09-12 10:50:39,200 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=CALL_FUNCTION_KW(arg=3, lineno=543)\n", - "2024-09-12 10:50:39,200 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$152binary_subscr.34', '$p_match154.35', '$const156.36', '$const158.37']\n", - "2024-09-12 10:50:39,201 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=LOAD_FAST(arg=0, lineno=543)\n", - "2024-09-12 10:50:39,202 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$160call_function_kw.38']\n", - "2024-09-12 10:50:39,202 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=LOAD_FAST(arg=7, lineno=543)\n", - "2024-09-12 10:50:39,203 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$160call_function_kw.38', '$starts_old162.39']\n", - "2024-09-12 10:50:39,204 - numba.core.byteflow - DEBUG - dispatch pc=166, inst=BINARY_SUBSCR(arg=None, lineno=543)\n", - "2024-09-12 10:50:39,204 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$160call_function_kw.38', '$starts_old162.39', '$j164.40']\n", - "2024-09-12 10:50:39,205 - numba.core.byteflow - DEBUG - dispatch pc=168, inst=BINARY_ADD(arg=None, lineno=543)\n", - "2024-09-12 10:50:39,205 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$160call_function_kw.38', '$166binary_subscr.41']\n", - "2024-09-12 10:50:39,206 - numba.core.byteflow - DEBUG - dispatch pc=170, inst=STORE_FAST(arg=10, lineno=543)\n", - "2024-09-12 10:50:39,207 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$168binary_add.42']\n", - "2024-09-12 10:50:39,207 - numba.core.byteflow - DEBUG - dispatch pc=172, inst=LOAD_FAST(arg=9, lineno=545)\n", - "2024-09-12 10:50:39,208 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1']\n", - "2024-09-12 10:50:39,209 - numba.core.byteflow - DEBUG - dispatch pc=174, inst=LOAD_FAST(arg=10, lineno=545)\n", - "2024-09-12 10:50:39,209 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$start172.43']\n", - "2024-09-12 10:50:39,210 - numba.core.byteflow - DEBUG - dispatch pc=176, inst=COMPARE_OP(arg=3, lineno=545)\n", - "2024-09-12 10:50:39,211 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$start172.43', '$stop174.44']\n", - "2024-09-12 10:50:39,212 - numba.core.byteflow - DEBUG - dispatch pc=178, inst=POP_JUMP_IF_FALSE(arg=107, lineno=545)\n", - "2024-09-12 10:50:39,212 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$176compare_op.45']\n", - "2024-09-12 10:50:39,213 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=180, stack=('$phi90.0', '$phi90.1'), blockstack=(), npush=0), Edge(pc=212, stack=('$phi90.0', '$phi90.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,214 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=1), State(pc_initial=180 nstack_initial=2), State(pc_initial=212 nstack_initial=2)])\n", - "2024-09-12 10:50:39,214 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=180 nstack_initial=2), State(pc_initial=212 nstack_initial=2)])\n", - "2024-09-12 10:50:39,215 - numba.core.byteflow - DEBUG - stack: ['$phi180.0', '$phi180.1']\n", - "2024-09-12 10:50:39,215 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=180 nstack_initial=2)\n", - "2024-09-12 10:50:39,216 - numba.core.byteflow - DEBUG - dispatch pc=180, inst=LOAD_FAST(arg=4, lineno=546)\n", - "2024-09-12 10:50:39,216 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1']\n", - "2024-09-12 10:50:39,217 - numba.core.byteflow - DEBUG - dispatch pc=182, inst=LOAD_METHOD(arg=10, lineno=546)\n", - "2024-09-12 10:50:39,218 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$starts180.2']\n", - "2024-09-12 10:50:39,218 - numba.core.byteflow - DEBUG - dispatch pc=184, inst=LOAD_FAST(arg=9, lineno=546)\n", - "2024-09-12 10:50:39,219 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$182load_method.3']\n", - "2024-09-12 10:50:39,220 - numba.core.byteflow - DEBUG - dispatch pc=186, inst=CALL_METHOD(arg=1, lineno=546)\n", - "2024-09-12 10:50:39,220 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$182load_method.3', '$start184.4']\n", - "2024-09-12 10:50:39,221 - numba.core.byteflow - DEBUG - dispatch pc=188, inst=POP_TOP(arg=None, lineno=546)\n", - "2024-09-12 10:50:39,222 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$186call_method.5']\n", - "2024-09-12 10:50:39,222 - numba.core.byteflow - DEBUG - dispatch pc=190, inst=LOAD_FAST(arg=5, lineno=547)\n", - "2024-09-12 10:50:39,223 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1']\n", - "2024-09-12 10:50:39,224 - numba.core.byteflow - DEBUG - dispatch pc=192, inst=LOAD_METHOD(arg=10, lineno=547)\n", - "2024-09-12 10:50:39,224 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$stops190.6']\n", - "2024-09-12 10:50:39,225 - numba.core.byteflow - DEBUG - dispatch pc=194, inst=LOAD_FAST(arg=10, lineno=547)\n", - "2024-09-12 10:50:39,226 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$192load_method.7']\n", - "2024-09-12 10:50:39,226 - numba.core.byteflow - DEBUG - dispatch pc=196, inst=CALL_METHOD(arg=1, lineno=547)\n", - "2024-09-12 10:50:39,227 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$192load_method.7', '$stop194.8']\n", - "2024-09-12 10:50:39,228 - numba.core.byteflow - DEBUG - dispatch pc=198, inst=POP_TOP(arg=None, lineno=547)\n", - "2024-09-12 10:50:39,228 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$196call_method.9']\n", - "2024-09-12 10:50:39,229 - numba.core.byteflow - DEBUG - dispatch pc=200, inst=LOAD_FAST(arg=6, lineno=548)\n", - "2024-09-12 10:50:39,230 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1']\n", - "2024-09-12 10:50:39,230 - numba.core.byteflow - DEBUG - dispatch pc=202, inst=LOAD_FAST(arg=10, lineno=548)\n", - "2024-09-12 10:50:39,231 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$n_matches200.10']\n", - "2024-09-12 10:50:39,231 - numba.core.byteflow - DEBUG - dispatch pc=204, inst=LOAD_FAST(arg=9, lineno=548)\n", - "2024-09-12 10:50:39,232 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$n_matches200.10', '$stop202.11']\n", - "2024-09-12 10:50:39,233 - numba.core.byteflow - DEBUG - dispatch pc=206, inst=BINARY_SUBTRACT(arg=None, lineno=548)\n", - "2024-09-12 10:50:39,233 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$n_matches200.10', '$stop202.11', '$start204.12']\n", - "2024-09-12 10:50:39,234 - numba.core.byteflow - DEBUG - dispatch pc=208, inst=INPLACE_ADD(arg=None, lineno=548)\n", - "2024-09-12 10:50:39,235 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$n_matches200.10', '$206binary_subtract.13']\n", - "2024-09-12 10:50:39,235 - numba.core.byteflow - DEBUG - dispatch pc=210, inst=STORE_FAST(arg=6, lineno=548)\n", - "2024-09-12 10:50:39,236 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$208inplace_add.14']\n", - "2024-09-12 10:50:39,237 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=212, stack=('$phi180.0', '$phi180.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,237 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=212 nstack_initial=2), State(pc_initial=212 nstack_initial=2)])\n", - "2024-09-12 10:50:39,238 - numba.core.byteflow - DEBUG - stack: ['$phi212.0', '$phi212.1']\n", - "2024-09-12 10:50:39,239 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=212 nstack_initial=2)\n", - "2024-09-12 10:50:39,239 - numba.core.byteflow - DEBUG - dispatch pc=212, inst=JUMP_ABSOLUTE(arg=45, lineno=548)\n", - "2024-09-12 10:50:39,240 - numba.core.byteflow - DEBUG - stack ['$phi212.0', '$phi212.1']\n", - "2024-09-12 10:50:39,240 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=88, stack=('$phi212.0', '$phi212.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,241 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=212 nstack_initial=2), State(pc_initial=88 nstack_initial=2)])\n", - "2024-09-12 10:50:39,242 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=88 nstack_initial=2)])\n", - "2024-09-12 10:50:39,243 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:39,243 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=60 nstack_initial=1): {'$phi60.0'},\n", - " State(pc_initial=62 nstack_initial=2): {'$phi62.1'},\n", - " State(pc_initial=88 nstack_initial=2): {'$phi88.1'},\n", - " State(pc_initial=90 nstack_initial=3): {'$phi90.2'},\n", - " State(pc_initial=180 nstack_initial=2): set(),\n", - " State(pc_initial=212 nstack_initial=2): set(),\n", - " State(pc_initial=214 nstack_initial=1): set(),\n", - " State(pc_initial=216 nstack_initial=0): set()})\n", - "2024-09-12 10:50:39,244 - numba.core.byteflow - DEBUG - defmap: {'$phi60.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi62.1': State(pc_initial=60 nstack_initial=1),\n", - " '$phi88.1': State(pc_initial=62 nstack_initial=2),\n", - " '$phi90.2': State(pc_initial=88 nstack_initial=2)}\n", - "2024-09-12 10:50:39,245 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi180.0': {('$phi90.0', State(pc_initial=90 nstack_initial=3))},\n", - " '$phi180.1': {('$phi90.1', State(pc_initial=90 nstack_initial=3))},\n", - " '$phi212.0': {('$phi180.0',\n", - " State(pc_initial=180 nstack_initial=2)),\n", - " ('$phi90.0', State(pc_initial=90 nstack_initial=3))},\n", - " '$phi212.1': {('$phi180.1',\n", - " State(pc_initial=180 nstack_initial=2)),\n", - " ('$phi90.1', State(pc_initial=90 nstack_initial=3))},\n", - " '$phi214.0': {('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi60.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi214.0',\n", - " State(pc_initial=214 nstack_initial=1))},\n", - " '$phi62.0': {('$phi60.0', State(pc_initial=60 nstack_initial=1))},\n", - " '$phi62.1': {('$60for_iter.2',\n", - " State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.0': {('$phi212.0', State(pc_initial=212 nstack_initial=2)),\n", - " ('$phi62.0', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi88.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2)),\n", - " ('$phi212.1',\n", - " State(pc_initial=212 nstack_initial=2))},\n", - " '$phi90.0': {('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi90.1': {('$phi88.1', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3',\n", - " State(pc_initial=88 nstack_initial=2))}})\n", - "2024-09-12 10:50:39,246 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi180.0': {('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi180.1': {('$phi88.1', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi212.0': {('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi212.1': {('$phi88.1', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi214.0': {('$phi212.0',\n", - " State(pc_initial=212 nstack_initial=2)),\n", - " ('$phi62.0', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi60.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi212.0', State(pc_initial=212 nstack_initial=2)),\n", - " ('$phi62.0', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi62.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi212.0', State(pc_initial=212 nstack_initial=2)),\n", - " ('$phi62.0', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi62.1': {('$60for_iter.2',\n", - " State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi88.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2)),\n", - " ('$phi88.1', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi90.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi90.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3',\n", - " State(pc_initial=88 nstack_initial=2))}})\n", - "2024-09-12 10:50:39,248 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi180.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi180.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi212.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi212.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi214.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi60.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.1': {('$60for_iter.2',\n", - " State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi88.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi90.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3',\n", - " State(pc_initial=88 nstack_initial=2))}})\n", - "2024-09-12 10:50:39,249 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi180.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi180.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi212.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi212.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi214.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi60.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.1': {('$60for_iter.2',\n", - " State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi88.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi90.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3',\n", - " State(pc_initial=88 nstack_initial=2))}})\n", - "2024-09-12 10:50:39,251 - numba.core.byteflow - DEBUG - keep phismap: {'$phi60.0': {('$58get_iter.25', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.1': {('$60for_iter.2', State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.1': {('$86get_iter.13', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3', State(pc_initial=88 nstack_initial=2))}}\n", - "2024-09-12 10:50:39,252 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi60.0': '$58get_iter.25'},\n", - " State(pc_initial=60 nstack_initial=1): {'$phi62.1': '$60for_iter.2'},\n", - " State(pc_initial=62 nstack_initial=2): {'$phi88.1': '$86get_iter.13'},\n", - " State(pc_initial=88 nstack_initial=2): {'$phi90.2': '$88for_iter.3'}})\n", - "2024-09-12 10:50:39,253 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:39,253 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'item': '$4load_attr.1', 'res': '$6load_attr.2'}), (8, {'item': '$6load_attr.2', 'res': '$8load_method.3'}), (10, {'res': '$10load_global.4'}), (12, {'item': '$10load_global.4', 'res': '$12load_attr.5'}), (14, {'item': '$12load_attr.5', 'res': '$14load_attr.6'}), (16, {'func': '$8load_method.3', 'args': ['$14load_attr.6'], 'res': '$16call_method.7'}), (18, {'value': '$16call_method.7'}), (20, {'res': '$20load_global.8'}), (22, {'item': '$20load_global.8', 'res': '$22load_attr.9'}), (24, {'item': '$22load_attr.9', 'res': '$24load_attr.10'}), (26, {'item': '$24load_attr.10', 'res': '$26load_method.11'}), (28, {'res': '$28load_global.12'}), (30, {'item': '$28load_global.12', 'res': '$30load_attr.13'}), (32, {'item': '$30load_attr.13', 'res': '$32load_attr.14'}), (34, {'func': '$26load_method.11', 'args': ['$32load_attr.14'], 'res': '$34call_method.15'}), (36, {'value': '$34call_method.15'}), (38, {'res': '$38load_global.16'}), (40, {'item': '$38load_global.16', 'res': '$40load_method.17'}), (42, {'res': '$const42.18'}), (44, {'func': '$40load_method.17', 'args': ['$const42.18'], 'res': '$44call_method.19'}), (46, {'value': '$44call_method.19'}), (48, {'res': '$48load_global.20'}), (50, {'res': '$50load_global.21'}), (52, {'res': '$starts_old52.22'}), (54, {'func': '$50load_global.21', 'args': ['$starts_old52.22'], 'res': '$54call_function.23'}), (56, {'func': '$48load_global.20', 'args': ['$54call_function.23'], 'res': '$56call_function.24'}), (58, {'value': '$56call_function.24', 'res': '$58get_iter.25'})), outgoing_phis={'$phi60.0': '$58get_iter.25'}, blockstack=(), active_try_block=None, outgoing_edgepushed={60: ('$58get_iter.25',)})\n", - "2024-09-12 10:50:39,254 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=60 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((60, {'iterator': '$phi60.0', 'pair': '$60for_iter.1', 'indval': '$60for_iter.2', 'pred': '$60for_iter.3'}),), outgoing_phis={'$phi62.1': '$60for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={216: (), 62: ('$phi60.0', '$60for_iter.2')})\n", - "2024-09-12 10:50:39,255 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=62 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((62, {'value': '$phi62.1'}), (64, {'res': '$64load_global.2'}), (66, {'res': '$idx66.3'}), (68, {'res': '$const68.4'}), (70, {'index': '$const68.4', 'target': '$idx66.3', 'res': '$70binary_subscr.5'}), (72, {'res': '$idx72.6'}), (74, {'res': '$const74.7'}), (76, {'index': '$const74.7', 'target': '$idx72.6', 'res': '$76binary_subscr.8'}), (78, {'res': '$idx78.9'}), (80, {'res': '$const80.10'}), (82, {'index': '$const80.10', 'target': '$idx78.9', 'res': '$82binary_subscr.11'}), (84, {'func': '$64load_global.2', 'args': ['$70binary_subscr.5', '$76binary_subscr.8', '$82binary_subscr.11'], 'res': '$84call_function.12'}), (86, {'value': '$84call_function.12', 'res': '$86get_iter.13'})), outgoing_phis={'$phi88.1': '$86get_iter.13'}, blockstack=(), active_try_block=None, outgoing_edgepushed={88: ('$phi62.0', '$86get_iter.13')})\n", - "2024-09-12 10:50:39,256 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=88 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((88, {'iterator': '$phi88.1', 'pair': '$88for_iter.2', 'indval': '$88for_iter.3', 'pred': '$88for_iter.4'}),), outgoing_phis={'$phi90.2': '$88for_iter.3'}, blockstack=(), active_try_block=None, outgoing_edgepushed={214: ('$phi88.0',), 90: ('$phi88.0', '$phi88.1', '$88for_iter.3')})\n", - "2024-09-12 10:50:39,256 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=90 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((90, {'value': '$phi90.2'}), (92, {'res': '$92load_global.3'}), (94, {'item': '$92load_global.3', 'res': '$94load_attr.4'}), (96, {'res': '$c96.5'}), (98, {'res': '$starts_old98.6'}), (100, {'res': '$j100.7'}), (102, {'index': '$j100.7', 'target': '$starts_old98.6', 'res': '$102binary_subscr.8'}), (104, {'res': '$stops_old104.9'}), (106, {'res': '$j106.10'}), (108, {'index': '$j106.10', 'target': '$stops_old104.9', 'res': '$108binary_subscr.11'}), (110, {'start': '$102binary_subscr.8', 'stop': '$108binary_subscr.11', 'step': None, 'res': '$110build_slice.13', 'slicevar': '$110build_slice.12'}), (112, {'index': '$110build_slice.13', 'target': '$c96.5', 'res': '$112binary_subscr.14'}), (114, {'res': '$p_match114.15'}), (116, {'res': '$const116.16'}), (118, {'res': '$const118.17'}), (120, {'func': '$94load_attr.4', 'args': ['$112binary_subscr.14', '$p_match114.15', '$const116.16'], 'names': '$const118.17', 'res': '$120call_function_kw.18'}), (122, {'res': '$starts_old122.19'}), (124, {'res': '$j124.20'}), (126, {'index': '$j124.20', 'target': '$starts_old122.19', 'res': '$126binary_subscr.21'}), (128, {'lhs': '$120call_function_kw.18', 'rhs': '$126binary_subscr.21', 'res': '$128binary_add.22'}), (130, {'value': '$128binary_add.22'}), (132, {'res': '$132load_global.23'}), (134, {'item': '$132load_global.23', 'res': '$134load_attr.24'}), (136, {'res': '$c136.25'}), (138, {'res': '$starts_old138.26'}), (140, {'res': '$j140.27'}), (142, {'index': '$j140.27', 'target': '$starts_old138.26', 'res': '$142binary_subscr.28'}), (144, {'res': '$stops_old144.29'}), (146, {'res': '$j146.30'}), (148, {'index': '$j146.30', 'target': '$stops_old144.29', 'res': '$148binary_subscr.31'}), (150, {'start': '$142binary_subscr.28', 'stop': '$148binary_subscr.31', 'step': None, 'res': '$150build_slice.33', 'slicevar': '$150build_slice.32'}), (152, {'index': '$150build_slice.33', 'target': '$c136.25', 'res': '$152binary_subscr.34'}), (154, {'res': '$p_match154.35'}), (156, {'res': '$const156.36'}), (158, {'res': '$const158.37'}), (160, {'func': '$134load_attr.24', 'args': ['$152binary_subscr.34', '$p_match154.35', '$const156.36'], 'names': '$const158.37', 'res': '$160call_function_kw.38'}), (162, {'res': '$starts_old162.39'}), (164, {'res': '$j164.40'}), (166, {'index': '$j164.40', 'target': '$starts_old162.39', 'res': '$166binary_subscr.41'}), (168, {'lhs': '$160call_function_kw.38', 'rhs': '$166binary_subscr.41', 'res': '$168binary_add.42'}), (170, {'value': '$168binary_add.42'}), (172, {'res': '$start172.43'}), (174, {'res': '$stop174.44'}), (176, {'lhs': '$start172.43', 'rhs': '$stop174.44', 'res': '$176compare_op.45'}), (178, {'pred': '$176compare_op.45'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={180: ('$phi90.0', '$phi90.1'), 212: ('$phi90.0', '$phi90.1')})\n", - "2024-09-12 10:50:39,257 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=180 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((180, {'res': '$starts180.2'}), (182, {'item': '$starts180.2', 'res': '$182load_method.3'}), (184, {'res': '$start184.4'}), (186, {'func': '$182load_method.3', 'args': ['$start184.4'], 'res': '$186call_method.5'}), (190, {'res': '$stops190.6'}), (192, {'item': '$stops190.6', 'res': '$192load_method.7'}), (194, {'res': '$stop194.8'}), (196, {'func': '$192load_method.7', 'args': ['$stop194.8'], 'res': '$196call_method.9'}), (200, {'res': '$n_matches200.10'}), (202, {'res': '$stop202.11'}), (204, {'res': '$start204.12'}), (206, {'lhs': '$stop202.11', 'rhs': '$start204.12', 'res': '$206binary_subtract.13'}), (208, {'lhs': '$n_matches200.10', 'rhs': '$206binary_subtract.13', 'res': '$208inplace_add.14'}), (210, {'value': '$208inplace_add.14'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={212: ('$phi180.0', '$phi180.1')})\n", - "2024-09-12 10:50:39,258 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=212 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((212, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={88: ('$phi212.0', '$phi212.1')})\n", - "2024-09-12 10:50:39,258 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=214 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((214, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={60: ('$phi214.0',)})\n", - "2024-09-12 10:50:39,259 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=216 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((216, {'res': '$starts216.0'}), (218, {'res': '$stops218.1'}), (220, {'res': '$n_matches220.2'}), (222, {'items': ['$starts216.0', '$stops218.1', '$n_matches220.2'], 'res': '$222build_tuple.3'}), (224, {'retval': '$222build_tuple.3', 'castval': '$224return_value.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:39,269 - numba.core.interpreter - DEBUG - label 0:\n", - " starts_old = arg(0, name=starts_old) ['starts_old']\n", - " stops_old = arg(1, name=stops_old) ['stops_old']\n", - " c = arg(2, name=c) ['c']\n", - " idx = arg(3, name=idx) ['idx']\n", - " $2load_global.0 = global(numba: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=typed) ['$2load_global.0', '$4load_attr.1']\n", - " $6load_attr.2 = getattr(value=$4load_attr.1, attr=List) ['$4load_attr.1', '$6load_attr.2']\n", - " $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list) ['$6load_attr.2', '$8load_method.3']\n", - " $10load_global.4 = global(numba: ) ['$10load_global.4']\n", - " $12load_attr.5 = getattr(value=$10load_global.4, attr=types) ['$10load_global.4', '$12load_attr.5']\n", - " $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp) ['$12load_attr.5', '$14load_attr.6']\n", - " starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:534)], kws=(), vararg=None, varkwarg=None, target=None) ['$14load_attr.6', '$8load_method.3', 'starts']\n", - " $20load_global.8 = global(numba: ) ['$20load_global.8']\n", - " $22load_attr.9 = getattr(value=$20load_global.8, attr=typed) ['$20load_global.8', '$22load_attr.9']\n", - " $24load_attr.10 = getattr(value=$22load_attr.9, attr=List) ['$22load_attr.9', '$24load_attr.10']\n", - " $26load_method.11 = getattr(value=$24load_attr.10, attr=empty_list) ['$24load_attr.10', '$26load_method.11']\n", - " $28load_global.12 = global(numba: ) ['$28load_global.12']\n", - " $30load_attr.13 = getattr(value=$28load_global.12, attr=types) ['$28load_global.12', '$30load_attr.13']\n", - " $32load_attr.14 = getattr(value=$30load_attr.13, attr=intp) ['$30load_attr.13', '$32load_attr.14']\n", - " stops = call $26load_method.11($32load_attr.14, func=$26load_method.11, args=[Var($32load_attr.14, indexing.py:535)], kws=(), vararg=None, varkwarg=None, target=None) ['$26load_method.11', '$32load_attr.14', 'stops']\n", - " $38load_global.16 = global(np: ) ['$38load_global.16']\n", - " $40load_method.17 = getattr(value=$38load_global.16, attr=intp) ['$38load_global.16', '$40load_method.17']\n", - " $const42.18 = const(int, 0) ['$const42.18']\n", - " n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None) ['$40load_method.17', '$const42.18', 'n_matches']\n", - " $48load_global.20 = global(range: ) ['$48load_global.20']\n", - " $50load_global.21 = global(len: ) ['$50load_global.21']\n", - " $54call_function.23 = call $50load_global.21(starts_old, func=$50load_global.21, args=[Var(starts_old, indexing.py:494)], kws=(), vararg=None, varkwarg=None, target=None) ['$50load_global.21', '$54call_function.23', 'starts_old']\n", - " $56call_function.24 = call $48load_global.20($54call_function.23, func=$48load_global.20, args=[Var($54call_function.23, indexing.py:538)], kws=(), vararg=None, varkwarg=None, target=None) ['$48load_global.20', '$54call_function.23', '$56call_function.24']\n", - " $58get_iter.25 = getiter(value=$56call_function.24) ['$56call_function.24', '$58get_iter.25']\n", - " $phi60.0 = $58get_iter.25 ['$58get_iter.25', '$phi60.0']\n", - " jump 60 []\n", - "label 60:\n", - " $60for_iter.1 = iternext(value=$phi60.0) ['$60for_iter.1', '$phi60.0']\n", - " $60for_iter.2 = pair_first(value=$60for_iter.1) ['$60for_iter.1', '$60for_iter.2']\n", - " $60for_iter.3 = pair_second(value=$60for_iter.1) ['$60for_iter.1', '$60for_iter.3']\n", - " $phi62.1 = $60for_iter.2 ['$60for_iter.2', '$phi62.1']\n", - " branch $60for_iter.3, 62, 216 ['$60for_iter.3']\n", - "label 62:\n", - " j = $phi62.1 ['$phi62.1', 'j']\n", - " $64load_global.2 = global(range: ) ['$64load_global.2']\n", - " $const68.4 = const(int, 0) ['$const68.4']\n", - " $70binary_subscr.5 = getitem(value=idx, index=$const68.4, fn=) ['$70binary_subscr.5', '$const68.4', 'idx']\n", - " $const74.7 = const(int, 1) ['$const74.7']\n", - " $76binary_subscr.8 = getitem(value=idx, index=$const74.7, fn=) ['$76binary_subscr.8', '$const74.7', 'idx']\n", - " $const80.10 = const(int, 2) ['$const80.10']\n", - " $82binary_subscr.11 = getitem(value=idx, index=$const80.10, fn=) ['$82binary_subscr.11', '$const80.10', 'idx']\n", - " $84call_function.12 = call $64load_global.2($70binary_subscr.5, $76binary_subscr.8, $82binary_subscr.11, func=$64load_global.2, args=[Var($70binary_subscr.5, indexing.py:541), Var($76binary_subscr.8, indexing.py:541), Var($82binary_subscr.11, indexing.py:541)], kws=(), vararg=None, varkwarg=None, target=None) ['$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8', '$82binary_subscr.11', '$84call_function.12']\n", - " $86get_iter.13 = getiter(value=$84call_function.12) ['$84call_function.12', '$86get_iter.13']\n", - " $phi88.1 = $86get_iter.13 ['$86get_iter.13', '$phi88.1']\n", - " jump 88 []\n", - "label 88:\n", - " $88for_iter.2 = iternext(value=$phi88.1) ['$88for_iter.2', '$phi88.1']\n", - " $88for_iter.3 = pair_first(value=$88for_iter.2) ['$88for_iter.2', '$88for_iter.3']\n", - " $88for_iter.4 = pair_second(value=$88for_iter.2) ['$88for_iter.2', '$88for_iter.4']\n", - " $phi90.2 = $88for_iter.3 ['$88for_iter.3', '$phi90.2']\n", - " branch $88for_iter.4, 90, 214 ['$88for_iter.4']\n", - "label 90:\n", - " p_match = $phi90.2 ['$phi90.2', 'p_match']\n", - " $92load_global.3 = global(np: ) ['$92load_global.3']\n", - " $94load_attr.4 = getattr(value=$92load_global.3, attr=searchsorted) ['$92load_global.3', '$94load_attr.4']\n", - " $102binary_subscr.8 = getitem(value=starts_old, index=j, fn=) ['$102binary_subscr.8', 'j', 'starts_old']\n", - " $108binary_subscr.11 = getitem(value=stops_old, index=j, fn=) ['$108binary_subscr.11', 'j', 'stops_old']\n", - " $110build_slice.12 = global(slice: ) ['$110build_slice.12']\n", - " $110build_slice.13 = call $110build_slice.12($102binary_subscr.8, $108binary_subscr.11, func=$110build_slice.12, args=(Var($102binary_subscr.8, indexing.py:542), Var($108binary_subscr.11, indexing.py:542)), kws=(), vararg=None, varkwarg=None, target=None) ['$102binary_subscr.8', '$108binary_subscr.11', '$110build_slice.12', '$110build_slice.13']\n", - " $112binary_subscr.14 = getitem(value=c, index=$110build_slice.13, fn=) ['$110build_slice.13', '$112binary_subscr.14', 'c']\n", - " $const116.16 = const(str, left) ['$const116.16']\n", - " $120call_function_kw.18 = call $94load_attr.4($112binary_subscr.14, p_match, func=$94load_attr.4, args=[Var($112binary_subscr.14, indexing.py:542), Var(p_match, indexing.py:541)], kws=[('side', Var($const116.16, indexing.py:542))], vararg=None, varkwarg=None, target=None) ['$112binary_subscr.14', '$120call_function_kw.18', '$94load_attr.4', '$const116.16', 'p_match']\n", - " $126binary_subscr.21 = getitem(value=starts_old, index=j, fn=) ['$126binary_subscr.21', 'j', 'starts_old']\n", - " start = $120call_function_kw.18 + $126binary_subscr.21 ['$120call_function_kw.18', '$126binary_subscr.21', 'start']\n", - " $132load_global.23 = global(np: ) ['$132load_global.23']\n", - " $134load_attr.24 = getattr(value=$132load_global.23, attr=searchsorted) ['$132load_global.23', '$134load_attr.24']\n", - " $142binary_subscr.28 = getitem(value=starts_old, index=j, fn=) ['$142binary_subscr.28', 'j', 'starts_old']\n", - " $148binary_subscr.31 = getitem(value=stops_old, index=j, fn=) ['$148binary_subscr.31', 'j', 'stops_old']\n", - " $150build_slice.32 = global(slice: ) ['$150build_slice.32']\n", - " $150build_slice.33 = call $150build_slice.32($142binary_subscr.28, $148binary_subscr.31, func=$150build_slice.32, args=(Var($142binary_subscr.28, indexing.py:543), Var($148binary_subscr.31, indexing.py:543)), kws=(), vararg=None, varkwarg=None, target=None) ['$142binary_subscr.28', '$148binary_subscr.31', '$150build_slice.32', '$150build_slice.33']\n", - " $152binary_subscr.34 = getitem(value=c, index=$150build_slice.33, fn=) ['$150build_slice.33', '$152binary_subscr.34', 'c']\n", - " $const156.36 = const(str, right) ['$const156.36']\n", - " $160call_function_kw.38 = call $134load_attr.24($152binary_subscr.34, p_match, func=$134load_attr.24, args=[Var($152binary_subscr.34, indexing.py:543), Var(p_match, indexing.py:541)], kws=[('side', Var($const156.36, indexing.py:543))], vararg=None, varkwarg=None, target=None) ['$134load_attr.24', '$152binary_subscr.34', '$160call_function_kw.38', '$const156.36', 'p_match']\n", - " $166binary_subscr.41 = getitem(value=starts_old, index=j, fn=) ['$166binary_subscr.41', 'j', 'starts_old']\n", - " stop = $160call_function_kw.38 + $166binary_subscr.41 ['$160call_function_kw.38', '$166binary_subscr.41', 'stop']\n", - " $176compare_op.45 = start != stop ['$176compare_op.45', 'start', 'stop']\n", - " bool178 = global(bool: ) ['bool178']\n", - " $178pred = call bool178($176compare_op.45, func=bool178, args=(Var($176compare_op.45, indexing.py:545),), kws=(), vararg=None, varkwarg=None, target=None) ['$176compare_op.45', '$178pred', 'bool178']\n", - " branch $178pred, 180, 212 ['$178pred']\n", - "label 180:\n", - " $182load_method.3 = getattr(value=starts, attr=append) ['$182load_method.3', 'starts']\n", - " $186call_method.5 = call $182load_method.3(start, func=$182load_method.3, args=[Var(start, indexing.py:542)], kws=(), vararg=None, varkwarg=None, target=None) ['$182load_method.3', '$186call_method.5', 'start']\n", - " $192load_method.7 = getattr(value=stops, attr=append) ['$192load_method.7', 'stops']\n", - " $196call_method.9 = call $192load_method.7(stop, func=$192load_method.7, args=[Var(stop, indexing.py:543)], kws=(), vararg=None, varkwarg=None, target=None) ['$192load_method.7', '$196call_method.9', 'stop']\n", - " $206binary_subtract.13 = stop - start ['$206binary_subtract.13', 'start', 'stop']\n", - " $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined) ['$206binary_subtract.13', '$208inplace_add.14', 'n_matches']\n", - " n_matches = $208inplace_add.14 ['$208inplace_add.14', 'n_matches']\n", - " jump 212 []\n", - "label 212:\n", - " jump 88 []\n", - "label 214:\n", - " jump 60 []\n", - "label 216:\n", - " $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)]) ['$222build_tuple.3', 'n_matches', 'starts', 'stops']\n", - " $224return_value.4 = cast(value=$222build_tuple.3) ['$222build_tuple.3', '$224return_value.4']\n", - " return $224return_value.4 ['$224return_value.4']\n", - "\n", - "2024-09-12 10:50:39,364 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:39,365 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,366 - numba.core.ssa - DEBUG - on stmt: starts_old = arg(0, name=starts_old)\n", - "2024-09-12 10:50:39,366 - numba.core.ssa - DEBUG - on stmt: stops_old = arg(1, name=stops_old)\n", - "2024-09-12 10:50:39,367 - numba.core.ssa - DEBUG - on stmt: c = arg(2, name=c)\n", - "2024-09-12 10:50:39,367 - numba.core.ssa - DEBUG - on stmt: idx = arg(3, name=idx)\n", - "2024-09-12 10:50:39,368 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:39,369 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:39,369 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:39,370 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:39,370 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:39,371 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:39,371 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:39,372 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:534)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,372 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(numba: )\n", - "2024-09-12 10:50:39,373 - numba.core.ssa - DEBUG - on stmt: $22load_attr.9 = getattr(value=$20load_global.8, attr=typed)\n", - "2024-09-12 10:50:39,373 - numba.core.ssa - DEBUG - on stmt: $24load_attr.10 = getattr(value=$22load_attr.9, attr=List)\n", - "2024-09-12 10:50:39,374 - numba.core.ssa - DEBUG - on stmt: $26load_method.11 = getattr(value=$24load_attr.10, attr=empty_list)\n", - "2024-09-12 10:50:39,377 - numba.core.ssa - DEBUG - on stmt: $28load_global.12 = global(numba: )\n", - "2024-09-12 10:50:39,377 - numba.core.ssa - DEBUG - on stmt: $30load_attr.13 = getattr(value=$28load_global.12, attr=types)\n", - "2024-09-12 10:50:39,378 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30load_attr.13, attr=intp)\n", - "2024-09-12 10:50:39,378 - numba.core.ssa - DEBUG - on stmt: stops = call $26load_method.11($32load_attr.14, func=$26load_method.11, args=[Var($32load_attr.14, indexing.py:535)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,379 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(np: )\n", - "2024-09-12 10:50:39,379 - numba.core.ssa - DEBUG - on stmt: $40load_method.17 = getattr(value=$38load_global.16, attr=intp)\n", - "2024-09-12 10:50:39,380 - numba.core.ssa - DEBUG - on stmt: $const42.18 = const(int, 0)\n", - "2024-09-12 10:50:39,380 - numba.core.ssa - DEBUG - on stmt: n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,381 - numba.core.ssa - DEBUG - on stmt: $48load_global.20 = global(range: )\n", - "2024-09-12 10:50:39,382 - numba.core.ssa - DEBUG - on stmt: $50load_global.21 = global(len: )\n", - "2024-09-12 10:50:39,382 - numba.core.ssa - DEBUG - on stmt: $54call_function.23 = call $50load_global.21(starts_old, func=$50load_global.21, args=[Var(starts_old, indexing.py:494)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,383 - numba.core.ssa - DEBUG - on stmt: $56call_function.24 = call $48load_global.20($54call_function.23, func=$48load_global.20, args=[Var($54call_function.23, indexing.py:538)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,383 - numba.core.ssa - DEBUG - on stmt: $58get_iter.25 = getiter(value=$56call_function.24)\n", - "2024-09-12 10:50:39,384 - numba.core.ssa - DEBUG - on stmt: $phi60.0 = $58get_iter.25\n", - "2024-09-12 10:50:39,384 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:39,385 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 60\n", - "2024-09-12 10:50:39,385 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,386 - numba.core.ssa - DEBUG - on stmt: $60for_iter.1 = iternext(value=$phi60.0)\n", - "2024-09-12 10:50:39,386 - numba.core.ssa - DEBUG - on stmt: $60for_iter.2 = pair_first(value=$60for_iter.1)\n", - "2024-09-12 10:50:39,387 - numba.core.ssa - DEBUG - on stmt: $60for_iter.3 = pair_second(value=$60for_iter.1)\n", - "2024-09-12 10:50:39,387 - numba.core.ssa - DEBUG - on stmt: $phi62.1 = $60for_iter.2\n", - "2024-09-12 10:50:39,388 - numba.core.ssa - DEBUG - on stmt: branch $60for_iter.3, 62, 216\n", - "2024-09-12 10:50:39,388 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 62\n", - "2024-09-12 10:50:39,389 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,389 - numba.core.ssa - DEBUG - on stmt: j = $phi62.1\n", - "2024-09-12 10:50:39,390 - numba.core.ssa - DEBUG - on stmt: $64load_global.2 = global(range: )\n", - "2024-09-12 10:50:39,390 - numba.core.ssa - DEBUG - on stmt: $const68.4 = const(int, 0)\n", - "2024-09-12 10:50:39,391 - numba.core.ssa - DEBUG - on stmt: $70binary_subscr.5 = static_getitem(value=idx, index=0, index_var=$const68.4, fn=)\n", - "2024-09-12 10:50:39,391 - numba.core.ssa - DEBUG - on stmt: $const74.7 = const(int, 1)\n", - "2024-09-12 10:50:39,392 - numba.core.ssa - DEBUG - on stmt: $76binary_subscr.8 = static_getitem(value=idx, index=1, index_var=$const74.7, fn=)\n", - "2024-09-12 10:50:39,396 - numba.core.ssa - DEBUG - on stmt: $const80.10 = const(int, 2)\n", - "2024-09-12 10:50:39,397 - numba.core.ssa - DEBUG - on stmt: $82binary_subscr.11 = static_getitem(value=idx, index=2, index_var=$const80.10, fn=)\n", - "2024-09-12 10:50:39,397 - numba.core.ssa - DEBUG - on stmt: $84call_function.12 = call $64load_global.2($70binary_subscr.5, $76binary_subscr.8, $82binary_subscr.11, func=$64load_global.2, args=[Var($70binary_subscr.5, indexing.py:541), Var($76binary_subscr.8, indexing.py:541), Var($82binary_subscr.11, indexing.py:541)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,398 - numba.core.ssa - DEBUG - on stmt: $86get_iter.13 = getiter(value=$84call_function.12)\n", - "2024-09-12 10:50:39,398 - numba.core.ssa - DEBUG - on stmt: $phi88.1 = $86get_iter.13\n", - "2024-09-12 10:50:39,399 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:39,400 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 88\n", - "2024-09-12 10:50:39,400 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,401 - numba.core.ssa - DEBUG - on stmt: $88for_iter.2 = iternext(value=$phi88.1)\n", - "2024-09-12 10:50:39,401 - numba.core.ssa - DEBUG - on stmt: $88for_iter.3 = pair_first(value=$88for_iter.2)\n", - "2024-09-12 10:50:39,402 - numba.core.ssa - DEBUG - on stmt: $88for_iter.4 = pair_second(value=$88for_iter.2)\n", - "2024-09-12 10:50:39,402 - numba.core.ssa - DEBUG - on stmt: $phi90.2 = $88for_iter.3\n", - "2024-09-12 10:50:39,403 - numba.core.ssa - DEBUG - on stmt: branch $88for_iter.4, 90, 214\n", - "2024-09-12 10:50:39,403 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 90\n", - "2024-09-12 10:50:39,404 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,405 - numba.core.ssa - DEBUG - on stmt: p_match = $phi90.2\n", - "2024-09-12 10:50:39,407 - numba.core.ssa - DEBUG - on stmt: $92load_global.3 = global(np: )\n", - "2024-09-12 10:50:39,407 - numba.core.ssa - DEBUG - on stmt: $94load_attr.4 = getattr(value=$92load_global.3, attr=searchsorted)\n", - "2024-09-12 10:50:39,408 - numba.core.ssa - DEBUG - on stmt: $102binary_subscr.8 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,408 - numba.core.ssa - DEBUG - on stmt: $108binary_subscr.11 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:39,409 - numba.core.ssa - DEBUG - on stmt: $110build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:39,410 - numba.core.ssa - DEBUG - on stmt: $110build_slice.13 = call $110build_slice.12($102binary_subscr.8, $108binary_subscr.11, func=$110build_slice.12, args=(Var($102binary_subscr.8, indexing.py:542), Var($108binary_subscr.11, indexing.py:542)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,410 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.14 = getitem(value=c, index=$110build_slice.13, fn=)\n", - "2024-09-12 10:50:39,411 - numba.core.ssa - DEBUG - on stmt: $const116.16 = const(str, left)\n", - "2024-09-12 10:50:39,412 - numba.core.ssa - DEBUG - on stmt: $120call_function_kw.18 = call $94load_attr.4($112binary_subscr.14, p_match, func=$94load_attr.4, args=[Var($112binary_subscr.14, indexing.py:542), Var(p_match, indexing.py:541)], kws=[('side', Var($const116.16, indexing.py:542))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,412 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.21 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,414 - numba.core.ssa - DEBUG - on stmt: start = $120call_function_kw.18 + $126binary_subscr.21\n", - "2024-09-12 10:50:39,414 - numba.core.ssa - DEBUG - on stmt: $132load_global.23 = global(np: )\n", - "2024-09-12 10:50:39,415 - numba.core.ssa - DEBUG - on stmt: $134load_attr.24 = getattr(value=$132load_global.23, attr=searchsorted)\n", - "2024-09-12 10:50:39,415 - numba.core.ssa - DEBUG - on stmt: $142binary_subscr.28 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,416 - numba.core.ssa - DEBUG - on stmt: $148binary_subscr.31 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:39,417 - numba.core.ssa - DEBUG - on stmt: $150build_slice.32 = global(slice: )\n", - "2024-09-12 10:50:39,417 - numba.core.ssa - DEBUG - on stmt: $150build_slice.33 = call $150build_slice.32($142binary_subscr.28, $148binary_subscr.31, func=$150build_slice.32, args=(Var($142binary_subscr.28, indexing.py:543), Var($148binary_subscr.31, indexing.py:543)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,418 - numba.core.ssa - DEBUG - on stmt: $152binary_subscr.34 = getitem(value=c, index=$150build_slice.33, fn=)\n", - "2024-09-12 10:50:39,419 - numba.core.ssa - DEBUG - on stmt: $const156.36 = const(str, right)\n", - "2024-09-12 10:50:39,419 - numba.core.ssa - DEBUG - on stmt: $160call_function_kw.38 = call $134load_attr.24($152binary_subscr.34, p_match, func=$134load_attr.24, args=[Var($152binary_subscr.34, indexing.py:543), Var(p_match, indexing.py:541)], kws=[('side', Var($const156.36, indexing.py:543))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,420 - numba.core.ssa - DEBUG - on stmt: $166binary_subscr.41 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,420 - numba.core.ssa - DEBUG - on stmt: stop = $160call_function_kw.38 + $166binary_subscr.41\n", - "2024-09-12 10:50:39,421 - numba.core.ssa - DEBUG - on stmt: $176compare_op.45 = start != stop\n", - "2024-09-12 10:50:39,421 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:39,422 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.45, func=bool178, args=(Var($176compare_op.45, indexing.py:545),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,422 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 212\n", - "2024-09-12 10:50:39,424 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 180\n", - "2024-09-12 10:50:39,425 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,425 - numba.core.ssa - DEBUG - on stmt: $182load_method.3 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:39,426 - numba.core.ssa - DEBUG - on stmt: $186call_method.5 = call $182load_method.3(start, func=$182load_method.3, args=[Var(start, indexing.py:542)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,427 - numba.core.ssa - DEBUG - on stmt: $192load_method.7 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:39,427 - numba.core.ssa - DEBUG - on stmt: $196call_method.9 = call $192load_method.7(stop, func=$192load_method.7, args=[Var(stop, indexing.py:543)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,428 - numba.core.ssa - DEBUG - on stmt: $206binary_subtract.13 = stop - start\n", - "2024-09-12 10:50:39,428 - numba.core.ssa - DEBUG - on stmt: $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:39,429 - numba.core.ssa - DEBUG - on stmt: n_matches = $208inplace_add.14\n", - "2024-09-12 10:50:39,429 - numba.core.ssa - DEBUG - on stmt: jump 212\n", - "2024-09-12 10:50:39,430 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 212\n", - "2024-09-12 10:50:39,430 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,431 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:39,431 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 214\n", - "2024-09-12 10:50:39,432 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,434 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:39,435 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 216\n", - "2024-09-12 10:50:39,435 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,436 - numba.core.ssa - DEBUG - on stmt: $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)])\n", - "2024-09-12 10:50:39,437 - numba.core.ssa - DEBUG - on stmt: $224return_value.4 = cast(value=$222build_tuple.3)\n", - "2024-09-12 10:50:39,438 - numba.core.ssa - DEBUG - on stmt: return $224return_value.4\n", - "2024-09-12 10:50:39,441 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102binary_subscr.8': [],\n", - " '$108binary_subscr.11': [],\n", - " '$10load_global.4': [],\n", - " '$110build_slice.12': [],\n", - " '$110build_slice.13': [],\n", - " '$112binary_subscr.14': [],\n", - " '$120call_function_kw.18': [],\n", - " '$126binary_subscr.21': [],\n", - " '$12load_attr.5': [],\n", - " '$132load_global.23': [],\n", - " '$134load_attr.24': [],\n", - " '$142binary_subscr.28': [],\n", - " '$148binary_subscr.31': [],\n", - " '$14load_attr.6': [],\n", - " '$150build_slice.32': [],\n", - " '$150build_slice.33': [],\n", - " '$152binary_subscr.34': [],\n", - " '$160call_function_kw.38': [],\n", - " '$166binary_subscr.41': [],\n", - " '$176compare_op.45': [],\n", - " '$178pred': [],\n", - " '$182load_method.3': [],\n", - " '$186call_method.5': [],\n", - " '$192load_method.7': [],\n", - " '$196call_method.9': [],\n", - " '$206binary_subtract.13': [],\n", - " '$208inplace_add.14': [],\n", - " '$20load_global.8': [],\n", - " '$222build_tuple.3': [],\n", - " '$224return_value.4': [],\n", - " '$22load_attr.9': [],\n", - " '$24load_attr.10': [],\n", - " '$26load_method.11': [],\n", - " '$28load_global.12': [],\n", - " '$2load_global.0': [],\n", - " '$30load_attr.13': [],\n", - " '$32load_attr.14': [],\n", - " '$38load_global.16': [],\n", - " '$40load_method.17': [],\n", - " '$48load_global.20': [],\n", - " '$4load_attr.1': [],\n", - " '$50load_global.21': [],\n", - " '$54call_function.23': [],\n", - " '$56call_function.24': [],\n", - " '$58get_iter.25': [],\n", - " '$60for_iter.1': [],\n", - " '$60for_iter.2': [],\n", - " '$60for_iter.3': [],\n", - " '$64load_global.2': [],\n", - " '$6load_attr.2': [],\n", - " '$70binary_subscr.5': [],\n", - " '$76binary_subscr.8': [],\n", - " '$82binary_subscr.11': [],\n", - " '$84call_function.12': [],\n", - " '$86get_iter.13': [],\n", - " '$88for_iter.2': [],\n", - " '$88for_iter.3': [],\n", - " '$88for_iter.4': [],\n", - " '$8load_method.3': [],\n", - " '$92load_global.3': [],\n", - " '$94load_attr.4': [],\n", - " '$const116.16': [],\n", - " '$const156.36': [],\n", - " '$const42.18': [],\n", - " '$const68.4': [],\n", - " '$const74.7': [],\n", - " '$const80.10': [],\n", - " '$phi60.0': [],\n", - " '$phi62.1': [],\n", - " '$phi88.1': [],\n", - " '$phi90.2': [],\n", - " 'bool178': [],\n", - " 'c': [],\n", - " 'idx': [],\n", - " 'j': [],\n", - " 'n_matches': [,\n", - " ],\n", - " 'p_match': [],\n", - " 'start': [],\n", - " 'starts': [],\n", - " 'starts_old': [],\n", - " 'stop': [],\n", - " 'stops': [],\n", - " 'stops_old': []})\n", - "2024-09-12 10:50:39,441 - numba.core.ssa - DEBUG - SSA violators {'n_matches'}\n", - "2024-09-12 10:50:39,442 - numba.core.ssa - DEBUG - Fix SSA violator on var n_matches\n", - "2024-09-12 10:50:39,443 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:39,443 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,444 - numba.core.ssa - DEBUG - on stmt: starts_old = arg(0, name=starts_old)\n", - "2024-09-12 10:50:39,444 - numba.core.ssa - DEBUG - on stmt: stops_old = arg(1, name=stops_old)\n", - "2024-09-12 10:50:39,445 - numba.core.ssa - DEBUG - on stmt: c = arg(2, name=c)\n", - "2024-09-12 10:50:39,445 - numba.core.ssa - DEBUG - on stmt: idx = arg(3, name=idx)\n", - "2024-09-12 10:50:39,446 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:39,446 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:39,447 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:39,447 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:39,448 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:39,449 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:39,449 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:39,450 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:534)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,450 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(numba: )\n", - "2024-09-12 10:50:39,451 - numba.core.ssa - DEBUG - on stmt: $22load_attr.9 = getattr(value=$20load_global.8, attr=typed)\n", - "2024-09-12 10:50:39,451 - numba.core.ssa - DEBUG - on stmt: $24load_attr.10 = getattr(value=$22load_attr.9, attr=List)\n", - "2024-09-12 10:50:39,454 - numba.core.ssa - DEBUG - on stmt: $26load_method.11 = getattr(value=$24load_attr.10, attr=empty_list)\n", - "2024-09-12 10:50:39,455 - numba.core.ssa - DEBUG - on stmt: $28load_global.12 = global(numba: )\n", - "2024-09-12 10:50:39,455 - numba.core.ssa - DEBUG - on stmt: $30load_attr.13 = getattr(value=$28load_global.12, attr=types)\n", - "2024-09-12 10:50:39,456 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30load_attr.13, attr=intp)\n", - "2024-09-12 10:50:39,456 - numba.core.ssa - DEBUG - on stmt: stops = call $26load_method.11($32load_attr.14, func=$26load_method.11, args=[Var($32load_attr.14, indexing.py:535)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,457 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(np: )\n", - "2024-09-12 10:50:39,458 - numba.core.ssa - DEBUG - on stmt: $40load_method.17 = getattr(value=$38load_global.16, attr=intp)\n", - "2024-09-12 10:50:39,458 - numba.core.ssa - DEBUG - on stmt: $const42.18 = const(int, 0)\n", - "2024-09-12 10:50:39,459 - numba.core.ssa - DEBUG - on stmt: n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,459 - numba.core.ssa - DEBUG - first assign: n_matches\n", - "2024-09-12 10:50:39,460 - numba.core.ssa - DEBUG - replaced with: n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,460 - numba.core.ssa - DEBUG - on stmt: $48load_global.20 = global(range: )\n", - "2024-09-12 10:50:39,461 - numba.core.ssa - DEBUG - on stmt: $50load_global.21 = global(len: )\n", - "2024-09-12 10:50:39,461 - numba.core.ssa - DEBUG - on stmt: $54call_function.23 = call $50load_global.21(starts_old, func=$50load_global.21, args=[Var(starts_old, indexing.py:494)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,464 - numba.core.ssa - DEBUG - on stmt: $56call_function.24 = call $48load_global.20($54call_function.23, func=$48load_global.20, args=[Var($54call_function.23, indexing.py:538)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,464 - numba.core.ssa - DEBUG - on stmt: $58get_iter.25 = getiter(value=$56call_function.24)\n", - "2024-09-12 10:50:39,465 - numba.core.ssa - DEBUG - on stmt: $phi60.0 = $58get_iter.25\n", - "2024-09-12 10:50:39,466 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:39,466 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:39,467 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,467 - numba.core.ssa - DEBUG - on stmt: $60for_iter.1 = iternext(value=$phi60.0)\n", - "2024-09-12 10:50:39,468 - numba.core.ssa - DEBUG - on stmt: $60for_iter.2 = pair_first(value=$60for_iter.1)\n", - "2024-09-12 10:50:39,468 - numba.core.ssa - DEBUG - on stmt: $60for_iter.3 = pair_second(value=$60for_iter.1)\n", - "2024-09-12 10:50:39,469 - numba.core.ssa - DEBUG - on stmt: $phi62.1 = $60for_iter.2\n", - "2024-09-12 10:50:39,469 - numba.core.ssa - DEBUG - on stmt: branch $60for_iter.3, 62, 216\n", - "2024-09-12 10:50:39,470 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 62\n", - "2024-09-12 10:50:39,470 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,471 - numba.core.ssa - DEBUG - on stmt: j = $phi62.1\n", - "2024-09-12 10:50:39,473 - numba.core.ssa - DEBUG - on stmt: $64load_global.2 = global(range: )\n", - "2024-09-12 10:50:39,473 - numba.core.ssa - DEBUG - on stmt: $const68.4 = const(int, 0)\n", - "2024-09-12 10:50:39,474 - numba.core.ssa - DEBUG - on stmt: $70binary_subscr.5 = static_getitem(value=idx, index=0, index_var=$const68.4, fn=)\n", - "2024-09-12 10:50:39,474 - numba.core.ssa - DEBUG - on stmt: $const74.7 = const(int, 1)\n", - "2024-09-12 10:50:39,475 - numba.core.ssa - DEBUG - on stmt: $76binary_subscr.8 = static_getitem(value=idx, index=1, index_var=$const74.7, fn=)\n", - "2024-09-12 10:50:39,475 - numba.core.ssa - DEBUG - on stmt: $const80.10 = const(int, 2)\n", - "2024-09-12 10:50:39,476 - numba.core.ssa - DEBUG - on stmt: $82binary_subscr.11 = static_getitem(value=idx, index=2, index_var=$const80.10, fn=)\n", - "2024-09-12 10:50:39,476 - numba.core.ssa - DEBUG - on stmt: $84call_function.12 = call $64load_global.2($70binary_subscr.5, $76binary_subscr.8, $82binary_subscr.11, func=$64load_global.2, args=[Var($70binary_subscr.5, indexing.py:541), Var($76binary_subscr.8, indexing.py:541), Var($82binary_subscr.11, indexing.py:541)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,477 - numba.core.ssa - DEBUG - on stmt: $86get_iter.13 = getiter(value=$84call_function.12)\n", - "2024-09-12 10:50:39,479 - numba.core.ssa - DEBUG - on stmt: $phi88.1 = $86get_iter.13\n", - "2024-09-12 10:50:39,479 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:39,480 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 88\n", - "2024-09-12 10:50:39,480 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,481 - numba.core.ssa - DEBUG - on stmt: $88for_iter.2 = iternext(value=$phi88.1)\n", - "2024-09-12 10:50:39,481 - numba.core.ssa - DEBUG - on stmt: $88for_iter.3 = pair_first(value=$88for_iter.2)\n", - "2024-09-12 10:50:39,482 - numba.core.ssa - DEBUG - on stmt: $88for_iter.4 = pair_second(value=$88for_iter.2)\n", - "2024-09-12 10:50:39,483 - numba.core.ssa - DEBUG - on stmt: $phi90.2 = $88for_iter.3\n", - "2024-09-12 10:50:39,484 - numba.core.ssa - DEBUG - on stmt: branch $88for_iter.4, 90, 214\n", - "2024-09-12 10:50:39,484 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 90\n", - "2024-09-12 10:50:39,485 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,485 - numba.core.ssa - DEBUG - on stmt: p_match = $phi90.2\n", - "2024-09-12 10:50:39,486 - numba.core.ssa - DEBUG - on stmt: $92load_global.3 = global(np: )\n", - "2024-09-12 10:50:39,486 - numba.core.ssa - DEBUG - on stmt: $94load_attr.4 = getattr(value=$92load_global.3, attr=searchsorted)\n", - "2024-09-12 10:50:39,487 - numba.core.ssa - DEBUG - on stmt: $102binary_subscr.8 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,487 - numba.core.ssa - DEBUG - on stmt: $108binary_subscr.11 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:39,488 - numba.core.ssa - DEBUG - on stmt: $110build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:39,488 - numba.core.ssa - DEBUG - on stmt: $110build_slice.13 = call $110build_slice.12($102binary_subscr.8, $108binary_subscr.11, func=$110build_slice.12, args=(Var($102binary_subscr.8, indexing.py:542), Var($108binary_subscr.11, indexing.py:542)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,489 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.14 = getitem(value=c, index=$110build_slice.13, fn=)\n", - "2024-09-12 10:50:39,490 - numba.core.ssa - DEBUG - on stmt: $const116.16 = const(str, left)\n", - "2024-09-12 10:50:39,492 - numba.core.ssa - DEBUG - on stmt: $120call_function_kw.18 = call $94load_attr.4($112binary_subscr.14, p_match, func=$94load_attr.4, args=[Var($112binary_subscr.14, indexing.py:542), Var(p_match, indexing.py:541)], kws=[('side', Var($const116.16, indexing.py:542))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,492 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.21 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,493 - numba.core.ssa - DEBUG - on stmt: start = $120call_function_kw.18 + $126binary_subscr.21\n", - "2024-09-12 10:50:39,493 - numba.core.ssa - DEBUG - on stmt: $132load_global.23 = global(np: )\n", - "2024-09-12 10:50:39,494 - numba.core.ssa - DEBUG - on stmt: $134load_attr.24 = getattr(value=$132load_global.23, attr=searchsorted)\n", - "2024-09-12 10:50:39,494 - numba.core.ssa - DEBUG - on stmt: $142binary_subscr.28 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,495 - numba.core.ssa - DEBUG - on stmt: $148binary_subscr.31 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:39,495 - numba.core.ssa - DEBUG - on stmt: $150build_slice.32 = global(slice: )\n", - "2024-09-12 10:50:39,496 - numba.core.ssa - DEBUG - on stmt: $150build_slice.33 = call $150build_slice.32($142binary_subscr.28, $148binary_subscr.31, func=$150build_slice.32, args=(Var($142binary_subscr.28, indexing.py:543), Var($148binary_subscr.31, indexing.py:543)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,497 - numba.core.ssa - DEBUG - on stmt: $152binary_subscr.34 = getitem(value=c, index=$150build_slice.33, fn=)\n", - "2024-09-12 10:50:39,498 - numba.core.ssa - DEBUG - on stmt: $const156.36 = const(str, right)\n", - "2024-09-12 10:50:39,499 - numba.core.ssa - DEBUG - on stmt: $160call_function_kw.38 = call $134load_attr.24($152binary_subscr.34, p_match, func=$134load_attr.24, args=[Var($152binary_subscr.34, indexing.py:543), Var(p_match, indexing.py:541)], kws=[('side', Var($const156.36, indexing.py:543))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,499 - numba.core.ssa - DEBUG - on stmt: $166binary_subscr.41 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,500 - numba.core.ssa - DEBUG - on stmt: stop = $160call_function_kw.38 + $166binary_subscr.41\n", - "2024-09-12 10:50:39,500 - numba.core.ssa - DEBUG - on stmt: $176compare_op.45 = start != stop\n", - "2024-09-12 10:50:39,501 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:39,501 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.45, func=bool178, args=(Var($176compare_op.45, indexing.py:545),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,502 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 212\n", - "2024-09-12 10:50:39,502 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:39,503 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,503 - numba.core.ssa - DEBUG - on stmt: $182load_method.3 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:39,505 - numba.core.ssa - DEBUG - on stmt: $186call_method.5 = call $182load_method.3(start, func=$182load_method.3, args=[Var(start, indexing.py:542)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,506 - numba.core.ssa - DEBUG - on stmt: $192load_method.7 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:39,506 - numba.core.ssa - DEBUG - on stmt: $196call_method.9 = call $192load_method.7(stop, func=$192load_method.7, args=[Var(stop, indexing.py:543)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,507 - numba.core.ssa - DEBUG - on stmt: $206binary_subtract.13 = stop - start\n", - "2024-09-12 10:50:39,507 - numba.core.ssa - DEBUG - on stmt: $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:39,508 - numba.core.ssa - DEBUG - on stmt: n_matches = $208inplace_add.14\n", - "2024-09-12 10:50:39,509 - numba.core.ssa - DEBUG - replaced with: n_matches.1 = $208inplace_add.14\n", - "2024-09-12 10:50:39,510 - numba.core.ssa - DEBUG - on stmt: jump 212\n", - "2024-09-12 10:50:39,510 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 212\n", - "2024-09-12 10:50:39,511 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,511 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:39,512 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 214\n", - "2024-09-12 10:50:39,512 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,513 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:39,513 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:39,515 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,515 - numba.core.ssa - DEBUG - on stmt: $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)])\n", - "2024-09-12 10:50:39,516 - numba.core.ssa - DEBUG - on stmt: $224return_value.4 = cast(value=$222build_tuple.3)\n", - "2024-09-12 10:50:39,516 - numba.core.ssa - DEBUG - on stmt: return $224return_value.4\n", - "2024-09-12 10:50:39,517 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 180: []})\n", - "2024-09-12 10:50:39,518 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:39,519 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,519 - numba.core.ssa - DEBUG - on stmt: starts_old = arg(0, name=starts_old)\n", - "2024-09-12 10:50:39,520 - numba.core.ssa - DEBUG - on stmt: stops_old = arg(1, name=stops_old)\n", - "2024-09-12 10:50:39,521 - numba.core.ssa - DEBUG - on stmt: c = arg(2, name=c)\n", - "2024-09-12 10:50:39,521 - numba.core.ssa - DEBUG - on stmt: idx = arg(3, name=idx)\n", - "2024-09-12 10:50:39,522 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:39,522 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:39,523 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:39,523 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:39,525 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:39,525 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:39,526 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:39,526 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:534)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,527 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(numba: )\n", - "2024-09-12 10:50:39,528 - numba.core.ssa - DEBUG - on stmt: $22load_attr.9 = getattr(value=$20load_global.8, attr=typed)\n", - "2024-09-12 10:50:39,528 - numba.core.ssa - DEBUG - on stmt: $24load_attr.10 = getattr(value=$22load_attr.9, attr=List)\n", - "2024-09-12 10:50:39,529 - numba.core.ssa - DEBUG - on stmt: $26load_method.11 = getattr(value=$24load_attr.10, attr=empty_list)\n", - "2024-09-12 10:50:39,529 - numba.core.ssa - DEBUG - on stmt: $28load_global.12 = global(numba: )\n", - "2024-09-12 10:50:39,530 - numba.core.ssa - DEBUG - on stmt: $30load_attr.13 = getattr(value=$28load_global.12, attr=types)\n", - "2024-09-12 10:50:39,530 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30load_attr.13, attr=intp)\n", - "2024-09-12 10:50:39,531 - numba.core.ssa - DEBUG - on stmt: stops = call $26load_method.11($32load_attr.14, func=$26load_method.11, args=[Var($32load_attr.14, indexing.py:535)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,531 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(np: )\n", - "2024-09-12 10:50:39,532 - numba.core.ssa - DEBUG - on stmt: $40load_method.17 = getattr(value=$38load_global.16, attr=intp)\n", - "2024-09-12 10:50:39,533 - numba.core.ssa - DEBUG - on stmt: $const42.18 = const(int, 0)\n", - "2024-09-12 10:50:39,535 - numba.core.ssa - DEBUG - on stmt: n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,535 - numba.core.ssa - DEBUG - on stmt: $48load_global.20 = global(range: )\n", - "2024-09-12 10:50:39,536 - numba.core.ssa - DEBUG - on stmt: $50load_global.21 = global(len: )\n", - "2024-09-12 10:50:39,537 - numba.core.ssa - DEBUG - on stmt: $54call_function.23 = call $50load_global.21(starts_old, func=$50load_global.21, args=[Var(starts_old, indexing.py:494)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,537 - numba.core.ssa - DEBUG - on stmt: $56call_function.24 = call $48load_global.20($54call_function.23, func=$48load_global.20, args=[Var($54call_function.23, indexing.py:538)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,538 - numba.core.ssa - DEBUG - on stmt: $58get_iter.25 = getiter(value=$56call_function.24)\n", - "2024-09-12 10:50:39,538 - numba.core.ssa - DEBUG - on stmt: $phi60.0 = $58get_iter.25\n", - "2024-09-12 10:50:39,539 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:39,540 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:39,540 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,541 - numba.core.ssa - DEBUG - on stmt: $60for_iter.1 = iternext(value=$phi60.0)\n", - "2024-09-12 10:50:39,541 - numba.core.ssa - DEBUG - on stmt: $60for_iter.2 = pair_first(value=$60for_iter.1)\n", - "2024-09-12 10:50:39,542 - numba.core.ssa - DEBUG - on stmt: $60for_iter.3 = pair_second(value=$60for_iter.1)\n", - "2024-09-12 10:50:39,543 - numba.core.ssa - DEBUG - on stmt: $phi62.1 = $60for_iter.2\n", - "2024-09-12 10:50:39,544 - numba.core.ssa - DEBUG - on stmt: branch $60for_iter.3, 62, 216\n", - "2024-09-12 10:50:39,544 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 62\n", - "2024-09-12 10:50:39,545 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,545 - numba.core.ssa - DEBUG - on stmt: j = $phi62.1\n", - "2024-09-12 10:50:39,546 - numba.core.ssa - DEBUG - on stmt: $64load_global.2 = global(range: )\n", - "2024-09-12 10:50:39,546 - numba.core.ssa - DEBUG - on stmt: $const68.4 = const(int, 0)\n", - "2024-09-12 10:50:39,547 - numba.core.ssa - DEBUG - on stmt: $70binary_subscr.5 = static_getitem(value=idx, index=0, index_var=$const68.4, fn=)\n", - "2024-09-12 10:50:39,548 - numba.core.ssa - DEBUG - on stmt: $const74.7 = const(int, 1)\n", - "2024-09-12 10:50:39,549 - numba.core.ssa - DEBUG - on stmt: $76binary_subscr.8 = static_getitem(value=idx, index=1, index_var=$const74.7, fn=)\n", - "2024-09-12 10:50:39,550 - numba.core.ssa - DEBUG - on stmt: $const80.10 = const(int, 2)\n", - "2024-09-12 10:50:39,550 - numba.core.ssa - DEBUG - on stmt: $82binary_subscr.11 = static_getitem(value=idx, index=2, index_var=$const80.10, fn=)\n", - "2024-09-12 10:50:39,551 - numba.core.ssa - DEBUG - on stmt: $84call_function.12 = call $64load_global.2($70binary_subscr.5, $76binary_subscr.8, $82binary_subscr.11, func=$64load_global.2, args=[Var($70binary_subscr.5, indexing.py:541), Var($76binary_subscr.8, indexing.py:541), Var($82binary_subscr.11, indexing.py:541)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,552 - numba.core.ssa - DEBUG - on stmt: $86get_iter.13 = getiter(value=$84call_function.12)\n", - "2024-09-12 10:50:39,553 - numba.core.ssa - DEBUG - on stmt: $phi88.1 = $86get_iter.13\n", - "2024-09-12 10:50:39,553 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:39,554 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 88\n", - "2024-09-12 10:50:39,554 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,555 - numba.core.ssa - DEBUG - on stmt: $88for_iter.2 = iternext(value=$phi88.1)\n", - "2024-09-12 10:50:39,556 - numba.core.ssa - DEBUG - on stmt: $88for_iter.3 = pair_first(value=$88for_iter.2)\n", - "2024-09-12 10:50:39,556 - numba.core.ssa - DEBUG - on stmt: $88for_iter.4 = pair_second(value=$88for_iter.2)\n", - "2024-09-12 10:50:39,557 - numba.core.ssa - DEBUG - on stmt: $phi90.2 = $88for_iter.3\n", - "2024-09-12 10:50:39,558 - numba.core.ssa - DEBUG - on stmt: branch $88for_iter.4, 90, 214\n", - "2024-09-12 10:50:39,558 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 90\n", - "2024-09-12 10:50:39,559 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,559 - numba.core.ssa - DEBUG - on stmt: p_match = $phi90.2\n", - "2024-09-12 10:50:39,560 - numba.core.ssa - DEBUG - on stmt: $92load_global.3 = global(np: )\n", - "2024-09-12 10:50:39,560 - numba.core.ssa - DEBUG - on stmt: $94load_attr.4 = getattr(value=$92load_global.3, attr=searchsorted)\n", - "2024-09-12 10:50:39,561 - numba.core.ssa - DEBUG - on stmt: $102binary_subscr.8 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,562 - numba.core.ssa - DEBUG - on stmt: $108binary_subscr.11 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:39,562 - numba.core.ssa - DEBUG - on stmt: $110build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:39,563 - numba.core.ssa - DEBUG - on stmt: $110build_slice.13 = call $110build_slice.12($102binary_subscr.8, $108binary_subscr.11, func=$110build_slice.12, args=(Var($102binary_subscr.8, indexing.py:542), Var($108binary_subscr.11, indexing.py:542)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,563 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.14 = getitem(value=c, index=$110build_slice.13, fn=)\n", - "2024-09-12 10:50:39,564 - numba.core.ssa - DEBUG - on stmt: $const116.16 = const(str, left)\n", - "2024-09-12 10:50:39,566 - numba.core.ssa - DEBUG - on stmt: $120call_function_kw.18 = call $94load_attr.4($112binary_subscr.14, p_match, func=$94load_attr.4, args=[Var($112binary_subscr.14, indexing.py:542), Var(p_match, indexing.py:541)], kws=[('side', Var($const116.16, indexing.py:542))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,566 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.21 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,567 - numba.core.ssa - DEBUG - on stmt: start = $120call_function_kw.18 + $126binary_subscr.21\n", - "2024-09-12 10:50:39,567 - numba.core.ssa - DEBUG - on stmt: $132load_global.23 = global(np: )\n", - "2024-09-12 10:50:39,568 - numba.core.ssa - DEBUG - on stmt: $134load_attr.24 = getattr(value=$132load_global.23, attr=searchsorted)\n", - "2024-09-12 10:50:39,568 - numba.core.ssa - DEBUG - on stmt: $142binary_subscr.28 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,569 - numba.core.ssa - DEBUG - on stmt: $148binary_subscr.31 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:39,569 - numba.core.ssa - DEBUG - on stmt: $150build_slice.32 = global(slice: )\n", - "2024-09-12 10:50:39,571 - numba.core.ssa - DEBUG - on stmt: $150build_slice.33 = call $150build_slice.32($142binary_subscr.28, $148binary_subscr.31, func=$150build_slice.32, args=(Var($142binary_subscr.28, indexing.py:543), Var($148binary_subscr.31, indexing.py:543)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,572 - numba.core.ssa - DEBUG - on stmt: $152binary_subscr.34 = getitem(value=c, index=$150build_slice.33, fn=)\n", - "2024-09-12 10:50:39,573 - numba.core.ssa - DEBUG - on stmt: $const156.36 = const(str, right)\n", - "2024-09-12 10:50:39,575 - numba.core.ssa - DEBUG - on stmt: $160call_function_kw.38 = call $134load_attr.24($152binary_subscr.34, p_match, func=$134load_attr.24, args=[Var($152binary_subscr.34, indexing.py:543), Var(p_match, indexing.py:541)], kws=[('side', Var($const156.36, indexing.py:543))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,575 - numba.core.ssa - DEBUG - on stmt: $166binary_subscr.41 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:39,576 - numba.core.ssa - DEBUG - on stmt: stop = $160call_function_kw.38 + $166binary_subscr.41\n", - "2024-09-12 10:50:39,576 - numba.core.ssa - DEBUG - on stmt: $176compare_op.45 = start != stop\n", - "2024-09-12 10:50:39,577 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:39,577 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.45, func=bool178, args=(Var($176compare_op.45, indexing.py:545),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,579 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 212\n", - "2024-09-12 10:50:39,579 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:39,580 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,580 - numba.core.ssa - DEBUG - on stmt: $182load_method.3 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:39,581 - numba.core.ssa - DEBUG - on stmt: $186call_method.5 = call $182load_method.3(start, func=$182load_method.3, args=[Var(start, indexing.py:542)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,582 - numba.core.ssa - DEBUG - on stmt: $192load_method.7 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:39,583 - numba.core.ssa - DEBUG - on stmt: $196call_method.9 = call $192load_method.7(stop, func=$192load_method.7, args=[Var(stop, indexing.py:543)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,583 - numba.core.ssa - DEBUG - on stmt: $206binary_subtract.13 = stop - start\n", - "2024-09-12 10:50:39,584 - numba.core.ssa - DEBUG - on stmt: $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:39,584 - numba.core.ssa - DEBUG - find_def var='n_matches' stmt=$208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:39,585 - numba.core.ssa - DEBUG - find_def_from_top label 180\n", - "2024-09-12 10:50:39,586 - numba.core.ssa - DEBUG - idom 90 from label 180\n", - "2024-09-12 10:50:39,587 - numba.core.ssa - DEBUG - find_def_from_bottom label 90\n", - "2024-09-12 10:50:39,587 - numba.core.ssa - DEBUG - find_def_from_top label 90\n", - "2024-09-12 10:50:39,588 - numba.core.ssa - DEBUG - idom 88 from label 90\n", - "2024-09-12 10:50:39,589 - numba.core.ssa - DEBUG - find_def_from_bottom label 88\n", - "2024-09-12 10:50:39,589 - numba.core.ssa - DEBUG - find_def_from_top label 88\n", - "2024-09-12 10:50:39,590 - numba.core.ssa - DEBUG - insert phi node n_matches.2 = phi(incoming_values=[], incoming_blocks=[]) at 88\n", - "2024-09-12 10:50:39,591 - numba.core.ssa - DEBUG - find_def_from_bottom label 212\n", - "2024-09-12 10:50:39,591 - numba.core.ssa - DEBUG - find_def_from_top label 212\n", - "2024-09-12 10:50:39,592 - numba.core.ssa - DEBUG - insert phi node n_matches.3 = phi(incoming_values=[], incoming_blocks=[]) at 212\n", - "2024-09-12 10:50:39,592 - numba.core.ssa - DEBUG - find_def_from_bottom label 90\n", - "2024-09-12 10:50:39,593 - numba.core.ssa - DEBUG - find_def_from_top label 90\n", - "2024-09-12 10:50:39,593 - numba.core.ssa - DEBUG - idom 88 from label 90\n", - "2024-09-12 10:50:39,594 - numba.core.ssa - DEBUG - find_def_from_bottom label 88\n", - "2024-09-12 10:50:39,595 - numba.core.ssa - DEBUG - incoming_def n_matches.2 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-09-12 10:50:39,596 - numba.core.ssa - DEBUG - find_def_from_bottom label 180\n", - "2024-09-12 10:50:39,596 - numba.core.ssa - DEBUG - incoming_def n_matches.1 = $208inplace_add.14\n", - "2024-09-12 10:50:39,597 - numba.core.ssa - DEBUG - incoming_def n_matches.3 = phi(incoming_values=[Var(n_matches.2, indexing.py:546), Var(n_matches.1, indexing.py:548)], incoming_blocks=[90, 180])\n", - "2024-09-12 10:50:39,597 - numba.core.ssa - DEBUG - find_def_from_bottom label 62\n", - "2024-09-12 10:50:39,598 - numba.core.ssa - DEBUG - find_def_from_top label 62\n", - "2024-09-12 10:50:39,598 - numba.core.ssa - DEBUG - idom 60 from label 62\n", - "2024-09-12 10:50:39,600 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:39,600 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:39,601 - numba.core.ssa - DEBUG - insert phi node n_matches.4 = phi(incoming_values=[], incoming_blocks=[]) at 60\n", - "2024-09-12 10:50:39,601 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:39,602 - numba.core.ssa - DEBUG - incoming_def n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,602 - numba.core.ssa - DEBUG - find_def_from_bottom label 214\n", - "2024-09-12 10:50:39,603 - numba.core.ssa - DEBUG - find_def_from_top label 214\n", - "2024-09-12 10:50:39,604 - numba.core.ssa - DEBUG - idom 88 from label 214\n", - "2024-09-12 10:50:39,605 - numba.core.ssa - DEBUG - find_def_from_bottom label 88\n", - "2024-09-12 10:50:39,605 - numba.core.ssa - DEBUG - incoming_def n_matches.2 = phi(incoming_values=[Var(n_matches.3, indexing.py:546)], incoming_blocks=[212])\n", - "2024-09-12 10:50:39,606 - numba.core.ssa - DEBUG - incoming_def n_matches.4 = phi(incoming_values=[Var(n_matches, indexing.py:536), Var(n_matches.2, indexing.py:546)], incoming_blocks=[0, 214])\n", - "2024-09-12 10:50:39,606 - numba.core.ssa - DEBUG - replaced with: $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches.2, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:39,607 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $208inplace_add.14\n", - "2024-09-12 10:50:39,608 - numba.core.ssa - DEBUG - on stmt: jump 212\n", - "2024-09-12 10:50:39,608 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 212\n", - "2024-09-12 10:50:39,609 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,609 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:39,610 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 214\n", - "2024-09-12 10:50:39,610 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,611 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:39,611 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:39,612 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,614 - numba.core.ssa - DEBUG - on stmt: $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)])\n", - "2024-09-12 10:50:39,614 - numba.core.ssa - DEBUG - find_def var='n_matches' stmt=$222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)])\n", - "2024-09-12 10:50:39,615 - numba.core.ssa - DEBUG - find_def_from_top label 216\n", - "2024-09-12 10:50:39,616 - numba.core.ssa - DEBUG - idom 60 from label 216\n", - "2024-09-12 10:50:39,617 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:39,617 - numba.core.ssa - DEBUG - replaced with: $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches.4, indexing.py:546)])\n", - "2024-09-12 10:50:39,618 - numba.core.ssa - DEBUG - on stmt: $224return_value.4 = cast(value=$222build_tuple.3)\n", - "2024-09-12 10:50:39,618 - numba.core.ssa - DEBUG - on stmt: return $224return_value.4\n", - "2024-09-12 10:50:39,651 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=766)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=767)\n", - " 4\tLOAD_FAST(arg=1, lineno=767)\n", - " 6\tLOAD_DEREF(arg=0, lineno=767)\n", - " 8\tCALL_FUNCTION(arg=2, lineno=767)\n", - " 10\tSTORE_FAST(arg=2, lineno=767)\n", - " 12\tLOAD_GLOBAL(arg=1, lineno=768)\n", - " 14\tLOAD_FAST(arg=0, lineno=768)\n", - " 16\tLOAD_FAST(arg=2, lineno=768)\n", - " 18\tCALL_FUNCTION(arg=2, lineno=768)\n", - " 20\tSTORE_FAST(arg=3, lineno=768)\n", - " 22\tLOAD_GLOBAL(arg=2, lineno=769)\n", - " 24\tLOAD_FAST(arg=0, lineno=769)\n", - " 26\tLOAD_FAST(arg=3, lineno=769)\n", - " 28\tCALL_FUNCTION(arg=2, lineno=769)\n", - " 30\tUNPACK_SEQUENCE(arg=2, lineno=769)\n", - " 32\tSTORE_FAST(arg=4, lineno=769)\n", - " 34\tSTORE_FAST(arg=5, lineno=769)\n", - " 36\tLOAD_FAST(arg=4, lineno=770)\n", - " 38\tLOAD_GLOBAL(arg=3, lineno=770)\n", - " 40\tLOAD_ATTR(arg=4, lineno=770)\n", - " 42\tCOMPARE_OP(arg=2, lineno=770)\n", - " 44\tPOP_JUMP_IF_FALSE(arg=28, lineno=770)\n", - " 46\tLOAD_GLOBAL(arg=5, lineno=771)\n", - " 48\tLOAD_FAST(arg=5, lineno=771)\n", - " 50\tCALL_FUNCTION(arg=1, lineno=771)\n", - " 52\tRETURN_VALUE(arg=None, lineno=771)\n", - "> 54\tLOAD_GLOBAL(arg=6, lineno=773)\n", - " 56\tLOAD_CONST(arg=1, lineno=773)\n", - " 58\tCALL_FUNCTION(arg=1, lineno=773)\n", - " 60\tRAISE_VARARGS(arg=1, lineno=773)\n", - "2024-09-12 10:50:39,652 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:39,653 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,654 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:39,654 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=766)\n", - "2024-09-12 10:50:39,655 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,656 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=767)\n", - "2024-09-12 10:50:39,656 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,657 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=1, lineno=767)\n", - "2024-09-12 10:50:39,658 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:39,658 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_DEREF(arg=0, lineno=767)\n", - "2024-09-12 10:50:39,659 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$index4.1']\n", - "2024-09-12 10:50:39,660 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_FUNCTION(arg=2, lineno=767)\n", - "2024-09-12 10:50:39,660 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$index4.1', '$6load_deref.2']\n", - "2024-09-12 10:50:39,661 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=STORE_FAST(arg=2, lineno=767)\n", - "2024-09-12 10:50:39,661 - numba.core.byteflow - DEBUG - stack ['$8call_function.3']\n", - "2024-09-12 10:50:39,662 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_GLOBAL(arg=1, lineno=768)\n", - "2024-09-12 10:50:39,663 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,663 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=0, lineno=768)\n", - "2024-09-12 10:50:39,664 - numba.core.byteflow - DEBUG - stack ['$12load_global.4']\n", - "2024-09-12 10:50:39,665 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=2, lineno=768)\n", - "2024-09-12 10:50:39,665 - numba.core.byteflow - DEBUG - stack ['$12load_global.4', '$l14.5']\n", - "2024-09-12 10:50:39,666 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=CALL_FUNCTION(arg=2, lineno=768)\n", - "2024-09-12 10:50:39,667 - numba.core.byteflow - DEBUG - stack ['$12load_global.4', '$l14.5', '$castedindex16.6']\n", - "2024-09-12 10:50:39,667 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=STORE_FAST(arg=3, lineno=768)\n", - "2024-09-12 10:50:39,668 - numba.core.byteflow - DEBUG - stack ['$18call_function.7']\n", - "2024-09-12 10:50:39,673 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_GLOBAL(arg=2, lineno=769)\n", - "2024-09-12 10:50:39,674 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,675 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_FAST(arg=0, lineno=769)\n", - "2024-09-12 10:50:39,675 - numba.core.byteflow - DEBUG - stack ['$22load_global.8']\n", - "2024-09-12 10:50:39,676 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_FAST(arg=3, lineno=769)\n", - "2024-09-12 10:50:39,677 - numba.core.byteflow - DEBUG - stack ['$22load_global.8', '$l24.9']\n", - "2024-09-12 10:50:39,677 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=CALL_FUNCTION(arg=2, lineno=769)\n", - "2024-09-12 10:50:39,678 - numba.core.byteflow - DEBUG - stack ['$22load_global.8', '$l24.9', '$handledindex26.10']\n", - "2024-09-12 10:50:39,678 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=UNPACK_SEQUENCE(arg=2, lineno=769)\n", - "2024-09-12 10:50:39,679 - numba.core.byteflow - DEBUG - stack ['$28call_function.11']\n", - "2024-09-12 10:50:39,680 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=STORE_FAST(arg=4, lineno=769)\n", - "2024-09-12 10:50:39,680 - numba.core.byteflow - DEBUG - stack ['$30unpack_sequence.13', '$30unpack_sequence.12']\n", - "2024-09-12 10:50:39,681 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=STORE_FAST(arg=5, lineno=769)\n", - "2024-09-12 10:50:39,684 - numba.core.byteflow - DEBUG - stack ['$30unpack_sequence.13']\n", - "2024-09-12 10:50:39,685 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_FAST(arg=4, lineno=770)\n", - "2024-09-12 10:50:39,686 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,686 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_GLOBAL(arg=3, lineno=770)\n", - "2024-09-12 10:50:39,687 - numba.core.byteflow - DEBUG - stack ['$status36.15']\n", - "2024-09-12 10:50:39,687 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_ATTR(arg=4, lineno=770)\n", - "2024-09-12 10:50:39,688 - numba.core.byteflow - DEBUG - stack ['$status36.15', '$38load_global.16']\n", - "2024-09-12 10:50:39,689 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=COMPARE_OP(arg=2, lineno=770)\n", - "2024-09-12 10:50:39,689 - numba.core.byteflow - DEBUG - stack ['$status36.15', '$40load_attr.17']\n", - "2024-09-12 10:50:39,690 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_FALSE(arg=28, lineno=770)\n", - "2024-09-12 10:50:39,690 - numba.core.byteflow - DEBUG - stack ['$42compare_op.18']\n", - "2024-09-12 10:50:39,691 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=(), blockstack=(), npush=0), Edge(pc=54, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,692 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=0), State(pc_initial=54 nstack_initial=0)])\n", - "2024-09-12 10:50:39,692 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,693 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=0)\n", - "2024-09-12 10:50:39,694 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_GLOBAL(arg=5, lineno=771)\n", - "2024-09-12 10:50:39,694 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,695 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_FAST(arg=5, lineno=771)\n", - "2024-09-12 10:50:39,696 - numba.core.byteflow - DEBUG - stack ['$46load_global.0']\n", - "2024-09-12 10:50:39,696 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=CALL_FUNCTION(arg=1, lineno=771)\n", - "2024-09-12 10:50:39,697 - numba.core.byteflow - DEBUG - stack ['$46load_global.0', '$item48.1']\n", - "2024-09-12 10:50:39,697 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=RETURN_VALUE(arg=None, lineno=771)\n", - "2024-09-12 10:50:39,698 - numba.core.byteflow - DEBUG - stack ['$50call_function.2']\n", - "2024-09-12 10:50:39,699 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:39,699 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=0)])\n", - "2024-09-12 10:50:39,700 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,700 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=0)\n", - "2024-09-12 10:50:39,701 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=LOAD_GLOBAL(arg=6, lineno=773)\n", - "2024-09-12 10:50:39,702 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,702 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_CONST(arg=1, lineno=773)\n", - "2024-09-12 10:50:39,703 - numba.core.byteflow - DEBUG - stack ['$54load_global.0']\n", - "2024-09-12 10:50:39,703 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=CALL_FUNCTION(arg=1, lineno=773)\n", - "2024-09-12 10:50:39,704 - numba.core.byteflow - DEBUG - stack ['$54load_global.0', '$const56.1']\n", - "2024-09-12 10:50:39,705 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=RAISE_VARARGS(arg=1, lineno=773)\n", - "2024-09-12 10:50:39,705 - numba.core.byteflow - DEBUG - stack ['$58call_function.2']\n", - "2024-09-12 10:50:39,713 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:39,714 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:39,714 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=46 nstack_initial=0): set(),\n", - " State(pc_initial=54 nstack_initial=0): set()})\n", - "2024-09-12 10:50:39,716 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:39,716 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:39,717 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:39,718 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:39,718 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:39,719 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:39,719 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$index4.1'}), (6, {'res': '$6load_deref.2'}), (8, {'func': '$2load_global.0', 'args': ['$index4.1', '$6load_deref.2'], 'res': '$8call_function.3'}), (10, {'value': '$8call_function.3'}), (12, {'res': '$12load_global.4'}), (14, {'res': '$l14.5'}), (16, {'res': '$castedindex16.6'}), (18, {'func': '$12load_global.4', 'args': ['$l14.5', '$castedindex16.6'], 'res': '$18call_function.7'}), (20, {'value': '$18call_function.7'}), (22, {'res': '$22load_global.8'}), (24, {'res': '$l24.9'}), (26, {'res': '$handledindex26.10'}), (28, {'func': '$22load_global.8', 'args': ['$l24.9', '$handledindex26.10'], 'res': '$28call_function.11'}), (30, {'iterable': '$28call_function.11', 'stores': ['$30unpack_sequence.12', '$30unpack_sequence.13'], 'tupleobj': '$30unpack_sequence.14'}), (32, {'value': '$30unpack_sequence.12'}), (34, {'value': '$30unpack_sequence.13'}), (36, {'res': '$status36.15'}), (38, {'res': '$38load_global.16'}), (40, {'item': '$38load_global.16', 'res': '$40load_attr.17'}), (42, {'lhs': '$status36.15', 'rhs': '$40load_attr.17', 'res': '$42compare_op.18'}), (44, {'pred': '$42compare_op.18'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: (), 54: ()})\n", - "2024-09-12 10:50:39,720 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((46, {'res': '$46load_global.0'}), (48, {'res': '$item48.1'}), (50, {'func': '$46load_global.0', 'args': ['$item48.1'], 'res': '$50call_function.2'}), (52, {'retval': '$50call_function.2', 'castval': '$52return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:39,721 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((54, {'res': '$54load_global.0'}), (56, {'res': '$const56.1'}), (58, {'func': '$54load_global.0', 'args': ['$const56.1'], 'res': '$58call_function.2'}), (60, {'exc': '$58call_function.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:39,724 - numba.core.interpreter - DEBUG - label 0:\n", - " l = arg(0, name=l) ['l']\n", - " index = arg(1, name=index) ['index']\n", - " $2load_global.0 = global(_cast: ) ['$2load_global.0']\n", - " $6load_deref.2 = freevar(indexty: int64) ['$6load_deref.2']\n", - " castedindex = call $2load_global.0(index, $6load_deref.2, func=$2load_global.0, args=[Var(index, listobject.py:766), Var($6load_deref.2, listobject.py:767)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', '$6load_deref.2', 'castedindex', 'index']\n", - " $12load_global.4 = global(handle_index: ) ['$12load_global.4']\n", - " handledindex = call $12load_global.4(l, castedindex, func=$12load_global.4, args=[Var(l, listobject.py:766), Var(castedindex, listobject.py:767)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_global.4', 'castedindex', 'handledindex', 'l']\n", - " $22load_global.8 = global(_list_getitem: ) ['$22load_global.8']\n", - " $28call_function.11 = call $22load_global.8(l, handledindex, func=$22load_global.8, args=[Var(l, listobject.py:766), Var(handledindex, listobject.py:768)], kws=(), vararg=None, varkwarg=None, target=None) ['$22load_global.8', '$28call_function.11', 'handledindex', 'l']\n", - " $30unpack_sequence.14 = exhaust_iter(value=$28call_function.11, count=2) ['$28call_function.11', '$30unpack_sequence.14']\n", - " $30unpack_sequence.12 = static_getitem(value=$30unpack_sequence.14, index=0, index_var=None, fn=) ['$30unpack_sequence.12', '$30unpack_sequence.14']\n", - " $30unpack_sequence.13 = static_getitem(value=$30unpack_sequence.14, index=1, index_var=None, fn=) ['$30unpack_sequence.13', '$30unpack_sequence.14']\n", - " status = $30unpack_sequence.12 ['$30unpack_sequence.12', 'status']\n", - " item = $30unpack_sequence.13 ['$30unpack_sequence.13', 'item']\n", - " $38load_global.16 = global(ListStatus: ) ['$38load_global.16']\n", - " $40load_attr.17 = getattr(value=$38load_global.16, attr=LIST_OK) ['$38load_global.16', '$40load_attr.17']\n", - " $42compare_op.18 = status == $40load_attr.17 ['$40load_attr.17', '$42compare_op.18', 'status']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42compare_op.18, func=bool44, args=(Var($42compare_op.18, listobject.py:770),), kws=(), vararg=None, varkwarg=None, target=None) ['$42compare_op.18', '$44pred', 'bool44']\n", - " branch $44pred, 46, 54 ['$44pred']\n", - "label 46:\n", - " $46load_global.0 = global(_nonoptional: ) ['$46load_global.0']\n", - " $50call_function.2 = call $46load_global.0(item, func=$46load_global.0, args=[Var(item, listobject.py:769)], kws=(), vararg=None, varkwarg=None, target=None) ['$46load_global.0', '$50call_function.2', 'item']\n", - " $52return_value.3 = cast(value=$50call_function.2) ['$50call_function.2', '$52return_value.3']\n", - " return $52return_value.3 ['$52return_value.3']\n", - "label 54:\n", - " $54load_global.0 = global(AssertionError: ) ['$54load_global.0']\n", - " $const56.1 = const(str, internal list error during getitem) ['$const56.1']\n", - " $58call_function.2 = call $54load_global.0($const56.1, func=$54load_global.0, args=[Var($const56.1, listobject.py:773)], kws=(), vararg=None, varkwarg=None, target=None) ['$54load_global.0', '$58call_function.2', '$const56.1']\n", - " raise $58call_function.2 ['$58call_function.2']\n", - "\n", - "2024-09-12 10:50:39,744 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:39,745 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,746 - numba.core.ssa - DEBUG - on stmt: l = arg(0, name=l)\n", - "2024-09-12 10:50:39,746 - numba.core.ssa - DEBUG - on stmt: index = arg(1, name=index)\n", - "2024-09-12 10:50:39,747 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(_cast: )\n", - "2024-09-12 10:50:39,748 - numba.core.ssa - DEBUG - on stmt: $6load_deref.2 = freevar(indexty: int64)\n", - "2024-09-12 10:50:39,748 - numba.core.ssa - DEBUG - on stmt: castedindex = call $2load_global.0(index, $6load_deref.2, func=$2load_global.0, args=[Var(index, listobject.py:766), Var($6load_deref.2, listobject.py:767)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,749 - numba.core.ssa - DEBUG - on stmt: $12load_global.4 = global(handle_index: )\n", - "2024-09-12 10:50:39,750 - numba.core.ssa - DEBUG - on stmt: handledindex = call $12load_global.4(l, castedindex, func=$12load_global.4, args=[Var(l, listobject.py:766), Var(castedindex, listobject.py:767)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,751 - numba.core.ssa - DEBUG - on stmt: $22load_global.8 = global(_list_getitem: )\n", - "2024-09-12 10:50:39,751 - numba.core.ssa - DEBUG - on stmt: $28call_function.11 = call $22load_global.8(l, handledindex, func=$22load_global.8, args=[Var(l, listobject.py:766), Var(handledindex, listobject.py:768)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,752 - numba.core.ssa - DEBUG - on stmt: $30unpack_sequence.14 = exhaust_iter(value=$28call_function.11, count=2)\n", - "2024-09-12 10:50:39,753 - numba.core.ssa - DEBUG - on stmt: $30unpack_sequence.12 = static_getitem(value=$30unpack_sequence.14, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:39,753 - numba.core.ssa - DEBUG - on stmt: $30unpack_sequence.13 = static_getitem(value=$30unpack_sequence.14, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:39,754 - numba.core.ssa - DEBUG - on stmt: status = $30unpack_sequence.12\n", - "2024-09-12 10:50:39,755 - numba.core.ssa - DEBUG - on stmt: item = $30unpack_sequence.13\n", - "2024-09-12 10:50:39,755 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(ListStatus: )\n", - "2024-09-12 10:50:39,756 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=LIST_OK)\n", - "2024-09-12 10:50:39,757 - numba.core.ssa - DEBUG - on stmt: $42compare_op.18 = status == $40load_attr.17\n", - "2024-09-12 10:50:39,757 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:39,758 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42compare_op.18, func=bool44, args=(Var($42compare_op.18, listobject.py:770),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,759 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 46, 54\n", - "2024-09-12 10:50:39,759 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-09-12 10:50:39,760 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,761 - numba.core.ssa - DEBUG - on stmt: $46load_global.0 = global(_nonoptional: )\n", - "2024-09-12 10:50:39,761 - numba.core.ssa - DEBUG - on stmt: $50call_function.2 = call $46load_global.0(item, func=$46load_global.0, args=[Var(item, listobject.py:769)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,762 - numba.core.ssa - DEBUG - on stmt: $52return_value.3 = cast(value=$50call_function.2)\n", - "2024-09-12 10:50:39,763 - numba.core.ssa - DEBUG - on stmt: return $52return_value.3\n", - "2024-09-12 10:50:39,763 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-09-12 10:50:39,764 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,765 - numba.core.ssa - DEBUG - on stmt: $54load_global.0 = global(AssertionError: )\n", - "2024-09-12 10:50:39,765 - numba.core.ssa - DEBUG - on stmt: $const56.1 = const(str, internal list error during getitem)\n", - "2024-09-12 10:50:39,766 - numba.core.ssa - DEBUG - on stmt: $58call_function.2 = call $54load_global.0($const56.1, func=$54load_global.0, args=[Var($const56.1, listobject.py:773)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,767 - numba.core.ssa - DEBUG - on stmt: raise ('internal list error during getitem')\n", - "2024-09-12 10:50:39,768 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12load_global.4': [],\n", - " '$22load_global.8': [],\n", - " '$28call_function.11': [],\n", - " '$2load_global.0': [],\n", - " '$30unpack_sequence.12': [],\n", - " '$30unpack_sequence.13': [],\n", - " '$30unpack_sequence.14': [],\n", - " '$38load_global.16': [],\n", - " '$40load_attr.17': [],\n", - " '$42compare_op.18': [],\n", - " '$44pred': [],\n", - " '$46load_global.0': [],\n", - " '$50call_function.2': [],\n", - " '$52return_value.3': [],\n", - " '$54load_global.0': [],\n", - " '$58call_function.2': [],\n", - " '$6load_deref.2': [],\n", - " '$const56.1': [],\n", - " 'bool44': [],\n", - " 'castedindex': [],\n", - " 'handledindex': [],\n", - " 'index': [],\n", - " 'item': [],\n", - " 'l': [],\n", - " 'status': []})\n", - "2024-09-12 10:50:39,769 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:39,778 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=651)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=659)\n", - " 4\tLOAD_FAST(arg=0, lineno=659)\n", - " 6\tLOAD_FAST(arg=1, lineno=659)\n", - " 8\tCALL_FUNCTION(arg=2, lineno=659)\n", - " 10\tSTORE_FAST(arg=1, lineno=659)\n", - " 12\tLOAD_FAST(arg=1, lineno=661)\n", - " 14\tLOAD_CONST(arg=1, lineno=661)\n", - " 16\tCOMPARE_OP(arg=0, lineno=661)\n", - " 18\tPOP_JUMP_IF_TRUE(arg=17, lineno=661)\n", - " 20\tLOAD_FAST(arg=1, lineno=661)\n", - " 22\tLOAD_GLOBAL(arg=1, lineno=661)\n", - " 24\tLOAD_FAST(arg=0, lineno=661)\n", - " 26\tCALL_FUNCTION(arg=1, lineno=661)\n", - " 28\tCOMPARE_OP(arg=5, lineno=661)\n", - " 30\tPOP_JUMP_IF_FALSE(arg=21, lineno=661)\n", - "> 32\tLOAD_GLOBAL(arg=2, lineno=662)\n", - " 34\tLOAD_CONST(arg=2, lineno=662)\n", - " 36\tCALL_FUNCTION(arg=1, lineno=662)\n", - " 38\tRAISE_VARARGS(arg=1, lineno=662)\n", - "> 40\tLOAD_FAST(arg=1, lineno=663)\n", - " 42\tRETURN_VALUE(arg=None, lineno=663)\n", - "2024-09-12 10:50:39,779 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:39,780 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,780 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:39,781 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=651)\n", - "2024-09-12 10:50:39,782 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,782 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=659)\n", - "2024-09-12 10:50:39,783 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,784 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=659)\n", - "2024-09-12 10:50:39,785 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:39,785 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=659)\n", - "2024-09-12 10:50:39,786 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$l4.1']\n", - "2024-09-12 10:50:39,787 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_FUNCTION(arg=2, lineno=659)\n", - "2024-09-12 10:50:39,788 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$l4.1', '$index6.2']\n", - "2024-09-12 10:50:39,788 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=STORE_FAST(arg=1, lineno=659)\n", - "2024-09-12 10:50:39,789 - numba.core.byteflow - DEBUG - stack ['$8call_function.3']\n", - "2024-09-12 10:50:39,790 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=1, lineno=661)\n", - "2024-09-12 10:50:39,790 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,791 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_CONST(arg=1, lineno=661)\n", - "2024-09-12 10:50:39,792 - numba.core.byteflow - DEBUG - stack ['$index12.4']\n", - "2024-09-12 10:50:39,792 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=COMPARE_OP(arg=0, lineno=661)\n", - "2024-09-12 10:50:39,793 - numba.core.byteflow - DEBUG - stack ['$index12.4', '$const14.5']\n", - "2024-09-12 10:50:39,794 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=POP_JUMP_IF_TRUE(arg=17, lineno=661)\n", - "2024-09-12 10:50:39,794 - numba.core.byteflow - DEBUG - stack ['$16compare_op.6']\n", - "2024-09-12 10:50:39,795 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=20, stack=(), blockstack=(), npush=0), Edge(pc=32, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,796 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=20 nstack_initial=0), State(pc_initial=32 nstack_initial=0)])\n", - "2024-09-12 10:50:39,797 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,797 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=20 nstack_initial=0)\n", - "2024-09-12 10:50:39,798 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=1, lineno=661)\n", - "2024-09-12 10:50:39,799 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,799 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_GLOBAL(arg=1, lineno=661)\n", - "2024-09-12 10:50:39,800 - numba.core.byteflow - DEBUG - stack ['$index20.0']\n", - "2024-09-12 10:50:39,801 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_FAST(arg=0, lineno=661)\n", - "2024-09-12 10:50:39,801 - numba.core.byteflow - DEBUG - stack ['$index20.0', '$22load_global.1']\n", - "2024-09-12 10:50:39,802 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=CALL_FUNCTION(arg=1, lineno=661)\n", - "2024-09-12 10:50:39,803 - numba.core.byteflow - DEBUG - stack ['$index20.0', '$22load_global.1', '$l24.2']\n", - "2024-09-12 10:50:39,803 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=COMPARE_OP(arg=5, lineno=661)\n", - "2024-09-12 10:50:39,804 - numba.core.byteflow - DEBUG - stack ['$index20.0', '$26call_function.3']\n", - "2024-09-12 10:50:39,805 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=POP_JUMP_IF_FALSE(arg=21, lineno=661)\n", - "2024-09-12 10:50:39,806 - numba.core.byteflow - DEBUG - stack ['$28compare_op.4']\n", - "2024-09-12 10:50:39,806 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=32, stack=(), blockstack=(), npush=0), Edge(pc=40, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:39,807 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=0), State(pc_initial=32 nstack_initial=0), State(pc_initial=40 nstack_initial=0)])\n", - "2024-09-12 10:50:39,808 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,809 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=32 nstack_initial=0)\n", - "2024-09-12 10:50:39,809 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_GLOBAL(arg=2, lineno=662)\n", - "2024-09-12 10:50:39,810 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,811 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_CONST(arg=2, lineno=662)\n", - "2024-09-12 10:50:39,811 - numba.core.byteflow - DEBUG - stack ['$32load_global.0']\n", - "2024-09-12 10:50:39,812 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=CALL_FUNCTION(arg=1, lineno=662)\n", - "2024-09-12 10:50:39,813 - numba.core.byteflow - DEBUG - stack ['$32load_global.0', '$const34.1']\n", - "2024-09-12 10:50:39,813 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=RAISE_VARARGS(arg=1, lineno=662)\n", - "2024-09-12 10:50:39,814 - numba.core.byteflow - DEBUG - stack ['$36call_function.2']\n", - "2024-09-12 10:50:39,815 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:39,816 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=0), State(pc_initial=40 nstack_initial=0)])\n", - "2024-09-12 10:50:39,816 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=40 nstack_initial=0)])\n", - "2024-09-12 10:50:39,817 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,818 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=40 nstack_initial=0)\n", - "2024-09-12 10:50:39,818 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_FAST(arg=1, lineno=663)\n", - "2024-09-12 10:50:39,819 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,820 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=RETURN_VALUE(arg=None, lineno=663)\n", - "2024-09-12 10:50:39,820 - numba.core.byteflow - DEBUG - stack ['$index40.0']\n", - "2024-09-12 10:50:39,821 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:39,822 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:39,823 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=20 nstack_initial=0): set(),\n", - " State(pc_initial=32 nstack_initial=0): set(),\n", - " State(pc_initial=40 nstack_initial=0): set()})\n", - "2024-09-12 10:50:39,824 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:39,825 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:39,825 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:39,826 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:39,827 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:39,828 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:39,828 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$l4.1'}), (6, {'res': '$index6.2'}), (8, {'func': '$2load_global.0', 'args': ['$l4.1', '$index6.2'], 'res': '$8call_function.3'}), (10, {'value': '$8call_function.3'}), (12, {'res': '$index12.4'}), (14, {'res': '$const14.5'}), (16, {'lhs': '$index12.4', 'rhs': '$const14.5', 'res': '$16compare_op.6'}), (18, {'pred': '$16compare_op.6'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={20: (), 32: ()})\n", - "2024-09-12 10:50:39,829 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=20 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((20, {'res': '$index20.0'}), (22, {'res': '$22load_global.1'}), (24, {'res': '$l24.2'}), (26, {'func': '$22load_global.1', 'args': ['$l24.2'], 'res': '$26call_function.3'}), (28, {'lhs': '$index20.0', 'rhs': '$26call_function.3', 'res': '$28compare_op.4'}), (30, {'pred': '$28compare_op.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={32: (), 40: ()})\n", - "2024-09-12 10:50:39,852 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=32 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((32, {'res': '$32load_global.0'}), (34, {'res': '$const34.1'}), (36, {'func': '$32load_global.0', 'args': ['$const34.1'], 'res': '$36call_function.2'}), (38, {'exc': '$36call_function.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:39,853 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=40 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((40, {'res': '$index40.0'}), (42, {'retval': '$index40.0', 'castval': '$42return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:39,856 - numba.core.interpreter - DEBUG - label 0:\n", - " l = arg(0, name=l) ['l']\n", - " index = arg(1, name=index) ['index']\n", - " $2load_global.0 = global(fix_index: ) ['$2load_global.0']\n", - " index.1 = call $2load_global.0(l, index, func=$2load_global.0, args=[Var(l, listobject.py:651), Var(index, listobject.py:651)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'index', 'index.1', 'l']\n", - " $const14.5 = const(int, 0) ['$const14.5']\n", - " $16compare_op.6 = index.1 < $const14.5 ['$16compare_op.6', '$const14.5', 'index.1']\n", - " bool18 = global(bool: ) ['bool18']\n", - " $18pred = call bool18($16compare_op.6, func=bool18, args=(Var($16compare_op.6, listobject.py:661),), kws=(), vararg=None, varkwarg=None, target=None) ['$16compare_op.6', '$18pred', 'bool18']\n", - " branch $18pred, 32, 20 ['$18pred']\n", - "label 20:\n", - " $22load_global.1 = global(len: ) ['$22load_global.1']\n", - " $26call_function.3 = call $22load_global.1(l, func=$22load_global.1, args=[Var(l, listobject.py:651)], kws=(), vararg=None, varkwarg=None, target=None) ['$22load_global.1', '$26call_function.3', 'l']\n", - " $28compare_op.4 = index.1 >= $26call_function.3 ['$26call_function.3', '$28compare_op.4', 'index.1']\n", - " bool30 = global(bool: ) ['bool30']\n", - " $30pred = call bool30($28compare_op.4, func=bool30, args=(Var($28compare_op.4, listobject.py:661),), kws=(), vararg=None, varkwarg=None, target=None) ['$28compare_op.4', '$30pred', 'bool30']\n", - " branch $30pred, 32, 40 ['$30pred']\n", - "label 32:\n", - " $32load_global.0 = global(IndexError: ) ['$32load_global.0']\n", - " $const34.1 = const(str, list index out of range) ['$const34.1']\n", - " $36call_function.2 = call $32load_global.0($const34.1, func=$32load_global.0, args=[Var($const34.1, listobject.py:662)], kws=(), vararg=None, varkwarg=None, target=None) ['$32load_global.0', '$36call_function.2', '$const34.1']\n", - " raise $36call_function.2 ['$36call_function.2']\n", - "label 40:\n", - " $42return_value.1 = cast(value=index.1) ['$42return_value.1', 'index.1']\n", - " return $42return_value.1 ['$42return_value.1']\n", - "\n", - "2024-09-12 10:50:39,876 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:39,877 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,877 - numba.core.ssa - DEBUG - on stmt: l = arg(0, name=l)\n", - "2024-09-12 10:50:39,878 - numba.core.ssa - DEBUG - on stmt: index = arg(1, name=index)\n", - "2024-09-12 10:50:39,879 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(fix_index: )\n", - "2024-09-12 10:50:39,879 - numba.core.ssa - DEBUG - on stmt: index.1 = call $2load_global.0(l, index, func=$2load_global.0, args=[Var(l, listobject.py:651), Var(index, listobject.py:651)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,880 - numba.core.ssa - DEBUG - on stmt: $const14.5 = const(int, 0)\n", - "2024-09-12 10:50:39,881 - numba.core.ssa - DEBUG - on stmt: $16compare_op.6 = index.1 < $const14.5\n", - "2024-09-12 10:50:39,881 - numba.core.ssa - DEBUG - on stmt: bool18 = global(bool: )\n", - "2024-09-12 10:50:39,882 - numba.core.ssa - DEBUG - on stmt: $18pred = call bool18($16compare_op.6, func=bool18, args=(Var($16compare_op.6, listobject.py:661),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,883 - numba.core.ssa - DEBUG - on stmt: branch $18pred, 32, 20\n", - "2024-09-12 10:50:39,883 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 20\n", - "2024-09-12 10:50:39,884 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,885 - numba.core.ssa - DEBUG - on stmt: $22load_global.1 = global(len: )\n", - "2024-09-12 10:50:39,885 - numba.core.ssa - DEBUG - on stmt: $26call_function.3 = call $22load_global.1(l, func=$22load_global.1, args=[Var(l, listobject.py:651)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,886 - numba.core.ssa - DEBUG - on stmt: $28compare_op.4 = index.1 >= $26call_function.3\n", - "2024-09-12 10:50:39,887 - numba.core.ssa - DEBUG - on stmt: bool30 = global(bool: )\n", - "2024-09-12 10:50:39,888 - numba.core.ssa - DEBUG - on stmt: $30pred = call bool30($28compare_op.4, func=bool30, args=(Var($28compare_op.4, listobject.py:661),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,888 - numba.core.ssa - DEBUG - on stmt: branch $30pred, 32, 40\n", - "2024-09-12 10:50:39,889 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 32\n", - "2024-09-12 10:50:39,889 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,890 - numba.core.ssa - DEBUG - on stmt: $32load_global.0 = global(IndexError: )\n", - "2024-09-12 10:50:39,891 - numba.core.ssa - DEBUG - on stmt: $const34.1 = const(str, list index out of range)\n", - "2024-09-12 10:50:39,891 - numba.core.ssa - DEBUG - on stmt: $36call_function.2 = call $32load_global.0($const34.1, func=$32load_global.0, args=[Var($const34.1, listobject.py:662)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,892 - numba.core.ssa - DEBUG - on stmt: raise ('list index out of range')\n", - "2024-09-12 10:50:39,893 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 40\n", - "2024-09-12 10:50:39,893 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,894 - numba.core.ssa - DEBUG - on stmt: $42return_value.1 = cast(value=index.1)\n", - "2024-09-12 10:50:39,895 - numba.core.ssa - DEBUG - on stmt: return $42return_value.1\n", - "2024-09-12 10:50:39,896 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$16compare_op.6': [],\n", - " '$18pred': [],\n", - " '$22load_global.1': [],\n", - " '$26call_function.3': [],\n", - " '$28compare_op.4': [],\n", - " '$2load_global.0': [],\n", - " '$30pred': [],\n", - " '$32load_global.0': [],\n", - " '$36call_function.2': [],\n", - " '$42return_value.1': [],\n", - " '$const14.5': [],\n", - " '$const34.1': [],\n", - " 'bool18': [],\n", - " 'bool30': [],\n", - " 'index': [],\n", - " 'index.1': [],\n", - " 'l': []})\n", - "2024-09-12 10:50:39,897 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:39,923 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=407)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=408)\n", - " 4\tLOAD_FAST(arg=0, lineno=408)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=408)\n", - " 8\tRETURN_VALUE(arg=None, lineno=408)\n", - "2024-09-12 10:50:39,924 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:39,925 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:39,926 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:39,926 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=407)\n", - "2024-09-12 10:50:39,927 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,928 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=408)\n", - "2024-09-12 10:50:39,929 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:39,930 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=408)\n", - "2024-09-12 10:50:39,931 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:39,931 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=408)\n", - "2024-09-12 10:50:39,932 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$l4.1']\n", - "2024-09-12 10:50:39,933 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=408)\n", - "2024-09-12 10:50:39,934 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-09-12 10:50:39,935 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:39,936 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:39,936 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:39,937 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:39,938 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:39,939 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:39,940 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:39,941 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:39,941 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:39,942 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$l4.1'}), (6, {'func': '$2load_global.0', 'args': ['$l4.1'], 'res': '$6call_function.2'}), (8, {'retval': '$6call_function.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:39,944 - numba.core.interpreter - DEBUG - label 0:\n", - " l = arg(0, name=l) ['l']\n", - " $2load_global.0 = global(_list_length: ) ['$2load_global.0']\n", - " $6call_function.2 = call $2load_global.0(l, func=$2load_global.0, args=[Var(l, listobject.py:407)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', '$6call_function.2', 'l']\n", - " $8return_value.3 = cast(value=$6call_function.2) ['$6call_function.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-09-12 10:50:39,961 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:39,962 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:39,963 - numba.core.ssa - DEBUG - on stmt: l = arg(0, name=l)\n", - "2024-09-12 10:50:39,964 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(_list_length: )\n", - "2024-09-12 10:50:39,965 - numba.core.ssa - DEBUG - on stmt: $6call_function.2 = call $2load_global.0(l, func=$2load_global.0, args=[Var(l, listobject.py:407)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:39,965 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6call_function.2)\n", - "2024-09-12 10:50:39,966 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-09-12 10:50:39,967 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$2load_global.0': [],\n", - " '$6call_function.2': [],\n", - " '$8return_value.3': [],\n", - " 'l': []})\n", - "2024-09-12 10:50:39,968 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:40,150 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3773)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3774)\n", - " 4\tLOAD_FAST(arg=0, lineno=3774)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=3774)\n", - " 8\tSTORE_FAST(arg=3, lineno=3774)\n", - " 10\tLOAD_DEREF(arg=0, lineno=3775)\n", - " 12\tLOAD_FAST(arg=0, lineno=3775)\n", - " 14\tLOAD_FAST(arg=1, lineno=3775)\n", - " 16\tLOAD_FAST(arg=1, lineno=3775)\n", - " 18\tLOAD_CONST(arg=1, lineno=3775)\n", - " 20\tLOAD_FAST(arg=3, lineno=3775)\n", - " 22\tLOAD_FAST(arg=3, lineno=3775)\n", - " 24\tCALL_FUNCTION(arg=6, lineno=3775)\n", - " 26\tRETURN_VALUE(arg=None, lineno=3775)\n", - "2024-09-12 10:50:40,151 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:40,152 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,153 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:40,153 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3773)\n", - "2024-09-12 10:50:40,154 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,154 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3774)\n", - "2024-09-12 10:50:40,155 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,156 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=3774)\n", - "2024-09-12 10:50:40,156 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:40,157 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=3774)\n", - "2024-09-12 10:50:40,157 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$a4.1']\n", - "2024-09-12 10:50:40,158 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=3, lineno=3774)\n", - "2024-09-12 10:50:40,159 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-09-12 10:50:40,159 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_DEREF(arg=0, lineno=3775)\n", - "2024-09-12 10:50:40,160 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,160 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=0, lineno=3775)\n", - "2024-09-12 10:50:40,161 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3']\n", - "2024-09-12 10:50:40,162 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:40,163 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4']\n", - "2024-09-12 10:50:40,164 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:40,165 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5']\n", - "2024-09-12 10:50:40,165 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:40,166 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6']\n", - "2024-09-12 10:50:40,167 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-09-12 10:50:40,167 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7']\n", - "2024-09-12 10:50:40,168 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-09-12 10:50:40,168 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8']\n", - "2024-09-12 10:50:40,169 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=CALL_FUNCTION(arg=6, lineno=3775)\n", - "2024-09-12 10:50:40,170 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9']\n", - "2024-09-12 10:50:40,171 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=RETURN_VALUE(arg=None, lineno=3775)\n", - "2024-09-12 10:50:40,171 - numba.core.byteflow - DEBUG - stack ['$24call_function.10']\n", - "2024-09-12 10:50:40,172 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:40,172 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:40,173 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:40,174 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:40,174 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:40,175 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:40,176 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:40,176 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:40,177 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:40,177 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$a4.1'}), (6, {'func': '$2load_global.0', 'args': ['$a4.1'], 'res': '$6call_function.2'}), (8, {'value': '$6call_function.2'}), (10, {'res': '$10load_deref.3'}), (12, {'res': '$a12.4'}), (14, {'res': '$v14.5'}), (16, {'res': '$v16.6'}), (18, {'res': '$const18.7'}), (20, {'res': '$n20.8'}), (22, {'res': '$n22.9'}), (24, {'func': '$10load_deref.3', 'args': ['$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9'], 'res': '$24call_function.10'}), (26, {'retval': '$24call_function.10', 'castval': '$26return_value.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:40,179 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " side = arg(2, name=side) ['side']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'a', 'n']\n", - " $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f2dc32ed000>) ['$10load_deref.3']\n", - " $const18.7 = const(int, 0) ['$const18.7']\n", - " $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_deref.3', '$24call_function.10', '$const18.7', 'a', 'n', 'n', 'v', 'v']\n", - " $26return_value.11 = cast(value=$24call_function.10) ['$24call_function.10', '$26return_value.11']\n", - " return $26return_value.11 ['$26return_value.11']\n", - "\n", - "2024-09-12 10:50:40,190 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:40,191 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,192 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:40,192 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:40,193 - numba.core.ssa - DEBUG - on stmt: side = arg(2, name=side)\n", - "2024-09-12 10:50:40,202 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-09-12 10:50:40,203 - numba.core.ssa - DEBUG - on stmt: n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,204 - numba.core.ssa - DEBUG - on stmt: $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f2dc32ed000>)\n", - "2024-09-12 10:50:40,204 - numba.core.ssa - DEBUG - on stmt: $const18.7 = const(int, 0)\n", - "2024-09-12 10:50:40,205 - numba.core.ssa - DEBUG - on stmt: $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,206 - numba.core.ssa - DEBUG - on stmt: $26return_value.11 = cast(value=$24call_function.10)\n", - "2024-09-12 10:50:40,207 - numba.core.ssa - DEBUG - on stmt: return $26return_value.11\n", - "2024-09-12 10:50:40,208 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_deref.3': [],\n", - " '$24call_function.10': [],\n", - " '$26return_value.11': [],\n", - " '$2load_global.0': [],\n", - " '$const18.7': [],\n", - " 'a': [],\n", - " 'n': [],\n", - " 'side': [],\n", - " 'v': []})\n", - "2024-09-12 10:50:40,208 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:40,214 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3678)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3701)\n", - " 4\tLOAD_METHOD(arg=1, lineno=3701)\n", - " 6\tLOAD_FAST(arg=1, lineno=3701)\n", - " 8\tCALL_METHOD(arg=1, lineno=3701)\n", - " 10\tPOP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - " 12\tLOAD_GLOBAL(arg=2, lineno=3704)\n", - " 14\tLOAD_FAST(arg=5, lineno=3704)\n", - " 16\tLOAD_CONST(arg=1, lineno=3704)\n", - " 18\tLOAD_CONST(arg=2, lineno=3704)\n", - " 20\tCALL_FUNCTION(arg=3, lineno=3704)\n", - " 22\tGET_ITER(arg=None, lineno=3704)\n", - "> 24\tFOR_ITER(arg=15, lineno=3704)\n", - " 26\tSTORE_FAST(arg=6, lineno=3704)\n", - " 28\tLOAD_GLOBAL(arg=0, lineno=3705)\n", - " 30\tLOAD_METHOD(arg=1, lineno=3705)\n", - " 32\tLOAD_FAST(arg=0, lineno=3705)\n", - " 34\tLOAD_FAST(arg=6, lineno=3705)\n", - " 36\tLOAD_CONST(arg=3, lineno=3705)\n", - " 38\tBINARY_SUBTRACT(arg=None, lineno=3705)\n", - " 40\tBINARY_SUBSCR(arg=None, lineno=3705)\n", - " 42\tCALL_METHOD(arg=1, lineno=3705)\n", - " 44\tPOP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - " 46\tLOAD_FAST(arg=6, lineno=3706)\n", - " 48\tROT_TWO(arg=None, lineno=3706)\n", - " 50\tPOP_TOP(arg=None, lineno=3706)\n", - " 52\tRETURN_VALUE(arg=None, lineno=3706)\n", - "> 54\tJUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "> 56\tLOAD_CONST(arg=1, lineno=3707)\n", - " 58\tRETURN_VALUE(arg=None, lineno=3707)\n", - "> 60\tLOAD_FAST(arg=2, lineno=3709)\n", - " 62\tLOAD_FAST(arg=1, lineno=3709)\n", - " 64\tCOMPARE_OP(arg=0, lineno=3709)\n", - " 66\tPOP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - " 68\tLOAD_FAST(arg=5, lineno=3710)\n", - " 70\tSTORE_FAST(arg=4, lineno=3710)\n", - " 72\tJUMP_FORWARD(arg=12, lineno=3710)\n", - "> 74\tLOAD_CONST(arg=1, lineno=3712)\n", - " 76\tSTORE_FAST(arg=3, lineno=3712)\n", - " 78\tLOAD_FAST(arg=4, lineno=3713)\n", - " 80\tLOAD_FAST(arg=5, lineno=3713)\n", - " 82\tCOMPARE_OP(arg=0, lineno=3713)\n", - " 84\tPOP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - " 86\tLOAD_FAST(arg=4, lineno=3713)\n", - " 88\tLOAD_CONST(arg=3, lineno=3713)\n", - " 90\tBINARY_ADD(arg=None, lineno=3713)\n", - " 92\tJUMP_FORWARD(arg=1, lineno=3713)\n", - "> 94\tLOAD_FAST(arg=5, lineno=3713)\n", - "> 96\tSTORE_FAST(arg=4, lineno=3713)\n", - "> 98\tLOAD_FAST(arg=4, lineno=3715)\n", - " 100\tLOAD_FAST(arg=3, lineno=3715)\n", - " 102\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 104\tPOP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "> 106\tLOAD_FAST(arg=3, lineno=3716)\n", - " 108\tLOAD_FAST(arg=4, lineno=3716)\n", - " 110\tBINARY_ADD(arg=None, lineno=3716)\n", - " 112\tLOAD_CONST(arg=3, lineno=3716)\n", - " 114\tBINARY_RSHIFT(arg=None, lineno=3716)\n", - " 116\tSTORE_FAST(arg=7, lineno=3716)\n", - " 118\tLOAD_DEREF(arg=0, lineno=3717)\n", - " 120\tLOAD_FAST(arg=0, lineno=3717)\n", - " 122\tLOAD_FAST(arg=7, lineno=3717)\n", - " 124\tBINARY_SUBSCR(arg=None, lineno=3717)\n", - " 126\tLOAD_FAST(arg=1, lineno=3717)\n", - " 128\tCALL_FUNCTION(arg=2, lineno=3717)\n", - " 130\tPOP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - " 132\tLOAD_FAST(arg=7, lineno=3719)\n", - " 134\tLOAD_CONST(arg=3, lineno=3719)\n", - " 136\tBINARY_ADD(arg=None, lineno=3719)\n", - " 138\tSTORE_FAST(arg=3, lineno=3719)\n", - " 140\tJUMP_FORWARD(arg=2, lineno=3719)\n", - "> 142\tLOAD_FAST(arg=7, lineno=3722)\n", - " 144\tSTORE_FAST(arg=4, lineno=3722)\n", - "> 146\tLOAD_FAST(arg=4, lineno=3715)\n", - " 148\tLOAD_FAST(arg=3, lineno=3715)\n", - " 150\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 152\tPOP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "> 154\tLOAD_FAST(arg=3, lineno=3723)\n", - " 156\tRETURN_VALUE(arg=None, lineno=3723)\n", - "2024-09-12 10:50:40,215 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:40,215 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,216 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:40,220 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3678)\n", - "2024-09-12 10:50:40,221 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,222 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3701)\n", - "2024-09-12 10:50:40,223 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,223 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=1, lineno=3701)\n", - "2024-09-12 10:50:40,224 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:40,225 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=3701)\n", - "2024-09-12 10:50:40,226 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-09-12 10:50:40,227 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_METHOD(arg=1, lineno=3701)\n", - "2024-09-12 10:50:40,227 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$v6.2']\n", - "2024-09-12 10:50:40,228 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=POP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - "2024-09-12 10:50:40,229 - numba.core.byteflow - DEBUG - stack ['$8call_method.3']\n", - "2024-09-12 10:50:40,230 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=12, stack=(), blockstack=(), npush=0), Edge(pc=60, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,230 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=12 nstack_initial=0), State(pc_initial=60 nstack_initial=0)])\n", - "2024-09-12 10:50:40,231 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,232 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=12 nstack_initial=0)\n", - "2024-09-12 10:50:40,233 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_GLOBAL(arg=2, lineno=3704)\n", - "2024-09-12 10:50:40,233 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,234 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=5, lineno=3704)\n", - "2024-09-12 10:50:40,235 - numba.core.byteflow - DEBUG - stack ['$12load_global.0']\n", - "2024-09-12 10:50:40,236 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_CONST(arg=1, lineno=3704)\n", - "2024-09-12 10:50:40,237 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1']\n", - "2024-09-12 10:50:40,237 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=2, lineno=3704)\n", - "2024-09-12 10:50:40,238 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2']\n", - "2024-09-12 10:50:40,239 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=CALL_FUNCTION(arg=3, lineno=3704)\n", - "2024-09-12 10:50:40,240 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2', '$const18.3']\n", - "2024-09-12 10:50:40,241 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=GET_ITER(arg=None, lineno=3704)\n", - "2024-09-12 10:50:40,241 - numba.core.byteflow - DEBUG - stack ['$20call_function.4']\n", - "2024-09-12 10:50:40,242 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$22get_iter.5',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,243 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=0), State(pc_initial=24 nstack_initial=1)])\n", - "2024-09-12 10:50:40,244 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,245 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=60 nstack_initial=0)\n", - "2024-09-12 10:50:40,246 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_FAST(arg=2, lineno=3709)\n", - "2024-09-12 10:50:40,246 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,247 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_FAST(arg=1, lineno=3709)\n", - "2024-09-12 10:50:40,248 - numba.core.byteflow - DEBUG - stack ['$v_last60.0']\n", - "2024-09-12 10:50:40,249 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=COMPARE_OP(arg=0, lineno=3709)\n", - "2024-09-12 10:50:40,250 - numba.core.byteflow - DEBUG - stack ['$v_last60.0', '$v62.1']\n", - "2024-09-12 10:50:40,250 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=POP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - "2024-09-12 10:50:40,251 - numba.core.byteflow - DEBUG - stack ['$64compare_op.2']\n", - "2024-09-12 10:50:40,252 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=68, stack=(), blockstack=(), npush=0), Edge(pc=74, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,253 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0)])\n", - "2024-09-12 10:50:40,254 - numba.core.byteflow - DEBUG - stack: ['$phi24.0']\n", - "2024-09-12 10:50:40,254 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=24 nstack_initial=1)\n", - "2024-09-12 10:50:40,255 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=FOR_ITER(arg=15, lineno=3704)\n", - "2024-09-12 10:50:40,256 - numba.core.byteflow - DEBUG - stack ['$phi24.0']\n", - "2024-09-12 10:50:40,257 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=56, stack=(), blockstack=(), npush=0), Edge(pc=26, stack=('$phi24.0', '$24for_iter.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,258 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2)])\n", - "2024-09-12 10:50:40,259 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,260 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=68 nstack_initial=0)\n", - "2024-09-12 10:50:40,270 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_FAST(arg=5, lineno=3710)\n", - "2024-09-12 10:50:40,270 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,271 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=STORE_FAST(arg=4, lineno=3710)\n", - "2024-09-12 10:50:40,272 - numba.core.byteflow - DEBUG - stack ['$n68.0']\n", - "2024-09-12 10:50:40,272 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=JUMP_FORWARD(arg=12, lineno=3710)\n", - "2024-09-12 10:50:40,273 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,274 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,275 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:40,275 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,276 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=0)\n", - "2024-09-12 10:50:40,277 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=1, lineno=3712)\n", - "2024-09-12 10:50:40,278 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,278 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=STORE_FAST(arg=3, lineno=3712)\n", - "2024-09-12 10:50:40,279 - numba.core.byteflow - DEBUG - stack ['$const74.0']\n", - "2024-09-12 10:50:40,280 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-09-12 10:50:40,282 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,283 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-09-12 10:50:40,283 - numba.core.byteflow - DEBUG - stack ['$hi78.1']\n", - "2024-09-12 10:50:40,284 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=COMPARE_OP(arg=0, lineno=3713)\n", - "2024-09-12 10:50:40,285 - numba.core.byteflow - DEBUG - stack ['$hi78.1', '$n80.2']\n", - "2024-09-12 10:50:40,286 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=POP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - "2024-09-12 10:50:40,286 - numba.core.byteflow - DEBUG - stack ['$82compare_op.3']\n", - "2024-09-12 10:50:40,287 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=86, stack=(), blockstack=(), npush=0), Edge(pc=94, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,288 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-09-12 10:50:40,289 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,289 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=0)\n", - "2024-09-12 10:50:40,290 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_CONST(arg=1, lineno=3707)\n", - "2024-09-12 10:50:40,291 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,291 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=RETURN_VALUE(arg=None, lineno=3707)\n", - "2024-09-12 10:50:40,292 - numba.core.byteflow - DEBUG - stack ['$const56.0']\n", - "2024-09-12 10:50:40,293 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:40,294 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-09-12 10:50:40,294 - numba.core.byteflow - DEBUG - stack: ['$phi26.0', '$phi26.1']\n", - "2024-09-12 10:50:40,295 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=26 nstack_initial=2)\n", - "2024-09-12 10:50:40,296 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=STORE_FAST(arg=6, lineno=3704)\n", - "2024-09-12 10:50:40,296 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$phi26.1']\n", - "2024-09-12 10:50:40,297 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_GLOBAL(arg=0, lineno=3705)\n", - "2024-09-12 10:50:40,298 - numba.core.byteflow - DEBUG - stack ['$phi26.0']\n", - "2024-09-12 10:50:40,299 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_METHOD(arg=1, lineno=3705)\n", - "2024-09-12 10:50:40,299 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$28load_global.2']\n", - "2024-09-12 10:50:40,300 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_FAST(arg=0, lineno=3705)\n", - "2024-09-12 10:50:40,301 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3']\n", - "2024-09-12 10:50:40,301 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=6, lineno=3705)\n", - "2024-09-12 10:50:40,302 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4']\n", - "2024-09-12 10:50:40,303 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_CONST(arg=3, lineno=3705)\n", - "2024-09-12 10:50:40,304 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5']\n", - "2024-09-12 10:50:40,304 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=BINARY_SUBTRACT(arg=None, lineno=3705)\n", - "2024-09-12 10:50:40,305 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5', '$const36.6']\n", - "2024-09-12 10:50:40,306 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=BINARY_SUBSCR(arg=None, lineno=3705)\n", - "2024-09-12 10:50:40,306 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$38binary_subtract.7']\n", - "2024-09-12 10:50:40,307 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=CALL_METHOD(arg=1, lineno=3705)\n", - "2024-09-12 10:50:40,308 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$40binary_subscr.8']\n", - "2024-09-12 10:50:40,308 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - "2024-09-12 10:50:40,309 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$42call_method.9']\n", - "2024-09-12 10:50:40,310 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=('$phi26.0',), blockstack=(), npush=0), Edge(pc=54, stack=('$phi26.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,311 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1)])\n", - "2024-09-12 10:50:40,312 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,312 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=98 nstack_initial=0)\n", - "2024-09-12 10:50:40,313 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-09-12 10:50:40,314 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,314 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-09-12 10:50:40,315 - numba.core.byteflow - DEBUG - stack ['$hi98.0']\n", - "2024-09-12 10:50:40,316 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-09-12 10:50:40,316 - numba.core.byteflow - DEBUG - stack ['$hi98.0', '$lo100.1']\n", - "2024-09-12 10:50:40,317 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=POP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "2024-09-12 10:50:40,318 - numba.core.byteflow - DEBUG - stack ['$102compare_op.2']\n", - "2024-09-12 10:50:40,318 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=106, stack=(), blockstack=(), npush=0), Edge(pc=154, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,319 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0)])\n", - "2024-09-12 10:50:40,320 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,321 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=86 nstack_initial=0)\n", - "2024-09-12 10:50:40,321 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-09-12 10:50:40,322 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,323 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_CONST(arg=3, lineno=3713)\n", - "2024-09-12 10:50:40,323 - numba.core.byteflow - DEBUG - stack ['$hi86.0']\n", - "2024-09-12 10:50:40,324 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=BINARY_ADD(arg=None, lineno=3713)\n", - "2024-09-12 10:50:40,325 - numba.core.byteflow - DEBUG - stack ['$hi86.0', '$const88.1']\n", - "2024-09-12 10:50:40,325 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=JUMP_FORWARD(arg=1, lineno=3713)\n", - "2024-09-12 10:50:40,326 - numba.core.byteflow - DEBUG - stack ['$90binary_add.2']\n", - "2024-09-12 10:50:40,327 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$90binary_add.2',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,327 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1)])\n", - "2024-09-12 10:50:40,328 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,329 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=94 nstack_initial=0)\n", - "2024-09-12 10:50:40,330 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-09-12 10:50:40,330 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,331 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$n94.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,332 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-09-12 10:50:40,332 - numba.core.byteflow - DEBUG - stack: ['$phi46.0']\n", - "2024-09-12 10:50:40,333 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=1)\n", - "2024-09-12 10:50:40,334 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=6, lineno=3706)\n", - "2024-09-12 10:50:40,334 - numba.core.byteflow - DEBUG - stack ['$phi46.0']\n", - "2024-09-12 10:50:40,335 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=ROT_TWO(arg=None, lineno=3706)\n", - "2024-09-12 10:50:40,336 - numba.core.byteflow - DEBUG - stack ['$phi46.0', '$i46.1']\n", - "2024-09-12 10:50:40,336 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=POP_TOP(arg=None, lineno=3706)\n", - "2024-09-12 10:50:40,337 - numba.core.byteflow - DEBUG - stack ['$i46.1', '$phi46.0']\n", - "2024-09-12 10:50:40,338 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=RETURN_VALUE(arg=None, lineno=3706)\n", - "2024-09-12 10:50:40,338 - numba.core.byteflow - DEBUG - stack ['$i46.1']\n", - "2024-09-12 10:50:40,339 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:40,340 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-09-12 10:50:40,340 - numba.core.byteflow - DEBUG - stack: ['$phi54.0']\n", - "2024-09-12 10:50:40,341 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=1)\n", - "2024-09-12 10:50:40,342 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=JUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "2024-09-12 10:50:40,342 - numba.core.byteflow - DEBUG - stack ['$phi54.0']\n", - "2024-09-12 10:50:40,343 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$phi54.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,344 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1)])\n", - "2024-09-12 10:50:40,344 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,345 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=106 nstack_initial=0)\n", - "2024-09-12 10:50:40,346 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_FAST(arg=3, lineno=3716)\n", - "2024-09-12 10:50:40,346 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,347 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_FAST(arg=4, lineno=3716)\n", - "2024-09-12 10:50:40,347 - numba.core.byteflow - DEBUG - stack ['$lo106.0']\n", - "2024-09-12 10:50:40,348 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=BINARY_ADD(arg=None, lineno=3716)\n", - "2024-09-12 10:50:40,349 - numba.core.byteflow - DEBUG - stack ['$lo106.0', '$hi108.1']\n", - "2024-09-12 10:50:40,349 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=3, lineno=3716)\n", - "2024-09-12 10:50:40,350 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2']\n", - "2024-09-12 10:50:40,351 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BINARY_RSHIFT(arg=None, lineno=3716)\n", - "2024-09-12 10:50:40,352 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2', '$const112.3']\n", - "2024-09-12 10:50:40,352 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=STORE_FAST(arg=7, lineno=3716)\n", - "2024-09-12 10:50:40,353 - numba.core.byteflow - DEBUG - stack ['$114binary_rshift.4']\n", - "2024-09-12 10:50:40,353 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_DEREF(arg=0, lineno=3717)\n", - "2024-09-12 10:50:40,354 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,355 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=0, lineno=3717)\n", - "2024-09-12 10:50:40,355 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5']\n", - "2024-09-12 10:50:40,356 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_FAST(arg=7, lineno=3717)\n", - "2024-09-12 10:50:40,357 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6']\n", - "2024-09-12 10:50:40,357 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=BINARY_SUBSCR(arg=None, lineno=3717)\n", - "2024-09-12 10:50:40,358 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6', '$mid122.7']\n", - "2024-09-12 10:50:40,358 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_FAST(arg=1, lineno=3717)\n", - "2024-09-12 10:50:40,359 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8']\n", - "2024-09-12 10:50:40,360 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=CALL_FUNCTION(arg=2, lineno=3717)\n", - "2024-09-12 10:50:40,360 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8', '$v126.9']\n", - "2024-09-12 10:50:40,361 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=POP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - "2024-09-12 10:50:40,361 - numba.core.byteflow - DEBUG - stack ['$128call_function.10']\n", - "2024-09-12 10:50:40,362 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=132, stack=(), blockstack=(), npush=0), Edge(pc=142, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,363 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-09-12 10:50:40,363 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,364 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=154 nstack_initial=0)\n", - "2024-09-12 10:50:40,365 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_FAST(arg=3, lineno=3723)\n", - "2024-09-12 10:50:40,365 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,366 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=RETURN_VALUE(arg=None, lineno=3723)\n", - "2024-09-12 10:50:40,366 - numba.core.byteflow - DEBUG - stack ['$lo154.0']\n", - "2024-09-12 10:50:40,367 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:40,368 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-09-12 10:50:40,368 - numba.core.byteflow - DEBUG - stack: ['$phi96.0']\n", - "2024-09-12 10:50:40,369 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=96 nstack_initial=1)\n", - "2024-09-12 10:50:40,369 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=STORE_FAST(arg=4, lineno=3713)\n", - "2024-09-12 10:50:40,370 - numba.core.byteflow - DEBUG - stack ['$phi96.0']\n", - "2024-09-12 10:50:40,371 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,372 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:40,372 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:40,373 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:40,373 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,374 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=132 nstack_initial=0)\n", - "2024-09-12 10:50:40,375 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_FAST(arg=7, lineno=3719)\n", - "2024-09-12 10:50:40,375 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,376 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_CONST(arg=3, lineno=3719)\n", - "2024-09-12 10:50:40,377 - numba.core.byteflow - DEBUG - stack ['$mid132.0']\n", - "2024-09-12 10:50:40,377 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BINARY_ADD(arg=None, lineno=3719)\n", - "2024-09-12 10:50:40,378 - numba.core.byteflow - DEBUG - stack ['$mid132.0', '$const134.1']\n", - "2024-09-12 10:50:40,379 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=STORE_FAST(arg=3, lineno=3719)\n", - "2024-09-12 10:50:40,379 - numba.core.byteflow - DEBUG - stack ['$136binary_add.2']\n", - "2024-09-12 10:50:40,380 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=JUMP_FORWARD(arg=2, lineno=3719)\n", - "2024-09-12 10:50:40,380 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,381 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,382 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-09-12 10:50:40,382 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,383 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=142 nstack_initial=0)\n", - "2024-09-12 10:50:40,384 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=7, lineno=3722)\n", - "2024-09-12 10:50:40,384 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,385 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=STORE_FAST(arg=4, lineno=3722)\n", - "2024-09-12 10:50:40,385 - numba.core.byteflow - DEBUG - stack ['$mid142.0']\n", - "2024-09-12 10:50:40,386 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,387 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-09-12 10:50:40,408 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-09-12 10:50:40,409 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:40,409 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=146 nstack_initial=0)\n", - "2024-09-12 10:50:40,410 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-09-12 10:50:40,410 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:40,411 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-09-12 10:50:40,411 - numba.core.byteflow - DEBUG - stack ['$hi146.0']\n", - "2024-09-12 10:50:40,412 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-09-12 10:50:40,412 - numba.core.byteflow - DEBUG - stack ['$hi146.0', '$lo148.1']\n", - "2024-09-12 10:50:40,413 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=POP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "2024-09-12 10:50:40,414 - numba.core.byteflow - DEBUG - stack ['$150compare_op.2']\n", - "2024-09-12 10:50:40,414 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=154, stack=(), blockstack=(), npush=0), Edge(pc=106, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:40,415 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-09-12 10:50:40,415 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-09-12 10:50:40,416 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0)])\n", - "2024-09-12 10:50:40,416 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:40,417 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=12 nstack_initial=0): set(),\n", - " State(pc_initial=24 nstack_initial=1): {'$phi24.0'},\n", - " State(pc_initial=26 nstack_initial=2): {'$phi26.1'},\n", - " State(pc_initial=46 nstack_initial=1): set(),\n", - " State(pc_initial=54 nstack_initial=1): set(),\n", - " State(pc_initial=56 nstack_initial=0): set(),\n", - " State(pc_initial=60 nstack_initial=0): set(),\n", - " State(pc_initial=68 nstack_initial=0): set(),\n", - " State(pc_initial=74 nstack_initial=0): set(),\n", - " State(pc_initial=86 nstack_initial=0): set(),\n", - " State(pc_initial=94 nstack_initial=0): set(),\n", - " State(pc_initial=96 nstack_initial=1): {'$phi96.0'},\n", - " State(pc_initial=98 nstack_initial=0): set(),\n", - " State(pc_initial=106 nstack_initial=0): set(),\n", - " State(pc_initial=132 nstack_initial=0): set(),\n", - " State(pc_initial=142 nstack_initial=0): set(),\n", - " State(pc_initial=146 nstack_initial=0): set(),\n", - " State(pc_initial=154 nstack_initial=0): set()})\n", - "2024-09-12 10:50:40,420 - numba.core.byteflow - DEBUG - defmap: {'$phi24.0': State(pc_initial=12 nstack_initial=0),\n", - " '$phi26.1': State(pc_initial=24 nstack_initial=1),\n", - " '$phi96.0': State(pc_initial=86 nstack_initial=0)}\n", - "2024-09-12 10:50:40,421 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi54.0', State(pc_initial=54 nstack_initial=1))},\n", - " '$phi26.0': {('$phi24.0', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi54.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:40,422 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:40,423 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:40,425 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:40,426 - numba.core.byteflow - DEBUG - keep phismap: {'$phi24.0': {('$22get_iter.5', State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi96.0': {('$90binary_add.2', State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}}\n", - "2024-09-12 10:50:40,426 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=12 nstack_initial=0): {'$phi24.0': '$22get_iter.5'},\n", - " State(pc_initial=24 nstack_initial=1): {'$phi26.1': '$24for_iter.2'},\n", - " State(pc_initial=86 nstack_initial=0): {'$phi96.0': '$90binary_add.2'},\n", - " State(pc_initial=94 nstack_initial=0): {'$phi96.0': '$n94.0'}})\n", - "2024-09-12 10:50:40,427 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:40,428 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_method.1'}), (6, {'res': '$v6.2'}), (8, {'func': '$4load_method.1', 'args': ['$v6.2'], 'res': '$8call_method.3'}), (10, {'pred': '$8call_method.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={12: (), 60: ()})\n", - "2024-09-12 10:50:40,428 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=12 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((12, {'res': '$12load_global.0'}), (14, {'res': '$n14.1'}), (16, {'res': '$const16.2'}), (18, {'res': '$const18.3'}), (20, {'func': '$12load_global.0', 'args': ['$n14.1', '$const16.2', '$const18.3'], 'res': '$20call_function.4'}), (22, {'value': '$20call_function.4', 'res': '$22get_iter.5'})), outgoing_phis={'$phi24.0': '$22get_iter.5'}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$22get_iter.5',)})\n", - "2024-09-12 10:50:40,429 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=24 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((24, {'iterator': '$phi24.0', 'pair': '$24for_iter.1', 'indval': '$24for_iter.2', 'pred': '$24for_iter.3'}),), outgoing_phis={'$phi26.1': '$24for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={56: (), 26: ('$phi24.0', '$24for_iter.2')})\n", - "2024-09-12 10:50:40,430 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=26 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((26, {'value': '$phi26.1'}), (28, {'res': '$28load_global.2'}), (30, {'item': '$28load_global.2', 'res': '$30load_method.3'}), (32, {'res': '$a32.4'}), (34, {'res': '$i34.5'}), (36, {'res': '$const36.6'}), (38, {'lhs': '$i34.5', 'rhs': '$const36.6', 'res': '$38binary_subtract.7'}), (40, {'index': '$38binary_subtract.7', 'target': '$a32.4', 'res': '$40binary_subscr.8'}), (42, {'func': '$30load_method.3', 'args': ['$40binary_subscr.8'], 'res': '$42call_method.9'}), (44, {'pred': '$42call_method.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: ('$phi26.0',), 54: ('$phi26.0',)})\n", - "2024-09-12 10:50:40,430 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((46, {'res': '$i46.1'}), (52, {'retval': '$i46.1', 'castval': '$52return_value.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:40,431 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((54, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$phi54.0',)})\n", - "2024-09-12 10:50:40,431 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((56, {'res': '$const56.0'}), (58, {'retval': '$const56.0', 'castval': '$58return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:40,432 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=60 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((60, {'res': '$v_last60.0'}), (62, {'res': '$v62.1'}), (64, {'lhs': '$v_last60.0', 'rhs': '$v62.1', 'res': '$64compare_op.2'}), (66, {'pred': '$64compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={68: (), 74: ()})\n", - "2024-09-12 10:50:40,432 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=68 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((68, {'res': '$n68.0'}), (70, {'value': '$n68.0'}), (72, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-09-12 10:50:40,433 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((74, {'res': '$const74.0'}), (76, {'value': '$const74.0'}), (78, {'res': '$hi78.1'}), (80, {'res': '$n80.2'}), (82, {'lhs': '$hi78.1', 'rhs': '$n80.2', 'res': '$82compare_op.3'}), (84, {'pred': '$82compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={86: (), 94: ()})\n", - "2024-09-12 10:50:40,434 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=86 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((86, {'res': '$hi86.0'}), (88, {'res': '$const88.1'}), (90, {'lhs': '$hi86.0', 'rhs': '$const88.1', 'res': '$90binary_add.2'}), (92, {})), outgoing_phis={'$phi96.0': '$90binary_add.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$90binary_add.2',)})\n", - "2024-09-12 10:50:40,434 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=94 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((94, {'res': '$n94.0'}),), outgoing_phis={'$phi96.0': '$n94.0'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$n94.0',)})\n", - "2024-09-12 10:50:40,435 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=96 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((96, {'value': '$phi96.0'}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-09-12 10:50:40,435 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=98 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((98, {'res': '$hi98.0'}), (100, {'res': '$lo100.1'}), (102, {'lhs': '$hi98.0', 'rhs': '$lo100.1', 'res': '$102compare_op.2'}), (104, {'pred': '$102compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={106: (), 154: ()})\n", - "2024-09-12 10:50:40,436 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=106 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((106, {'res': '$lo106.0'}), (108, {'res': '$hi108.1'}), (110, {'lhs': '$lo106.0', 'rhs': '$hi108.1', 'res': '$110binary_add.2'}), (112, {'res': '$const112.3'}), (114, {'lhs': '$110binary_add.2', 'rhs': '$const112.3', 'res': '$114binary_rshift.4'}), (116, {'value': '$114binary_rshift.4'}), (118, {'res': '$118load_deref.5'}), (120, {'res': '$a120.6'}), (122, {'res': '$mid122.7'}), (124, {'index': '$mid122.7', 'target': '$a120.6', 'res': '$124binary_subscr.8'}), (126, {'res': '$v126.9'}), (128, {'func': '$118load_deref.5', 'args': ['$124binary_subscr.8', '$v126.9'], 'res': '$128call_function.10'}), (130, {'pred': '$128call_function.10'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={132: (), 142: ()})\n", - "2024-09-12 10:50:40,439 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=132 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((132, {'res': '$mid132.0'}), (134, {'res': '$const134.1'}), (136, {'lhs': '$mid132.0', 'rhs': '$const134.1', 'res': '$136binary_add.2'}), (138, {'value': '$136binary_add.2'}), (140, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-09-12 10:50:40,440 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=142 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((142, {'res': '$mid142.0'}), (144, {'value': '$mid142.0'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-09-12 10:50:40,440 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=146 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((146, {'res': '$hi146.0'}), (148, {'res': '$lo148.1'}), (150, {'lhs': '$hi146.0', 'rhs': '$lo148.1', 'res': '$150compare_op.2'}), (152, {'pred': '$150compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={154: (), 106: ()})\n", - "2024-09-12 10:50:40,441 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=154 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((154, {'res': '$lo154.0'}), (156, {'retval': '$lo154.0', 'castval': '$156return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:40,447 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " v_last = arg(2, name=v_last) ['v_last']\n", - " lo = arg(3, name=lo) ['lo']\n", - " hi = arg(4, name=hi) ['hi']\n", - " n = arg(5, name=n) ['n']\n", - " $2load_global.0 = global(np: ) ['$2load_global.0']\n", - " $4load_method.1 = getattr(value=$2load_global.0, attr=isnan) ['$2load_global.0', '$4load_method.1']\n", - " $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$8call_method.3', 'v']\n", - " bool10 = global(bool: ) ['bool10']\n", - " $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None) ['$10pred', '$8call_method.3', 'bool10']\n", - " branch $10pred, 12, 60 ['$10pred']\n", - "label 12:\n", - " $12load_global.0 = global(range: ) ['$12load_global.0']\n", - " $const16.2 = const(int, 0) ['$const16.2']\n", - " $const18.3 = const(int, -1) ['$const18.3']\n", - " $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_global.0', '$20call_function.4', '$const16.2', '$const18.3', 'n']\n", - " $22get_iter.5 = getiter(value=$20call_function.4) ['$20call_function.4', '$22get_iter.5']\n", - " $phi24.0 = $22get_iter.5 ['$22get_iter.5', '$phi24.0']\n", - " jump 24 []\n", - "label 24:\n", - " $24for_iter.1 = iternext(value=$phi24.0) ['$24for_iter.1', '$phi24.0']\n", - " $24for_iter.2 = pair_first(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.2']\n", - " $24for_iter.3 = pair_second(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.3']\n", - " $phi26.1 = $24for_iter.2 ['$24for_iter.2', '$phi26.1']\n", - " branch $24for_iter.3, 26, 56 ['$24for_iter.3']\n", - "label 26:\n", - " i = $phi26.1 ['$phi26.1', 'i']\n", - " $28load_global.2 = global(np: ) ['$28load_global.2']\n", - " $30load_method.3 = getattr(value=$28load_global.2, attr=isnan) ['$28load_global.2', '$30load_method.3']\n", - " $const36.6 = const(int, 1) ['$const36.6']\n", - " $38binary_subtract.7 = i - $const36.6 ['$38binary_subtract.7', '$const36.6', 'i']\n", - " $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=) ['$38binary_subtract.7', '$40binary_subscr.8', 'a']\n", - " $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None) ['$30load_method.3', '$40binary_subscr.8', '$42call_method.9']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None) ['$42call_method.9', '$44pred', 'bool44']\n", - " branch $44pred, 54, 46 ['$44pred']\n", - "label 46:\n", - " $52return_value.2 = cast(value=i) ['$52return_value.2', 'i']\n", - " return $52return_value.2 ['$52return_value.2']\n", - "label 54:\n", - " jump 24 []\n", - "label 56:\n", - " $const56.0 = const(int, 0) ['$const56.0']\n", - " $58return_value.1 = cast(value=$const56.0) ['$58return_value.1', '$const56.0']\n", - " return $58return_value.1 ['$58return_value.1']\n", - "label 60:\n", - " $64compare_op.2 = v_last < v ['$64compare_op.2', 'v', 'v_last']\n", - " bool66 = global(bool: ) ['bool66']\n", - " $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None) ['$64compare_op.2', '$66pred', 'bool66']\n", - " branch $66pred, 68, 74 ['$66pred']\n", - "label 68:\n", - " hi = n ['hi', 'n']\n", - " jump 98 []\n", - "label 74:\n", - " lo = const(int, 0) ['lo']\n", - " $82compare_op.3 = hi < n ['$82compare_op.3', 'hi', 'n']\n", - " bool84 = global(bool: ) ['bool84']\n", - " $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None) ['$82compare_op.3', '$84pred', 'bool84']\n", - " branch $84pred, 86, 94 ['$84pred']\n", - "label 86:\n", - " $const88.1 = const(int, 1) ['$const88.1']\n", - " $90binary_add.2 = hi + $const88.1 ['$90binary_add.2', '$const88.1', 'hi']\n", - " $phi96.0 = $90binary_add.2 ['$90binary_add.2', '$phi96.0']\n", - " jump 96 []\n", - "label 94:\n", - " $phi96.0 = n ['$phi96.0', 'n']\n", - " jump 96 []\n", - "label 96:\n", - " hi = $phi96.0 ['$phi96.0', 'hi']\n", - " jump 98 []\n", - "label 98:\n", - " $102compare_op.2 = hi > lo ['$102compare_op.2', 'hi', 'lo']\n", - " bool104 = global(bool: ) ['bool104']\n", - " $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$102compare_op.2', '$104pred', 'bool104']\n", - " branch $104pred, 106, 154 ['$104pred']\n", - "label 106:\n", - " $110binary_add.2 = lo + hi ['$110binary_add.2', 'hi', 'lo']\n", - " $const112.3 = const(int, 1) ['$const112.3']\n", - " mid = $110binary_add.2 >> $const112.3 ['$110binary_add.2', '$const112.3', 'mid']\n", - " $118load_deref.5 = freevar(func: ) ['$118load_deref.5']\n", - " $124binary_subscr.8 = getitem(value=a, index=mid, fn=) ['$124binary_subscr.8', 'a', 'mid']\n", - " $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$118load_deref.5', '$124binary_subscr.8', '$128call_function.10', 'v']\n", - " bool130 = global(bool: ) ['bool130']\n", - " $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None) ['$128call_function.10', '$130pred', 'bool130']\n", - " branch $130pred, 132, 142 ['$130pred']\n", - "label 132:\n", - " $const134.1 = const(int, 1) ['$const134.1']\n", - " lo = mid + $const134.1 ['$const134.1', 'lo', 'mid']\n", - " jump 146 []\n", - "label 142:\n", - " hi = mid ['hi', 'mid']\n", - " jump 146 []\n", - "label 146:\n", - " $150compare_op.2 = hi > lo ['$150compare_op.2', 'hi', 'lo']\n", - " bool152 = global(bool: ) ['bool152']\n", - " $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$150compare_op.2', '$152pred', 'bool152']\n", - " branch $152pred, 106, 154 ['$152pred']\n", - "label 154:\n", - " $156return_value.1 = cast(value=lo) ['$156return_value.1', 'lo']\n", - " return $156return_value.1 ['$156return_value.1']\n", - "\n", - "2024-09-12 10:50:40,483 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:40,484 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,484 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:40,485 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:40,486 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:40,487 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:40,487 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:40,488 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:40,489 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:40,489 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:40,490 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,491 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:40,492 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,492 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:40,493 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 12\n", - "2024-09-12 10:50:40,494 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,495 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:40,495 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:40,496 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:40,497 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,497 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:40,498 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:40,499 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,500 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 24\n", - "2024-09-12 10:50:40,500 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,501 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:40,502 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,502 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,503 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:40,504 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:40,505 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 26\n", - "2024-09-12 10:50:40,505 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,506 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:40,507 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:40,507 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:40,508 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:40,509 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:40,509 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:40,510 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,511 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:40,512 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,512 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:40,513 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-09-12 10:50:40,514 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,515 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:40,515 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:40,516 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-09-12 10:50:40,517 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,517 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,518 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-09-12 10:50:40,519 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,519 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:40,520 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:40,521 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:40,521 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 60\n", - "2024-09-12 10:50:40,522 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,523 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:40,524 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:40,524 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,525 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:40,526 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 68\n", - "2024-09-12 10:50:40,526 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,527 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:40,528 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,529 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-09-12 10:50:40,529 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,530 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-09-12 10:50:40,531 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:40,531 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:40,532 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,533 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:40,533 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 86\n", - "2024-09-12 10:50:40,534 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,535 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:40,535 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:40,536 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:40,537 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,537 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 94\n", - "2024-09-12 10:50:40,538 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,539 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:40,539 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,540 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 96\n", - "2024-09-12 10:50:40,541 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,541 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:40,542 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,543 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 98\n", - "2024-09-12 10:50:40,543 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,544 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:40,545 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:40,545 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,546 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:40,547 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 106\n", - "2024-09-12 10:50:40,547 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,548 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:40,549 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:40,549 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:40,550 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:40,550 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:40,551 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,552 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:40,553 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,553 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:40,554 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 132\n", - "2024-09-12 10:50:40,555 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,555 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:40,556 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-09-12 10:50:40,557 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,557 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 142\n", - "2024-09-12 10:50:40,558 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,559 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:40,559 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,560 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 146\n", - "2024-09-12 10:50:40,560 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,561 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:40,562 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:40,562 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,563 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:40,563 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 154\n", - "2024-09-12 10:50:40,564 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,565 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:40,565 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:40,567 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102compare_op.2': [],\n", - " '$104pred': [],\n", - " '$10pred': [],\n", - " '$110binary_add.2': [],\n", - " '$118load_deref.5': [],\n", - " '$124binary_subscr.8': [],\n", - " '$128call_function.10': [],\n", - " '$12load_global.0': [],\n", - " '$130pred': [],\n", - " '$150compare_op.2': [],\n", - " '$152pred': [],\n", - " '$156return_value.1': [],\n", - " '$20call_function.4': [],\n", - " '$22get_iter.5': [],\n", - " '$24for_iter.1': [],\n", - " '$24for_iter.2': [],\n", - " '$24for_iter.3': [],\n", - " '$28load_global.2': [],\n", - " '$2load_global.0': [],\n", - " '$30load_method.3': [],\n", - " '$38binary_subtract.7': [],\n", - " '$40binary_subscr.8': [],\n", - " '$42call_method.9': [],\n", - " '$44pred': [],\n", - " '$4load_method.1': [],\n", - " '$52return_value.2': [],\n", - " '$58return_value.1': [],\n", - " '$64compare_op.2': [],\n", - " '$66pred': [],\n", - " '$82compare_op.3': [],\n", - " '$84pred': [],\n", - " '$8call_method.3': [],\n", - " '$90binary_add.2': [],\n", - " '$const112.3': [],\n", - " '$const134.1': [],\n", - " '$const16.2': [],\n", - " '$const18.3': [],\n", - " '$const36.6': [],\n", - " '$const56.0': [],\n", - " '$const88.1': [],\n", - " '$phi24.0': [],\n", - " '$phi26.1': [],\n", - " '$phi96.0': [,\n", - " ],\n", - " 'a': [],\n", - " 'bool10': [],\n", - " 'bool104': [],\n", - " 'bool130': [],\n", - " 'bool152': [],\n", - " 'bool44': [],\n", - " 'bool66': [],\n", - " 'bool84': [],\n", - " 'hi': [,\n", - " ,\n", - " ,\n", - " ],\n", - " 'i': [],\n", - " 'lo': [,\n", - " ,\n", - " ],\n", - " 'mid': [],\n", - " 'n': [],\n", - " 'v': [],\n", - " 'v_last': []})\n", - "2024-09-12 10:50:40,568 - numba.core.ssa - DEBUG - SSA violators {'lo', 'hi', '$phi96.0'}\n", - "2024-09-12 10:50:40,569 - numba.core.ssa - DEBUG - Fix SSA violator on var lo\n", - "2024-09-12 10:50:40,570 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:40,570 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,571 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:40,572 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:40,572 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:40,573 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:40,574 - numba.core.ssa - DEBUG - first assign: lo\n", - "2024-09-12 10:50:40,574 - numba.core.ssa - DEBUG - replaced with: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:40,575 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:40,575 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:40,576 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:40,577 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:40,577 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,578 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:40,579 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,579 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:40,580 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:40,581 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,581 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:40,582 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:40,582 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:40,583 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,584 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:40,584 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:40,585 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,585 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:40,586 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,587 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:40,587 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,588 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,589 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:40,589 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:40,590 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:40,591 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,591 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:40,592 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:40,593 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:40,593 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:40,594 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:40,595 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:40,595 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,596 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:40,597 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,597 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:40,598 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:40,599 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,599 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:40,600 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:40,601 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:40,601 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,602 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,603 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:40,603 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,604 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:40,605 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:40,605 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:40,606 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:40,607 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,607 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:40,608 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:40,609 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,609 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:40,610 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:40,610 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,611 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:40,612 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,612 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:40,613 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,613 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-09-12 10:50:40,614 - numba.core.ssa - DEBUG - replaced with: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:40,615 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:40,615 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:40,616 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,617 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:40,617 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:40,618 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,618 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:40,619 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:40,620 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:40,620 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,621 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:40,622 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,622 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:40,623 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,624 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:40,624 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,625 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:40,626 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,626 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:40,627 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,627 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:40,628 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:40,629 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,629 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:40,630 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:40,630 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,631 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:40,631 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:40,632 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:40,633 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:40,633 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:40,634 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,637 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:40,638 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,639 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:40,640 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:40,641 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,641 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:40,642 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-09-12 10:50:40,643 - numba.core.ssa - DEBUG - replaced with: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:40,643 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,644 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:40,644 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,645 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:40,646 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,646 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:40,647 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,648 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:40,648 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:40,649 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,650 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:40,650 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:40,651 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,652 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:40,652 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:40,653 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 74: [],\n", - " 132: []})\n", - "2024-09-12 10:50:40,654 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:40,655 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,655 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:40,656 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:40,657 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:40,657 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:40,659 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:40,660 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:40,660 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:40,661 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:40,662 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,662 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:40,663 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,664 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:40,664 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:40,665 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,666 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:40,666 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:40,667 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:40,668 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,669 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:40,669 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:40,670 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,670 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:40,671 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,672 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:40,672 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,673 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,674 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:40,674 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:40,675 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:40,676 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,676 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:40,677 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:40,678 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:40,678 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:40,716 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:40,716 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:40,717 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,717 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:40,718 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,718 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:40,719 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:40,720 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,721 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:40,721 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:40,722 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:40,722 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,723 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,724 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:40,724 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,725 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:40,725 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:40,726 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:40,727 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:40,727 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,728 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:40,728 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:40,729 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,729 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:40,730 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:40,731 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,731 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:40,732 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,732 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:40,733 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,734 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:40,734 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:40,735 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:40,735 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,736 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:40,736 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:40,737 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,738 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:40,738 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:40,739 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:40,739 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,740 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:40,740 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,741 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:40,741 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,742 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:40,742 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,744 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:40,744 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,745 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:40,745 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,746 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:40,746 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:40,747 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-09-12 10:50:40,748 - numba.core.ssa - DEBUG - insert phi node lo.3 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-09-12 10:50:40,748 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:40,749 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:40,750 - numba.core.ssa - DEBUG - idom 74 from label 96\n", - "2024-09-12 10:50:40,750 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:40,751 - numba.core.ssa - DEBUG - incoming_def lo.1 = const(int, 0)\n", - "2024-09-12 10:50:40,751 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-09-12 10:50:40,752 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-09-12 10:50:40,753 - numba.core.ssa - DEBUG - idom 60 from label 68\n", - "2024-09-12 10:50:40,753 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:40,753 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:40,754 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-09-12 10:50:40,754 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:40,755 - numba.core.ssa - DEBUG - incoming_def lo = arg(3, name=lo)\n", - "2024-09-12 10:50:40,756 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:40,756 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:40,757 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,758 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:40,758 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:40,759 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,760 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:40,760 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:40,761 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-09-12 10:50:40,761 - numba.core.ssa - DEBUG - insert phi node lo.4 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-09-12 10:50:40,762 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-09-12 10:50:40,762 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:40,763 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-09-12 10:50:40,763 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-09-12 10:50:40,765 - numba.core.ssa - DEBUG - insert phi node lo.5 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-09-12 10:50:40,765 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-09-12 10:50:40,766 - numba.core.ssa - DEBUG - incoming_def lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:40,766 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-09-12 10:50:40,767 - numba.core.ssa - DEBUG - find_def_from_top label 142\n", - "2024-09-12 10:50:40,767 - numba.core.ssa - DEBUG - idom 106 from label 142\n", - "2024-09-12 10:50:40,768 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-09-12 10:50:40,768 - numba.core.ssa - DEBUG - incoming_def lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-09-12 10:50:40,769 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:40,770 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:40,771 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:40,771 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:40,772 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:40,773 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:40,773 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,774 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:40,774 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,775 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:40,776 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:40,776 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,777 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:40,777 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:40,778 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,779 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:40,779 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,780 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:40,781 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,781 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:40,782 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,782 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:40,783 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:40,784 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:40,784 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:40,785 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,785 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:40,786 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:40,787 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,787 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:40,788 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:40,788 - numba.core.ssa - DEBUG - find_def_from_top label 154\n", - "2024-09-12 10:50:40,789 - numba.core.ssa - DEBUG - insert phi node lo.6 = phi(incoming_values=[], incoming_blocks=[]) at 154\n", - "2024-09-12 10:50:40,789 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-09-12 10:50:40,789 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:40,790 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-09-12 10:50:40,790 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:40,791 - numba.core.ssa - DEBUG - replaced with: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:40,791 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:40,792 - numba.core.ssa - DEBUG - Fix SSA violator on var hi\n", - "2024-09-12 10:50:40,792 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:40,794 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,795 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:40,795 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:40,796 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:40,797 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:40,797 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:40,798 - numba.core.ssa - DEBUG - first assign: hi\n", - "2024-09-12 10:50:40,798 - numba.core.ssa - DEBUG - replaced with: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:40,799 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:40,799 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:40,799 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:40,800 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,801 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:40,802 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,802 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:40,803 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:40,804 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,804 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:40,805 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:40,805 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:40,806 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,807 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:40,807 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:40,808 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,808 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:40,809 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,809 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:40,810 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,811 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,811 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:40,812 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:40,813 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:40,813 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,814 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:40,814 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:40,814 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:40,815 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:40,815 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:40,816 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:40,817 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,818 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:40,818 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,819 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:40,820 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:40,820 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,821 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:40,821 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:40,821 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:40,823 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,823 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,824 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:40,824 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,825 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:40,825 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:40,826 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:40,827 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:40,827 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,827 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:40,828 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:40,828 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,829 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:40,829 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:40,830 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,830 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:40,831 - numba.core.ssa - DEBUG - replaced with: hi.1 = n\n", - "2024-09-12 10:50:40,831 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,832 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:40,832 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,834 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:40,835 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:40,835 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:40,836 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,836 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:40,837 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:40,838 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,838 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:40,839 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:40,839 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:40,840 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,841 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:40,841 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,842 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:40,842 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,843 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:40,843 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,844 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:40,844 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0\n", - "2024-09-12 10:50:40,844 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,845 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:40,846 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,847 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:40,847 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:40,848 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:40,849 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,849 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:40,850 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:40,850 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,851 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:40,852 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:40,852 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:40,853 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:40,853 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:40,854 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:40,855 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,855 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:40,856 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,857 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:40,857 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:40,858 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,858 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:40,859 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:40,859 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,860 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:40,860 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,860 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:40,861 - numba.core.ssa - DEBUG - replaced with: hi.3 = mid\n", - "2024-09-12 10:50:40,861 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,862 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:40,863 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,864 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:40,864 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:40,865 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:40,866 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,866 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:40,867 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:40,867 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,868 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:40,869 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:40,869 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:40,871 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 68: [],\n", - " 96: [],\n", - " 142: []})\n", - "2024-09-12 10:50:40,872 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:40,873 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,873 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:40,874 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:40,874 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:40,875 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:40,876 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:40,877 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:40,877 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:40,878 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:40,878 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,879 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:40,880 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,880 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:40,881 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:40,882 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,882 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:40,883 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:40,883 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:40,884 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,884 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:40,885 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:40,886 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,886 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:40,887 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,887 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:40,888 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,889 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,889 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:40,889 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:40,890 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:40,891 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,891 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:40,892 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:40,893 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:40,893 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:40,894 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:40,895 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:40,895 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,896 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:40,896 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,897 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:40,898 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:40,898 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,899 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:40,899 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:40,900 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:40,900 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,901 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,901 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:40,902 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,903 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:40,903 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:40,904 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:40,904 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:40,905 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,905 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:40,906 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:40,907 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,907 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:40,908 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:40,908 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,909 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-09-12 10:50:40,910 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,910 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:40,911 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,911 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:40,912 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:40,912 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$82compare_op.3 = hi < n\n", - "2024-09-12 10:50:40,913 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-09-12 10:50:40,914 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-09-12 10:50:40,914 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:40,915 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:40,915 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-09-12 10:50:40,916 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:40,916 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:40,917 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,917 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:40,918 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:40,918 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,919 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:40,919 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:40,919 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:40,921 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-09-12 10:50:40,922 - numba.core.ssa - DEBUG - idom 74 from label 86\n", - "2024-09-12 10:50:40,922 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:40,923 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-09-12 10:50:40,923 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-09-12 10:50:40,924 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:40,924 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:40,925 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-09-12 10:50:40,926 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:40,926 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:40,927 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,928 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:40,928 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,929 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:40,929 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:40,929 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:40,931 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,931 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-09-12 10:50:40,931 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:40,932 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:40,933 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,933 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:40,934 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:40,934 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:40,935 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-09-12 10:50:40,936 - numba.core.ssa - DEBUG - insert phi node hi.4 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-09-12 10:50:40,936 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:40,937 - numba.core.ssa - DEBUG - incoming_def hi.2 = $phi96.0\n", - "2024-09-12 10:50:40,937 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-09-12 10:50:40,938 - numba.core.ssa - DEBUG - incoming_def hi.1 = n\n", - "2024-09-12 10:50:40,939 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi.4 > lo.3\n", - "2024-09-12 10:50:40,939 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:40,940 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,941 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:40,941 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:40,942 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,942 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:40,943 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:40,943 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:40,945 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-09-12 10:50:40,945 - numba.core.ssa - DEBUG - insert phi node hi.5 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-09-12 10:50:40,946 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-09-12 10:50:40,946 - numba.core.ssa - DEBUG - incoming_def hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:40,947 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-09-12 10:50:40,947 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-09-12 10:50:40,948 - numba.core.ssa - DEBUG - insert phi node hi.6 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-09-12 10:50:40,948 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-09-12 10:50:40,949 - numba.core.ssa - DEBUG - find_def_from_top label 132\n", - "2024-09-12 10:50:40,949 - numba.core.ssa - DEBUG - idom 106 from label 132\n", - "2024-09-12 10:50:40,950 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-09-12 10:50:40,951 - numba.core.ssa - DEBUG - incoming_def hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-09-12 10:50:40,951 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-09-12 10:50:40,952 - numba.core.ssa - DEBUG - incoming_def hi.3 = mid\n", - "2024-09-12 10:50:40,952 - numba.core.ssa - DEBUG - incoming_def hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:40,953 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi.5\n", - "2024-09-12 10:50:40,953 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:40,955 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:40,955 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:40,956 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:40,956 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,957 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:40,957 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,957 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:40,959 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:40,959 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,960 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:40,960 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:40,961 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,962 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:40,962 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,963 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-09-12 10:50:40,963 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:40,964 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:40,964 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,965 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:40,966 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:40,966 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:40,967 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi.6 > lo.5\n", - "2024-09-12 10:50:40,967 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:40,968 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,969 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:40,969 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:40,970 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,970 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:40,971 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:40,971 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:40,972 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi96.0\n", - "2024-09-12 10:50:40,972 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:40,973 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,974 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:40,975 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:40,975 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:40,975 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:40,976 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:40,976 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:40,977 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:40,978 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:40,979 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,979 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:40,980 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,981 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:40,981 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:40,981 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,982 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:40,982 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:40,983 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:40,984 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,985 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:40,985 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:40,986 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:40,986 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:40,987 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,988 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:40,988 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,989 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:40,990 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:40,990 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:40,991 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:40,991 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,992 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:40,993 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:40,993 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:40,994 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:40,994 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:40,995 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:40,996 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,996 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:40,997 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:40,997 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:40,998 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:40,999 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:40,999 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:41,000 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:41,001 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:41,001 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,002 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:41,002 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:41,003 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,003 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:41,004 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:41,004 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:41,004 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:41,005 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,005 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:41,007 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:41,007 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,008 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:41,008 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:41,009 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,009 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-09-12 10:50:41,010 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,010 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:41,011 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,011 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:41,013 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:41,013 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:41,014 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,014 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:41,015 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:41,016 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,016 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:41,017 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:41,017 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:41,018 - numba.core.ssa - DEBUG - first assign: $phi96.0\n", - "2024-09-12 10:50:41,019 - numba.core.ssa - DEBUG - replaced with: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:41,019 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,019 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:41,020 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,021 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:41,021 - numba.core.ssa - DEBUG - replaced with: $phi96.0.1 = n\n", - "2024-09-12 10:50:41,022 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,022 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:41,023 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,023 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-09-12 10:50:41,024 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,024 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:41,026 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,026 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:41,026 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:41,027 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-09-12 10:50:41,028 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:41,028 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,029 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:41,029 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:41,030 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,030 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:41,031 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:41,031 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-09-12 10:50:41,033 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:41,033 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:41,034 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:41,034 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:41,035 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,036 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:41,036 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,037 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:41,037 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:41,038 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,038 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:41,039 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:41,039 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:41,040 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:41,040 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,041 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-09-12 10:50:41,041 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:41,042 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:41,042 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,044 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:41,044 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:41,045 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-09-12 10:50:41,045 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:41,046 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,047 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:41,047 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:41,048 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,049 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:41,049 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:41,050 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:41,050 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {86: [],\n", - " 94: []})\n", - "2024-09-12 10:50:41,051 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:41,051 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,052 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:41,053 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:41,053 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:41,054 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:41,054 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:41,055 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:41,055 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:41,056 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:41,057 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,057 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:41,058 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,058 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:41,059 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:41,060 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,060 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:41,061 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:41,061 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:41,062 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,063 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:41,063 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:41,064 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:41,064 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:41,065 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,065 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:41,066 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:41,067 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:41,067 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:41,068 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:41,069 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:41,069 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,070 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:41,070 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:41,071 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:41,072 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:41,072 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:41,073 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:41,073 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,074 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:41,075 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,075 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:41,076 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:41,076 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,077 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:41,078 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:41,078 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:41,079 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,079 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:41,080 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:41,080 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,080 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:41,081 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:41,081 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:41,083 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:41,083 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,084 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:41,084 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:41,085 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,086 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:41,086 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:41,087 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,087 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-09-12 10:50:41,087 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,088 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:41,088 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,090 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:41,090 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:41,091 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:41,091 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,092 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:41,093 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:41,093 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,094 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:41,094 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:41,095 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:41,095 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,096 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:41,096 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,097 - numba.core.ssa - DEBUG - on stmt: $phi96.0.1 = n\n", - "2024-09-12 10:50:41,098 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,099 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:41,099 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,099 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-09-12 10:50:41,100 - numba.core.ssa - DEBUG - find_def var='$phi96.0' stmt=hi.2 = $phi96.0\n", - "2024-09-12 10:50:41,101 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:41,101 - numba.core.ssa - DEBUG - insert phi node $phi96.0.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:41,102 - numba.core.ssa - DEBUG - find_def_from_bottom label 94\n", - "2024-09-12 10:50:41,103 - numba.core.ssa - DEBUG - incoming_def $phi96.0.1 = n\n", - "2024-09-12 10:50:41,103 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-09-12 10:50:41,104 - numba.core.ssa - DEBUG - incoming_def $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:41,105 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0.2\n", - "2024-09-12 10:50:41,105 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,106 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:41,106 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,107 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:41,108 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:41,109 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-09-12 10:50:41,109 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:41,110 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,110 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:41,111 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:41,111 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,112 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:41,112 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:41,113 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-09-12 10:50:41,114 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:41,114 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:41,115 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:41,116 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:41,116 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,117 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:41,117 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,118 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:41,119 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:41,119 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,120 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:41,121 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:41,121 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:41,122 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:41,122 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,123 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-09-12 10:50:41,123 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:41,124 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:41,125 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,125 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:41,126 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:41,126 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-09-12 10:50:41,127 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:41,128 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,128 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:41,129 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:41,129 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,130 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:41,131 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:41,131 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:41,167 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=1049)\n", - " 2\tLOAD_FAST(arg=0, lineno=1051)\n", - " 4\tLOAD_FAST(arg=1, lineno=1051)\n", - " 6\tCOMPARE_OP(arg=0, lineno=1051)\n", - " 8\tRETURN_VALUE(arg=None, lineno=1051)\n", - "2024-09-12 10:50:41,168 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:41,169 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,170 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:41,171 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=1049)\n", - "2024-09-12 10:50:41,171 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,172 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_FAST(arg=0, lineno=1051)\n", - "2024-09-12 10:50:41,172 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,173 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=1, lineno=1051)\n", - "2024-09-12 10:50:41,174 - numba.core.byteflow - DEBUG - stack ['$a2.0']\n", - "2024-09-12 10:50:41,174 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=COMPARE_OP(arg=0, lineno=1051)\n", - "2024-09-12 10:50:41,175 - numba.core.byteflow - DEBUG - stack ['$a2.0', '$b4.1']\n", - "2024-09-12 10:50:41,176 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=RETURN_VALUE(arg=None, lineno=1051)\n", - "2024-09-12 10:50:41,176 - numba.core.byteflow - DEBUG - stack ['$6compare_op.2']\n", - "2024-09-12 10:50:41,177 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:41,177 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:41,178 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:41,179 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:41,180 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:41,180 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:41,181 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:41,181 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:41,182 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:41,183 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$a2.0'}), (4, {'res': '$b4.1'}), (6, {'lhs': '$a2.0', 'rhs': '$b4.1', 'res': '$6compare_op.2'}), (8, {'retval': '$6compare_op.2', 'castval': '$8return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:41,184 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " b = arg(1, name=b) ['b']\n", - " $6compare_op.2 = a < b ['$6compare_op.2', 'a', 'b']\n", - " $8return_value.3 = cast(value=$6compare_op.2) ['$6compare_op.2', '$8return_value.3']\n", - " return $8return_value.3 ['$8return_value.3']\n", - "\n", - "2024-09-12 10:50:41,201 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:41,203 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,204 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:41,204 - numba.core.ssa - DEBUG - on stmt: b = arg(1, name=b)\n", - "2024-09-12 10:50:41,205 - numba.core.ssa - DEBUG - on stmt: $6compare_op.2 = a < b\n", - "2024-09-12 10:50:41,206 - numba.core.ssa - DEBUG - on stmt: $8return_value.3 = cast(value=$6compare_op.2)\n", - "2024-09-12 10:50:41,206 - numba.core.ssa - DEBUG - on stmt: return $8return_value.3\n", - "2024-09-12 10:50:41,207 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$6compare_op.2': [],\n", - " '$8return_value.3': [],\n", - " 'a': [],\n", - " 'b': []})\n", - "2024-09-12 10:50:41,208 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:41,400 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3773)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3774)\n", - " 4\tLOAD_FAST(arg=0, lineno=3774)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=3774)\n", - " 8\tSTORE_FAST(arg=3, lineno=3774)\n", - " 10\tLOAD_DEREF(arg=0, lineno=3775)\n", - " 12\tLOAD_FAST(arg=0, lineno=3775)\n", - " 14\tLOAD_FAST(arg=1, lineno=3775)\n", - " 16\tLOAD_FAST(arg=1, lineno=3775)\n", - " 18\tLOAD_CONST(arg=1, lineno=3775)\n", - " 20\tLOAD_FAST(arg=3, lineno=3775)\n", - " 22\tLOAD_FAST(arg=3, lineno=3775)\n", - " 24\tCALL_FUNCTION(arg=6, lineno=3775)\n", - " 26\tRETURN_VALUE(arg=None, lineno=3775)\n", - "2024-09-12 10:50:41,401 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:41,401 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,402 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:41,403 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3773)\n", - "2024-09-12 10:50:41,403 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,404 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3774)\n", - "2024-09-12 10:50:41,405 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,405 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=3774)\n", - "2024-09-12 10:50:41,406 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:41,407 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=3774)\n", - "2024-09-12 10:50:41,407 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$a4.1']\n", - "2024-09-12 10:50:41,408 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=3, lineno=3774)\n", - "2024-09-12 10:50:41,409 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-09-12 10:50:41,409 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_DEREF(arg=0, lineno=3775)\n", - "2024-09-12 10:50:41,410 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,410 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=0, lineno=3775)\n", - "2024-09-12 10:50:41,411 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3']\n", - "2024-09-12 10:50:41,412 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:41,412 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4']\n", - "2024-09-12 10:50:41,413 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:41,413 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5']\n", - "2024-09-12 10:50:41,414 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:41,415 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6']\n", - "2024-09-12 10:50:41,415 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-09-12 10:50:41,416 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7']\n", - "2024-09-12 10:50:41,416 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-09-12 10:50:41,417 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8']\n", - "2024-09-12 10:50:41,418 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=CALL_FUNCTION(arg=6, lineno=3775)\n", - "2024-09-12 10:50:41,418 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9']\n", - "2024-09-12 10:50:41,419 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=RETURN_VALUE(arg=None, lineno=3775)\n", - "2024-09-12 10:50:41,419 - numba.core.byteflow - DEBUG - stack ['$24call_function.10']\n", - "2024-09-12 10:50:41,420 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:41,421 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:41,421 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:41,422 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:41,422 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:41,423 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:41,424 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:41,424 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:41,425 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:41,425 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$a4.1'}), (6, {'func': '$2load_global.0', 'args': ['$a4.1'], 'res': '$6call_function.2'}), (8, {'value': '$6call_function.2'}), (10, {'res': '$10load_deref.3'}), (12, {'res': '$a12.4'}), (14, {'res': '$v14.5'}), (16, {'res': '$v16.6'}), (18, {'res': '$const18.7'}), (20, {'res': '$n20.8'}), (22, {'res': '$n22.9'}), (24, {'func': '$10load_deref.3', 'args': ['$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9'], 'res': '$24call_function.10'}), (26, {'retval': '$24call_function.10', 'castval': '$26return_value.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:41,427 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " side = arg(2, name=side) ['side']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'a', 'n']\n", - " $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f2dc32ed090>) ['$10load_deref.3']\n", - " $const18.7 = const(int, 0) ['$const18.7']\n", - " $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_deref.3', '$24call_function.10', '$const18.7', 'a', 'n', 'n', 'v', 'v']\n", - " $26return_value.11 = cast(value=$24call_function.10) ['$24call_function.10', '$26return_value.11']\n", - " return $26return_value.11 ['$26return_value.11']\n", - "\n", - "2024-09-12 10:50:41,438 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:41,439 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,439 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:41,440 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:41,441 - numba.core.ssa - DEBUG - on stmt: side = arg(2, name=side)\n", - "2024-09-12 10:50:41,441 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-09-12 10:50:41,442 - numba.core.ssa - DEBUG - on stmt: n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,443 - numba.core.ssa - DEBUG - on stmt: $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f2dc32ed090>)\n", - "2024-09-12 10:50:41,444 - numba.core.ssa - DEBUG - on stmt: $const18.7 = const(int, 0)\n", - "2024-09-12 10:50:41,444 - numba.core.ssa - DEBUG - on stmt: $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,445 - numba.core.ssa - DEBUG - on stmt: $26return_value.11 = cast(value=$24call_function.10)\n", - "2024-09-12 10:50:41,446 - numba.core.ssa - DEBUG - on stmt: return $26return_value.11\n", - "2024-09-12 10:50:41,447 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_deref.3': [],\n", - " '$24call_function.10': [],\n", - " '$26return_value.11': [],\n", - " '$2load_global.0': [],\n", - " '$const18.7': [],\n", - " 'a': [],\n", - " 'n': [],\n", - " 'side': [],\n", - " 'v': []})\n", - "2024-09-12 10:50:41,448 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:41,452 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3678)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3701)\n", - " 4\tLOAD_METHOD(arg=1, lineno=3701)\n", - " 6\tLOAD_FAST(arg=1, lineno=3701)\n", - " 8\tCALL_METHOD(arg=1, lineno=3701)\n", - " 10\tPOP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - " 12\tLOAD_GLOBAL(arg=2, lineno=3704)\n", - " 14\tLOAD_FAST(arg=5, lineno=3704)\n", - " 16\tLOAD_CONST(arg=1, lineno=3704)\n", - " 18\tLOAD_CONST(arg=2, lineno=3704)\n", - " 20\tCALL_FUNCTION(arg=3, lineno=3704)\n", - " 22\tGET_ITER(arg=None, lineno=3704)\n", - "> 24\tFOR_ITER(arg=15, lineno=3704)\n", - " 26\tSTORE_FAST(arg=6, lineno=3704)\n", - " 28\tLOAD_GLOBAL(arg=0, lineno=3705)\n", - " 30\tLOAD_METHOD(arg=1, lineno=3705)\n", - " 32\tLOAD_FAST(arg=0, lineno=3705)\n", - " 34\tLOAD_FAST(arg=6, lineno=3705)\n", - " 36\tLOAD_CONST(arg=3, lineno=3705)\n", - " 38\tBINARY_SUBTRACT(arg=None, lineno=3705)\n", - " 40\tBINARY_SUBSCR(arg=None, lineno=3705)\n", - " 42\tCALL_METHOD(arg=1, lineno=3705)\n", - " 44\tPOP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - " 46\tLOAD_FAST(arg=6, lineno=3706)\n", - " 48\tROT_TWO(arg=None, lineno=3706)\n", - " 50\tPOP_TOP(arg=None, lineno=3706)\n", - " 52\tRETURN_VALUE(arg=None, lineno=3706)\n", - "> 54\tJUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "> 56\tLOAD_CONST(arg=1, lineno=3707)\n", - " 58\tRETURN_VALUE(arg=None, lineno=3707)\n", - "> 60\tLOAD_FAST(arg=2, lineno=3709)\n", - " 62\tLOAD_FAST(arg=1, lineno=3709)\n", - " 64\tCOMPARE_OP(arg=0, lineno=3709)\n", - " 66\tPOP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - " 68\tLOAD_FAST(arg=5, lineno=3710)\n", - " 70\tSTORE_FAST(arg=4, lineno=3710)\n", - " 72\tJUMP_FORWARD(arg=12, lineno=3710)\n", - "> 74\tLOAD_CONST(arg=1, lineno=3712)\n", - " 76\tSTORE_FAST(arg=3, lineno=3712)\n", - " 78\tLOAD_FAST(arg=4, lineno=3713)\n", - " 80\tLOAD_FAST(arg=5, lineno=3713)\n", - " 82\tCOMPARE_OP(arg=0, lineno=3713)\n", - " 84\tPOP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - " 86\tLOAD_FAST(arg=4, lineno=3713)\n", - " 88\tLOAD_CONST(arg=3, lineno=3713)\n", - " 90\tBINARY_ADD(arg=None, lineno=3713)\n", - " 92\tJUMP_FORWARD(arg=1, lineno=3713)\n", - "> 94\tLOAD_FAST(arg=5, lineno=3713)\n", - "> 96\tSTORE_FAST(arg=4, lineno=3713)\n", - "> 98\tLOAD_FAST(arg=4, lineno=3715)\n", - " 100\tLOAD_FAST(arg=3, lineno=3715)\n", - " 102\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 104\tPOP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "> 106\tLOAD_FAST(arg=3, lineno=3716)\n", - " 108\tLOAD_FAST(arg=4, lineno=3716)\n", - " 110\tBINARY_ADD(arg=None, lineno=3716)\n", - " 112\tLOAD_CONST(arg=3, lineno=3716)\n", - " 114\tBINARY_RSHIFT(arg=None, lineno=3716)\n", - " 116\tSTORE_FAST(arg=7, lineno=3716)\n", - " 118\tLOAD_DEREF(arg=0, lineno=3717)\n", - " 120\tLOAD_FAST(arg=0, lineno=3717)\n", - " 122\tLOAD_FAST(arg=7, lineno=3717)\n", - " 124\tBINARY_SUBSCR(arg=None, lineno=3717)\n", - " 126\tLOAD_FAST(arg=1, lineno=3717)\n", - " 128\tCALL_FUNCTION(arg=2, lineno=3717)\n", - " 130\tPOP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - " 132\tLOAD_FAST(arg=7, lineno=3719)\n", - " 134\tLOAD_CONST(arg=3, lineno=3719)\n", - " 136\tBINARY_ADD(arg=None, lineno=3719)\n", - " 138\tSTORE_FAST(arg=3, lineno=3719)\n", - " 140\tJUMP_FORWARD(arg=2, lineno=3719)\n", - "> 142\tLOAD_FAST(arg=7, lineno=3722)\n", - " 144\tSTORE_FAST(arg=4, lineno=3722)\n", - "> 146\tLOAD_FAST(arg=4, lineno=3715)\n", - " 148\tLOAD_FAST(arg=3, lineno=3715)\n", - " 150\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 152\tPOP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "> 154\tLOAD_FAST(arg=3, lineno=3723)\n", - " 156\tRETURN_VALUE(arg=None, lineno=3723)\n", - "2024-09-12 10:50:41,453 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:41,454 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,455 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:41,456 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3678)\n", - "2024-09-12 10:50:41,456 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,457 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3701)\n", - "2024-09-12 10:50:41,458 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,459 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=1, lineno=3701)\n", - "2024-09-12 10:50:41,459 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:41,460 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=3701)\n", - "2024-09-12 10:50:41,461 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-09-12 10:50:41,462 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_METHOD(arg=1, lineno=3701)\n", - "2024-09-12 10:50:41,462 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$v6.2']\n", - "2024-09-12 10:50:41,463 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=POP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - "2024-09-12 10:50:41,464 - numba.core.byteflow - DEBUG - stack ['$8call_method.3']\n", - "2024-09-12 10:50:41,465 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=12, stack=(), blockstack=(), npush=0), Edge(pc=60, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,465 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=12 nstack_initial=0), State(pc_initial=60 nstack_initial=0)])\n", - "2024-09-12 10:50:41,466 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,467 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=12 nstack_initial=0)\n", - "2024-09-12 10:50:41,468 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_GLOBAL(arg=2, lineno=3704)\n", - "2024-09-12 10:50:41,468 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,469 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=5, lineno=3704)\n", - "2024-09-12 10:50:41,470 - numba.core.byteflow - DEBUG - stack ['$12load_global.0']\n", - "2024-09-12 10:50:41,471 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_CONST(arg=1, lineno=3704)\n", - "2024-09-12 10:50:41,474 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1']\n", - "2024-09-12 10:50:41,474 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=2, lineno=3704)\n", - "2024-09-12 10:50:41,475 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2']\n", - "2024-09-12 10:50:41,476 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=CALL_FUNCTION(arg=3, lineno=3704)\n", - "2024-09-12 10:50:41,477 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2', '$const18.3']\n", - "2024-09-12 10:50:41,477 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=GET_ITER(arg=None, lineno=3704)\n", - "2024-09-12 10:50:41,478 - numba.core.byteflow - DEBUG - stack ['$20call_function.4']\n", - "2024-09-12 10:50:41,479 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$22get_iter.5',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,480 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=0), State(pc_initial=24 nstack_initial=1)])\n", - "2024-09-12 10:50:41,481 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,481 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=60 nstack_initial=0)\n", - "2024-09-12 10:50:41,482 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_FAST(arg=2, lineno=3709)\n", - "2024-09-12 10:50:41,483 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,484 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_FAST(arg=1, lineno=3709)\n", - "2024-09-12 10:50:41,485 - numba.core.byteflow - DEBUG - stack ['$v_last60.0']\n", - "2024-09-12 10:50:41,485 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=COMPARE_OP(arg=0, lineno=3709)\n", - "2024-09-12 10:50:41,486 - numba.core.byteflow - DEBUG - stack ['$v_last60.0', '$v62.1']\n", - "2024-09-12 10:50:41,487 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=POP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - "2024-09-12 10:50:41,488 - numba.core.byteflow - DEBUG - stack ['$64compare_op.2']\n", - "2024-09-12 10:50:41,488 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=68, stack=(), blockstack=(), npush=0), Edge(pc=74, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,489 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0)])\n", - "2024-09-12 10:50:41,490 - numba.core.byteflow - DEBUG - stack: ['$phi24.0']\n", - "2024-09-12 10:50:41,491 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=24 nstack_initial=1)\n", - "2024-09-12 10:50:41,492 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=FOR_ITER(arg=15, lineno=3704)\n", - "2024-09-12 10:50:41,492 - numba.core.byteflow - DEBUG - stack ['$phi24.0']\n", - "2024-09-12 10:50:41,493 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=56, stack=(), blockstack=(), npush=0), Edge(pc=26, stack=('$phi24.0', '$24for_iter.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,494 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2)])\n", - "2024-09-12 10:50:41,495 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,496 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=68 nstack_initial=0)\n", - "2024-09-12 10:50:41,496 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_FAST(arg=5, lineno=3710)\n", - "2024-09-12 10:50:41,497 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,498 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=STORE_FAST(arg=4, lineno=3710)\n", - "2024-09-12 10:50:41,499 - numba.core.byteflow - DEBUG - stack ['$n68.0']\n", - "2024-09-12 10:50:41,499 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=JUMP_FORWARD(arg=12, lineno=3710)\n", - "2024-09-12 10:50:41,500 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,501 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,502 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:41,503 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,503 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=0)\n", - "2024-09-12 10:50:41,504 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=1, lineno=3712)\n", - "2024-09-12 10:50:41,505 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,506 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=STORE_FAST(arg=3, lineno=3712)\n", - "2024-09-12 10:50:41,507 - numba.core.byteflow - DEBUG - stack ['$const74.0']\n", - "2024-09-12 10:50:41,507 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-09-12 10:50:41,508 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,509 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-09-12 10:50:41,510 - numba.core.byteflow - DEBUG - stack ['$hi78.1']\n", - "2024-09-12 10:50:41,510 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=COMPARE_OP(arg=0, lineno=3713)\n", - "2024-09-12 10:50:41,511 - numba.core.byteflow - DEBUG - stack ['$hi78.1', '$n80.2']\n", - "2024-09-12 10:50:41,512 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=POP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - "2024-09-12 10:50:41,513 - numba.core.byteflow - DEBUG - stack ['$82compare_op.3']\n", - "2024-09-12 10:50:41,513 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=86, stack=(), blockstack=(), npush=0), Edge(pc=94, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,514 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-09-12 10:50:41,515 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,516 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=0)\n", - "2024-09-12 10:50:41,516 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_CONST(arg=1, lineno=3707)\n", - "2024-09-12 10:50:41,517 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,518 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=RETURN_VALUE(arg=None, lineno=3707)\n", - "2024-09-12 10:50:41,519 - numba.core.byteflow - DEBUG - stack ['$const56.0']\n", - "2024-09-12 10:50:41,520 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:41,520 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-09-12 10:50:41,521 - numba.core.byteflow - DEBUG - stack: ['$phi26.0', '$phi26.1']\n", - "2024-09-12 10:50:41,522 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=26 nstack_initial=2)\n", - "2024-09-12 10:50:41,523 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=STORE_FAST(arg=6, lineno=3704)\n", - "2024-09-12 10:50:41,523 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$phi26.1']\n", - "2024-09-12 10:50:41,524 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_GLOBAL(arg=0, lineno=3705)\n", - "2024-09-12 10:50:41,525 - numba.core.byteflow - DEBUG - stack ['$phi26.0']\n", - "2024-09-12 10:50:41,526 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_METHOD(arg=1, lineno=3705)\n", - "2024-09-12 10:50:41,526 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$28load_global.2']\n", - "2024-09-12 10:50:41,527 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_FAST(arg=0, lineno=3705)\n", - "2024-09-12 10:50:41,528 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3']\n", - "2024-09-12 10:50:41,529 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=6, lineno=3705)\n", - "2024-09-12 10:50:41,529 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4']\n", - "2024-09-12 10:50:41,530 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_CONST(arg=3, lineno=3705)\n", - "2024-09-12 10:50:41,531 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5']\n", - "2024-09-12 10:50:41,532 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=BINARY_SUBTRACT(arg=None, lineno=3705)\n", - "2024-09-12 10:50:41,533 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5', '$const36.6']\n", - "2024-09-12 10:50:41,533 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=BINARY_SUBSCR(arg=None, lineno=3705)\n", - "2024-09-12 10:50:41,534 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$38binary_subtract.7']\n", - "2024-09-12 10:50:41,535 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=CALL_METHOD(arg=1, lineno=3705)\n", - "2024-09-12 10:50:41,536 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$40binary_subscr.8']\n", - "2024-09-12 10:50:41,536 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - "2024-09-12 10:50:41,537 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$42call_method.9']\n", - "2024-09-12 10:50:41,538 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=('$phi26.0',), blockstack=(), npush=0), Edge(pc=54, stack=('$phi26.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,539 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1)])\n", - "2024-09-12 10:50:41,540 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,540 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=98 nstack_initial=0)\n", - "2024-09-12 10:50:41,541 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-09-12 10:50:41,542 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,543 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-09-12 10:50:41,543 - numba.core.byteflow - DEBUG - stack ['$hi98.0']\n", - "2024-09-12 10:50:41,544 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-09-12 10:50:41,545 - numba.core.byteflow - DEBUG - stack ['$hi98.0', '$lo100.1']\n", - "2024-09-12 10:50:41,546 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=POP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "2024-09-12 10:50:41,546 - numba.core.byteflow - DEBUG - stack ['$102compare_op.2']\n", - "2024-09-12 10:50:41,547 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=106, stack=(), blockstack=(), npush=0), Edge(pc=154, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,548 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0)])\n", - "2024-09-12 10:50:41,549 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,549 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=86 nstack_initial=0)\n", - "2024-09-12 10:50:41,550 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-09-12 10:50:41,551 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,551 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_CONST(arg=3, lineno=3713)\n", - "2024-09-12 10:50:41,552 - numba.core.byteflow - DEBUG - stack ['$hi86.0']\n", - "2024-09-12 10:50:41,553 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=BINARY_ADD(arg=None, lineno=3713)\n", - "2024-09-12 10:50:41,554 - numba.core.byteflow - DEBUG - stack ['$hi86.0', '$const88.1']\n", - "2024-09-12 10:50:41,554 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=JUMP_FORWARD(arg=1, lineno=3713)\n", - "2024-09-12 10:50:41,555 - numba.core.byteflow - DEBUG - stack ['$90binary_add.2']\n", - "2024-09-12 10:50:41,556 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$90binary_add.2',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,557 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1)])\n", - "2024-09-12 10:50:41,557 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,558 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=94 nstack_initial=0)\n", - "2024-09-12 10:50:41,559 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-09-12 10:50:41,559 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,560 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$n94.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,561 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-09-12 10:50:41,562 - numba.core.byteflow - DEBUG - stack: ['$phi46.0']\n", - "2024-09-12 10:50:41,562 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=1)\n", - "2024-09-12 10:50:41,563 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=6, lineno=3706)\n", - "2024-09-12 10:50:41,564 - numba.core.byteflow - DEBUG - stack ['$phi46.0']\n", - "2024-09-12 10:50:41,565 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=ROT_TWO(arg=None, lineno=3706)\n", - "2024-09-12 10:50:41,565 - numba.core.byteflow - DEBUG - stack ['$phi46.0', '$i46.1']\n", - "2024-09-12 10:50:41,566 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=POP_TOP(arg=None, lineno=3706)\n", - "2024-09-12 10:50:41,567 - numba.core.byteflow - DEBUG - stack ['$i46.1', '$phi46.0']\n", - "2024-09-12 10:50:41,567 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=RETURN_VALUE(arg=None, lineno=3706)\n", - "2024-09-12 10:50:41,568 - numba.core.byteflow - DEBUG - stack ['$i46.1']\n", - "2024-09-12 10:50:41,569 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:41,569 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-09-12 10:50:41,570 - numba.core.byteflow - DEBUG - stack: ['$phi54.0']\n", - "2024-09-12 10:50:41,571 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=1)\n", - "2024-09-12 10:50:41,571 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=JUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "2024-09-12 10:50:41,572 - numba.core.byteflow - DEBUG - stack ['$phi54.0']\n", - "2024-09-12 10:50:41,573 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$phi54.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,574 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1)])\n", - "2024-09-12 10:50:41,574 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,575 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=106 nstack_initial=0)\n", - "2024-09-12 10:50:41,576 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_FAST(arg=3, lineno=3716)\n", - "2024-09-12 10:50:41,576 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,577 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_FAST(arg=4, lineno=3716)\n", - "2024-09-12 10:50:41,578 - numba.core.byteflow - DEBUG - stack ['$lo106.0']\n", - "2024-09-12 10:50:41,578 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=BINARY_ADD(arg=None, lineno=3716)\n", - "2024-09-12 10:50:41,579 - numba.core.byteflow - DEBUG - stack ['$lo106.0', '$hi108.1']\n", - "2024-09-12 10:50:41,580 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=3, lineno=3716)\n", - "2024-09-12 10:50:41,580 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2']\n", - "2024-09-12 10:50:41,581 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BINARY_RSHIFT(arg=None, lineno=3716)\n", - "2024-09-12 10:50:41,582 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2', '$const112.3']\n", - "2024-09-12 10:50:41,583 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=STORE_FAST(arg=7, lineno=3716)\n", - "2024-09-12 10:50:41,583 - numba.core.byteflow - DEBUG - stack ['$114binary_rshift.4']\n", - "2024-09-12 10:50:41,584 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_DEREF(arg=0, lineno=3717)\n", - "2024-09-12 10:50:41,585 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,585 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=0, lineno=3717)\n", - "2024-09-12 10:50:41,586 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5']\n", - "2024-09-12 10:50:41,587 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_FAST(arg=7, lineno=3717)\n", - "2024-09-12 10:50:41,587 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6']\n", - "2024-09-12 10:50:41,588 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=BINARY_SUBSCR(arg=None, lineno=3717)\n", - "2024-09-12 10:50:41,589 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6', '$mid122.7']\n", - "2024-09-12 10:50:41,590 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_FAST(arg=1, lineno=3717)\n", - "2024-09-12 10:50:41,590 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8']\n", - "2024-09-12 10:50:41,591 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=CALL_FUNCTION(arg=2, lineno=3717)\n", - "2024-09-12 10:50:41,592 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8', '$v126.9']\n", - "2024-09-12 10:50:41,593 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=POP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - "2024-09-12 10:50:41,593 - numba.core.byteflow - DEBUG - stack ['$128call_function.10']\n", - "2024-09-12 10:50:41,594 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=132, stack=(), blockstack=(), npush=0), Edge(pc=142, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,595 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-09-12 10:50:41,595 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,596 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=154 nstack_initial=0)\n", - "2024-09-12 10:50:41,597 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_FAST(arg=3, lineno=3723)\n", - "2024-09-12 10:50:41,597 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,598 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=RETURN_VALUE(arg=None, lineno=3723)\n", - "2024-09-12 10:50:41,599 - numba.core.byteflow - DEBUG - stack ['$lo154.0']\n", - "2024-09-12 10:50:41,599 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:41,600 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-09-12 10:50:41,601 - numba.core.byteflow - DEBUG - stack: ['$phi96.0']\n", - "2024-09-12 10:50:41,601 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=96 nstack_initial=1)\n", - "2024-09-12 10:50:41,602 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=STORE_FAST(arg=4, lineno=3713)\n", - "2024-09-12 10:50:41,603 - numba.core.byteflow - DEBUG - stack ['$phi96.0']\n", - "2024-09-12 10:50:41,603 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,604 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:41,604 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:41,605 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:41,606 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,606 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=132 nstack_initial=0)\n", - "2024-09-12 10:50:41,607 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_FAST(arg=7, lineno=3719)\n", - "2024-09-12 10:50:41,608 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,608 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_CONST(arg=3, lineno=3719)\n", - "2024-09-12 10:50:41,609 - numba.core.byteflow - DEBUG - stack ['$mid132.0']\n", - "2024-09-12 10:50:41,610 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BINARY_ADD(arg=None, lineno=3719)\n", - "2024-09-12 10:50:41,610 - numba.core.byteflow - DEBUG - stack ['$mid132.0', '$const134.1']\n", - "2024-09-12 10:50:41,611 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=STORE_FAST(arg=3, lineno=3719)\n", - "2024-09-12 10:50:41,611 - numba.core.byteflow - DEBUG - stack ['$136binary_add.2']\n", - "2024-09-12 10:50:41,612 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=JUMP_FORWARD(arg=2, lineno=3719)\n", - "2024-09-12 10:50:41,613 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,613 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,614 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-09-12 10:50:41,614 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,615 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=142 nstack_initial=0)\n", - "2024-09-12 10:50:41,616 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=7, lineno=3722)\n", - "2024-09-12 10:50:41,616 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,617 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=STORE_FAST(arg=4, lineno=3722)\n", - "2024-09-12 10:50:41,618 - numba.core.byteflow - DEBUG - stack ['$mid142.0']\n", - "2024-09-12 10:50:41,618 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,619 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-09-12 10:50:41,619 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-09-12 10:50:41,620 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:41,621 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=146 nstack_initial=0)\n", - "2024-09-12 10:50:41,621 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-09-12 10:50:41,622 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:41,622 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-09-12 10:50:41,623 - numba.core.byteflow - DEBUG - stack ['$hi146.0']\n", - "2024-09-12 10:50:41,623 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-09-12 10:50:41,624 - numba.core.byteflow - DEBUG - stack ['$hi146.0', '$lo148.1']\n", - "2024-09-12 10:50:41,625 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=POP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "2024-09-12 10:50:41,625 - numba.core.byteflow - DEBUG - stack ['$150compare_op.2']\n", - "2024-09-12 10:50:41,626 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=154, stack=(), blockstack=(), npush=0), Edge(pc=106, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:41,627 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-09-12 10:50:41,627 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-09-12 10:50:41,628 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0)])\n", - "2024-09-12 10:50:41,629 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:41,630 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=12 nstack_initial=0): set(),\n", - " State(pc_initial=24 nstack_initial=1): {'$phi24.0'},\n", - " State(pc_initial=26 nstack_initial=2): {'$phi26.1'},\n", - " State(pc_initial=46 nstack_initial=1): set(),\n", - " State(pc_initial=54 nstack_initial=1): set(),\n", - " State(pc_initial=56 nstack_initial=0): set(),\n", - " State(pc_initial=60 nstack_initial=0): set(),\n", - " State(pc_initial=68 nstack_initial=0): set(),\n", - " State(pc_initial=74 nstack_initial=0): set(),\n", - " State(pc_initial=86 nstack_initial=0): set(),\n", - " State(pc_initial=94 nstack_initial=0): set(),\n", - " State(pc_initial=96 nstack_initial=1): {'$phi96.0'},\n", - " State(pc_initial=98 nstack_initial=0): set(),\n", - " State(pc_initial=106 nstack_initial=0): set(),\n", - " State(pc_initial=132 nstack_initial=0): set(),\n", - " State(pc_initial=142 nstack_initial=0): set(),\n", - " State(pc_initial=146 nstack_initial=0): set(),\n", - " State(pc_initial=154 nstack_initial=0): set()})\n", - "2024-09-12 10:50:41,631 - numba.core.byteflow - DEBUG - defmap: {'$phi24.0': State(pc_initial=12 nstack_initial=0),\n", - " '$phi26.1': State(pc_initial=24 nstack_initial=1),\n", - " '$phi96.0': State(pc_initial=86 nstack_initial=0)}\n", - "2024-09-12 10:50:41,632 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi54.0', State(pc_initial=54 nstack_initial=1))},\n", - " '$phi26.0': {('$phi24.0', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi54.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:41,633 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:41,634 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:41,635 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:41,636 - numba.core.byteflow - DEBUG - keep phismap: {'$phi24.0': {('$22get_iter.5', State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi96.0': {('$90binary_add.2', State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}}\n", - "2024-09-12 10:50:41,637 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=12 nstack_initial=0): {'$phi24.0': '$22get_iter.5'},\n", - " State(pc_initial=24 nstack_initial=1): {'$phi26.1': '$24for_iter.2'},\n", - " State(pc_initial=86 nstack_initial=0): {'$phi96.0': '$90binary_add.2'},\n", - " State(pc_initial=94 nstack_initial=0): {'$phi96.0': '$n94.0'}})\n", - "2024-09-12 10:50:41,638 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:41,639 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_method.1'}), (6, {'res': '$v6.2'}), (8, {'func': '$4load_method.1', 'args': ['$v6.2'], 'res': '$8call_method.3'}), (10, {'pred': '$8call_method.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={12: (), 60: ()})\n", - "2024-09-12 10:50:41,640 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=12 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((12, {'res': '$12load_global.0'}), (14, {'res': '$n14.1'}), (16, {'res': '$const16.2'}), (18, {'res': '$const18.3'}), (20, {'func': '$12load_global.0', 'args': ['$n14.1', '$const16.2', '$const18.3'], 'res': '$20call_function.4'}), (22, {'value': '$20call_function.4', 'res': '$22get_iter.5'})), outgoing_phis={'$phi24.0': '$22get_iter.5'}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$22get_iter.5',)})\n", - "2024-09-12 10:50:41,640 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=24 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((24, {'iterator': '$phi24.0', 'pair': '$24for_iter.1', 'indval': '$24for_iter.2', 'pred': '$24for_iter.3'}),), outgoing_phis={'$phi26.1': '$24for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={56: (), 26: ('$phi24.0', '$24for_iter.2')})\n", - "2024-09-12 10:50:41,641 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=26 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((26, {'value': '$phi26.1'}), (28, {'res': '$28load_global.2'}), (30, {'item': '$28load_global.2', 'res': '$30load_method.3'}), (32, {'res': '$a32.4'}), (34, {'res': '$i34.5'}), (36, {'res': '$const36.6'}), (38, {'lhs': '$i34.5', 'rhs': '$const36.6', 'res': '$38binary_subtract.7'}), (40, {'index': '$38binary_subtract.7', 'target': '$a32.4', 'res': '$40binary_subscr.8'}), (42, {'func': '$30load_method.3', 'args': ['$40binary_subscr.8'], 'res': '$42call_method.9'}), (44, {'pred': '$42call_method.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: ('$phi26.0',), 54: ('$phi26.0',)})\n", - "2024-09-12 10:50:41,642 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((46, {'res': '$i46.1'}), (52, {'retval': '$i46.1', 'castval': '$52return_value.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:41,643 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((54, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$phi54.0',)})\n", - "2024-09-12 10:50:41,643 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((56, {'res': '$const56.0'}), (58, {'retval': '$const56.0', 'castval': '$58return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:41,644 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=60 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((60, {'res': '$v_last60.0'}), (62, {'res': '$v62.1'}), (64, {'lhs': '$v_last60.0', 'rhs': '$v62.1', 'res': '$64compare_op.2'}), (66, {'pred': '$64compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={68: (), 74: ()})\n", - "2024-09-12 10:50:41,645 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=68 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((68, {'res': '$n68.0'}), (70, {'value': '$n68.0'}), (72, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-09-12 10:50:41,645 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((74, {'res': '$const74.0'}), (76, {'value': '$const74.0'}), (78, {'res': '$hi78.1'}), (80, {'res': '$n80.2'}), (82, {'lhs': '$hi78.1', 'rhs': '$n80.2', 'res': '$82compare_op.3'}), (84, {'pred': '$82compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={86: (), 94: ()})\n", - "2024-09-12 10:50:41,646 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=86 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((86, {'res': '$hi86.0'}), (88, {'res': '$const88.1'}), (90, {'lhs': '$hi86.0', 'rhs': '$const88.1', 'res': '$90binary_add.2'}), (92, {})), outgoing_phis={'$phi96.0': '$90binary_add.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$90binary_add.2',)})\n", - "2024-09-12 10:50:41,647 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=94 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((94, {'res': '$n94.0'}),), outgoing_phis={'$phi96.0': '$n94.0'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$n94.0',)})\n", - "2024-09-12 10:50:41,648 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=96 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((96, {'value': '$phi96.0'}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-09-12 10:50:41,648 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=98 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((98, {'res': '$hi98.0'}), (100, {'res': '$lo100.1'}), (102, {'lhs': '$hi98.0', 'rhs': '$lo100.1', 'res': '$102compare_op.2'}), (104, {'pred': '$102compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={106: (), 154: ()})\n", - "2024-09-12 10:50:41,649 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=106 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((106, {'res': '$lo106.0'}), (108, {'res': '$hi108.1'}), (110, {'lhs': '$lo106.0', 'rhs': '$hi108.1', 'res': '$110binary_add.2'}), (112, {'res': '$const112.3'}), (114, {'lhs': '$110binary_add.2', 'rhs': '$const112.3', 'res': '$114binary_rshift.4'}), (116, {'value': '$114binary_rshift.4'}), (118, {'res': '$118load_deref.5'}), (120, {'res': '$a120.6'}), (122, {'res': '$mid122.7'}), (124, {'index': '$mid122.7', 'target': '$a120.6', 'res': '$124binary_subscr.8'}), (126, {'res': '$v126.9'}), (128, {'func': '$118load_deref.5', 'args': ['$124binary_subscr.8', '$v126.9'], 'res': '$128call_function.10'}), (130, {'pred': '$128call_function.10'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={132: (), 142: ()})\n", - "2024-09-12 10:50:41,650 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=132 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((132, {'res': '$mid132.0'}), (134, {'res': '$const134.1'}), (136, {'lhs': '$mid132.0', 'rhs': '$const134.1', 'res': '$136binary_add.2'}), (138, {'value': '$136binary_add.2'}), (140, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-09-12 10:50:41,650 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=142 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((142, {'res': '$mid142.0'}), (144, {'value': '$mid142.0'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-09-12 10:50:41,651 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=146 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((146, {'res': '$hi146.0'}), (148, {'res': '$lo148.1'}), (150, {'lhs': '$hi146.0', 'rhs': '$lo148.1', 'res': '$150compare_op.2'}), (152, {'pred': '$150compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={154: (), 106: ()})\n", - "2024-09-12 10:50:41,652 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=154 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((154, {'res': '$lo154.0'}), (156, {'retval': '$lo154.0', 'castval': '$156return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:41,658 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " v_last = arg(2, name=v_last) ['v_last']\n", - " lo = arg(3, name=lo) ['lo']\n", - " hi = arg(4, name=hi) ['hi']\n", - " n = arg(5, name=n) ['n']\n", - " $2load_global.0 = global(np: ) ['$2load_global.0']\n", - " $4load_method.1 = getattr(value=$2load_global.0, attr=isnan) ['$2load_global.0', '$4load_method.1']\n", - " $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$8call_method.3', 'v']\n", - " bool10 = global(bool: ) ['bool10']\n", - " $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None) ['$10pred', '$8call_method.3', 'bool10']\n", - " branch $10pred, 12, 60 ['$10pred']\n", - "label 12:\n", - " $12load_global.0 = global(range: ) ['$12load_global.0']\n", - " $const16.2 = const(int, 0) ['$const16.2']\n", - " $const18.3 = const(int, -1) ['$const18.3']\n", - " $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_global.0', '$20call_function.4', '$const16.2', '$const18.3', 'n']\n", - " $22get_iter.5 = getiter(value=$20call_function.4) ['$20call_function.4', '$22get_iter.5']\n", - " $phi24.0 = $22get_iter.5 ['$22get_iter.5', '$phi24.0']\n", - " jump 24 []\n", - "label 24:\n", - " $24for_iter.1 = iternext(value=$phi24.0) ['$24for_iter.1', '$phi24.0']\n", - " $24for_iter.2 = pair_first(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.2']\n", - " $24for_iter.3 = pair_second(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.3']\n", - " $phi26.1 = $24for_iter.2 ['$24for_iter.2', '$phi26.1']\n", - " branch $24for_iter.3, 26, 56 ['$24for_iter.3']\n", - "label 26:\n", - " i = $phi26.1 ['$phi26.1', 'i']\n", - " $28load_global.2 = global(np: ) ['$28load_global.2']\n", - " $30load_method.3 = getattr(value=$28load_global.2, attr=isnan) ['$28load_global.2', '$30load_method.3']\n", - " $const36.6 = const(int, 1) ['$const36.6']\n", - " $38binary_subtract.7 = i - $const36.6 ['$38binary_subtract.7', '$const36.6', 'i']\n", - " $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=) ['$38binary_subtract.7', '$40binary_subscr.8', 'a']\n", - " $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None) ['$30load_method.3', '$40binary_subscr.8', '$42call_method.9']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None) ['$42call_method.9', '$44pred', 'bool44']\n", - " branch $44pred, 54, 46 ['$44pred']\n", - "label 46:\n", - " $52return_value.2 = cast(value=i) ['$52return_value.2', 'i']\n", - " return $52return_value.2 ['$52return_value.2']\n", - "label 54:\n", - " jump 24 []\n", - "label 56:\n", - " $const56.0 = const(int, 0) ['$const56.0']\n", - " $58return_value.1 = cast(value=$const56.0) ['$58return_value.1', '$const56.0']\n", - " return $58return_value.1 ['$58return_value.1']\n", - "label 60:\n", - " $64compare_op.2 = v_last < v ['$64compare_op.2', 'v', 'v_last']\n", - " bool66 = global(bool: ) ['bool66']\n", - " $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None) ['$64compare_op.2', '$66pred', 'bool66']\n", - " branch $66pred, 68, 74 ['$66pred']\n", - "label 68:\n", - " hi = n ['hi', 'n']\n", - " jump 98 []\n", - "label 74:\n", - " lo = const(int, 0) ['lo']\n", - " $82compare_op.3 = hi < n ['$82compare_op.3', 'hi', 'n']\n", - " bool84 = global(bool: ) ['bool84']\n", - " $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None) ['$82compare_op.3', '$84pred', 'bool84']\n", - " branch $84pred, 86, 94 ['$84pred']\n", - "label 86:\n", - " $const88.1 = const(int, 1) ['$const88.1']\n", - " $90binary_add.2 = hi + $const88.1 ['$90binary_add.2', '$const88.1', 'hi']\n", - " $phi96.0 = $90binary_add.2 ['$90binary_add.2', '$phi96.0']\n", - " jump 96 []\n", - "label 94:\n", - " $phi96.0 = n ['$phi96.0', 'n']\n", - " jump 96 []\n", - "label 96:\n", - " hi = $phi96.0 ['$phi96.0', 'hi']\n", - " jump 98 []\n", - "label 98:\n", - " $102compare_op.2 = hi > lo ['$102compare_op.2', 'hi', 'lo']\n", - " bool104 = global(bool: ) ['bool104']\n", - " $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$102compare_op.2', '$104pred', 'bool104']\n", - " branch $104pred, 106, 154 ['$104pred']\n", - "label 106:\n", - " $110binary_add.2 = lo + hi ['$110binary_add.2', 'hi', 'lo']\n", - " $const112.3 = const(int, 1) ['$const112.3']\n", - " mid = $110binary_add.2 >> $const112.3 ['$110binary_add.2', '$const112.3', 'mid']\n", - " $118load_deref.5 = freevar(func: at 0x7f2dc32ecf70>) ['$118load_deref.5']\n", - " $124binary_subscr.8 = getitem(value=a, index=mid, fn=) ['$124binary_subscr.8', 'a', 'mid']\n", - " $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$118load_deref.5', '$124binary_subscr.8', '$128call_function.10', 'v']\n", - " bool130 = global(bool: ) ['bool130']\n", - " $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None) ['$128call_function.10', '$130pred', 'bool130']\n", - " branch $130pred, 132, 142 ['$130pred']\n", - "label 132:\n", - " $const134.1 = const(int, 1) ['$const134.1']\n", - " lo = mid + $const134.1 ['$const134.1', 'lo', 'mid']\n", - " jump 146 []\n", - "label 142:\n", - " hi = mid ['hi', 'mid']\n", - " jump 146 []\n", - "label 146:\n", - " $150compare_op.2 = hi > lo ['$150compare_op.2', 'hi', 'lo']\n", - " bool152 = global(bool: ) ['bool152']\n", - " $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$150compare_op.2', '$152pred', 'bool152']\n", - " branch $152pred, 106, 154 ['$152pred']\n", - "label 154:\n", - " $156return_value.1 = cast(value=lo) ['$156return_value.1', 'lo']\n", - " return $156return_value.1 ['$156return_value.1']\n", - "\n", - "2024-09-12 10:50:41,736 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:41,737 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,738 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:41,739 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:41,740 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:41,741 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:41,741 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:41,742 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:41,743 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:41,744 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:41,744 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,745 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:41,746 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,747 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:41,747 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 12\n", - "2024-09-12 10:50:41,748 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,749 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:41,750 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:41,750 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:41,751 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,752 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:41,753 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:41,753 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:41,754 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 24\n", - "2024-09-12 10:50:41,755 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,755 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:41,756 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:41,757 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:41,758 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:41,758 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:41,759 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 26\n", - "2024-09-12 10:50:41,760 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,761 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:41,761 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:41,762 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:41,763 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:41,763 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:41,764 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:41,765 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,766 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:41,766 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,767 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:41,768 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-09-12 10:50:41,768 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,769 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:41,770 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:41,770 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-09-12 10:50:41,771 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,772 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:41,772 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-09-12 10:50:41,773 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,774 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:41,775 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:41,775 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:41,776 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 60\n", - "2024-09-12 10:50:41,777 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,777 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:41,778 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:41,779 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,779 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:41,780 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 68\n", - "2024-09-12 10:50:41,781 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,782 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:41,782 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,783 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-09-12 10:50:41,784 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,784 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-09-12 10:50:41,785 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:41,786 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:41,786 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,787 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:41,788 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 86\n", - "2024-09-12 10:50:41,788 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,789 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:41,790 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:41,791 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:41,791 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,792 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 94\n", - "2024-09-12 10:50:41,793 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,794 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:41,794 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,795 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 96\n", - "2024-09-12 10:50:41,796 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,796 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:41,797 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,798 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 98\n", - "2024-09-12 10:50:41,798 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,799 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:41,800 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:41,800 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,801 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:41,802 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 106\n", - "2024-09-12 10:50:41,802 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,803 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:41,804 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:41,804 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:41,805 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f2dc32ecf70>)\n", - "2024-09-12 10:50:41,806 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:41,806 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,807 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:41,808 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,808 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:41,809 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 132\n", - "2024-09-12 10:50:41,810 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,810 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:41,811 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-09-12 10:50:41,811 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:41,812 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 142\n", - "2024-09-12 10:50:41,813 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,813 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:41,814 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:41,815 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 146\n", - "2024-09-12 10:50:41,815 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,816 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:41,816 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:41,817 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,818 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:41,818 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 154\n", - "2024-09-12 10:50:41,819 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,820 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:41,820 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:41,822 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102compare_op.2': [],\n", - " '$104pred': [],\n", - " '$10pred': [],\n", - " '$110binary_add.2': [],\n", - " '$118load_deref.5': [],\n", - " '$124binary_subscr.8': [],\n", - " '$128call_function.10': [],\n", - " '$12load_global.0': [],\n", - " '$130pred': [],\n", - " '$150compare_op.2': [],\n", - " '$152pred': [],\n", - " '$156return_value.1': [],\n", - " '$20call_function.4': [],\n", - " '$22get_iter.5': [],\n", - " '$24for_iter.1': [],\n", - " '$24for_iter.2': [],\n", - " '$24for_iter.3': [],\n", - " '$28load_global.2': [],\n", - " '$2load_global.0': [],\n", - " '$30load_method.3': [],\n", - " '$38binary_subtract.7': [],\n", - " '$40binary_subscr.8': [],\n", - " '$42call_method.9': [],\n", - " '$44pred': [],\n", - " '$4load_method.1': [],\n", - " '$52return_value.2': [],\n", - " '$58return_value.1': [],\n", - " '$64compare_op.2': [],\n", - " '$66pred': [],\n", - " '$82compare_op.3': [],\n", - " '$84pred': [],\n", - " '$8call_method.3': [],\n", - " '$90binary_add.2': [],\n", - " '$const112.3': [],\n", - " '$const134.1': [],\n", - " '$const16.2': [],\n", - " '$const18.3': [],\n", - " '$const36.6': [],\n", - " '$const56.0': [],\n", - " '$const88.1': [],\n", - " '$phi24.0': [],\n", - " '$phi26.1': [],\n", - " '$phi96.0': [,\n", - " ],\n", - " 'a': [],\n", - " 'bool10': [],\n", - " 'bool104': [],\n", - " 'bool130': [],\n", - " 'bool152': [],\n", - " 'bool44': [],\n", - " 'bool66': [],\n", - " 'bool84': [],\n", - " 'hi': [,\n", - " ,\n", - " ,\n", - " ],\n", - " 'i': [],\n", - " 'lo': [,\n", - " ,\n", - " ],\n", - " 'mid': [],\n", - " 'n': [],\n", - " 'v': [],\n", - " 'v_last': []})\n", - "2024-09-12 10:50:41,823 - numba.core.ssa - DEBUG - SSA violators {'lo', 'hi', '$phi96.0'}\n", - "2024-09-12 10:50:41,824 - numba.core.ssa - DEBUG - Fix SSA violator on var lo\n", - "2024-09-12 10:50:41,824 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:41,825 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,826 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:41,826 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:41,827 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:41,827 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:41,828 - numba.core.ssa - DEBUG - first assign: lo\n", - "2024-09-12 10:50:41,829 - numba.core.ssa - DEBUG - replaced with: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:41,829 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:41,830 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:41,831 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:41,831 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:41,832 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,833 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:41,833 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,834 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:41,835 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:41,835 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,836 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:41,837 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:41,838 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:41,838 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,839 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:41,839 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:41,840 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:41,841 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:41,841 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,842 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:41,843 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:41,843 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:41,844 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:41,844 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:41,845 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:41,846 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,846 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:41,847 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:41,848 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:41,848 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:41,849 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:41,850 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:41,850 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,851 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:41,851 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,852 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:41,853 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:41,853 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,854 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:41,855 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:41,855 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:41,856 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,857 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:41,857 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:41,858 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,859 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:41,859 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:41,860 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:41,860 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:41,861 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,862 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:41,862 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:41,863 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,864 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:41,864 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:41,865 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,866 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:41,866 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,867 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:41,868 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,868 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-09-12 10:50:41,869 - numba.core.ssa - DEBUG - replaced with: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:41,870 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:41,870 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:41,871 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,872 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:41,872 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:41,873 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,873 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:41,874 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:41,875 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:41,875 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,876 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:41,877 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,877 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:41,878 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,879 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:41,879 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,880 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:41,880 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,881 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:41,882 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,882 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:41,883 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:41,883 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,884 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:41,885 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:41,885 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,886 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:41,887 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:41,888 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:41,889 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f2dc32ecf70>)\n", - "2024-09-12 10:50:41,889 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:41,890 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,891 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:41,891 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,892 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:41,893 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:41,893 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,894 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:41,894 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-09-12 10:50:41,895 - numba.core.ssa - DEBUG - replaced with: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:41,896 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:41,896 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:41,897 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,898 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:41,898 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:41,899 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:41,900 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,900 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:41,901 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:41,901 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,902 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:41,903 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:41,903 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,904 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:41,905 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:41,905 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 74: [],\n", - " 132: []})\n", - "2024-09-12 10:50:41,906 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:41,907 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,907 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:41,908 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:41,908 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:41,909 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:41,910 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:41,910 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:41,911 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:41,912 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:41,912 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,913 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:41,914 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,914 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:41,915 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:41,915 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,916 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:41,917 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:41,917 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:41,918 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,919 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:41,919 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:41,920 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:41,921 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:41,921 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,922 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:41,922 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:41,923 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:41,924 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:41,924 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:41,925 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:41,925 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,926 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:41,927 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:41,927 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:41,928 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:41,928 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:41,929 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:41,930 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,930 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:41,931 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,932 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:41,932 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:41,933 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,933 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:41,934 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:41,935 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:41,935 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,936 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:41,937 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:41,937 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,938 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:41,938 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:41,939 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:41,939 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:41,940 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,941 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:41,941 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:41,942 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,943 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:41,943 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:41,944 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,944 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:41,945 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,945 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:41,946 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,947 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:41,947 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:41,948 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:41,949 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,949 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:41,950 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:41,950 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,951 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:41,952 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:41,952 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:41,953 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,953 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:41,954 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,954 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:41,955 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:41,956 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:41,956 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,957 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:41,957 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:41,958 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:41,959 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,959 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:41,960 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:41,961 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-09-12 10:50:41,961 - numba.core.ssa - DEBUG - insert phi node lo.3 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-09-12 10:50:41,962 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:41,962 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:41,963 - numba.core.ssa - DEBUG - idom 74 from label 96\n", - "2024-09-12 10:50:41,964 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:41,964 - numba.core.ssa - DEBUG - incoming_def lo.1 = const(int, 0)\n", - "2024-09-12 10:50:41,965 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-09-12 10:50:41,965 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-09-12 10:50:41,966 - numba.core.ssa - DEBUG - idom 60 from label 68\n", - "2024-09-12 10:50:41,966 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:41,967 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:41,967 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-09-12 10:50:41,968 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:41,968 - numba.core.ssa - DEBUG - incoming_def lo = arg(3, name=lo)\n", - "2024-09-12 10:50:41,969 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:41,970 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:41,970 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:41,971 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:41,971 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:41,972 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:41,973 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:41,973 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:41,974 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-09-12 10:50:41,974 - numba.core.ssa - DEBUG - insert phi node lo.4 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-09-12 10:50:41,975 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-09-12 10:50:41,975 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:41,976 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-09-12 10:50:41,977 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-09-12 10:50:41,977 - numba.core.ssa - DEBUG - insert phi node lo.5 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-09-12 10:50:41,986 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-09-12 10:50:42,018 - numba.core.ssa - DEBUG - incoming_def lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:42,019 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-09-12 10:50:42,019 - numba.core.ssa - DEBUG - find_def_from_top label 142\n", - "2024-09-12 10:50:42,020 - numba.core.ssa - DEBUG - idom 106 from label 142\n", - "2024-09-12 10:50:42,020 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-09-12 10:50:42,021 - numba.core.ssa - DEBUG - incoming_def lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-09-12 10:50:42,021 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:42,022 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:42,022 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:42,023 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:42,023 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f2dc32ecf70>)\n", - "2024-09-12 10:50:42,024 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:42,024 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,026 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:42,026 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,027 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:42,027 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:42,028 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,029 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:42,029 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:42,030 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,030 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:42,031 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,032 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:42,032 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,033 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:42,034 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,034 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:42,035 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:42,035 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:42,036 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:42,037 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,037 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:42,038 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:42,039 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,039 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:42,040 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:42,040 - numba.core.ssa - DEBUG - find_def_from_top label 154\n", - "2024-09-12 10:50:42,041 - numba.core.ssa - DEBUG - insert phi node lo.6 = phi(incoming_values=[], incoming_blocks=[]) at 154\n", - "2024-09-12 10:50:42,042 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-09-12 10:50:42,042 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:42,043 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-09-12 10:50:42,043 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:42,044 - numba.core.ssa - DEBUG - replaced with: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:42,045 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:42,045 - numba.core.ssa - DEBUG - Fix SSA violator on var hi\n", - "2024-09-12 10:50:42,046 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:42,046 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,047 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:42,047 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:42,047 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:42,048 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:42,048 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:42,050 - numba.core.ssa - DEBUG - first assign: hi\n", - "2024-09-12 10:50:42,050 - numba.core.ssa - DEBUG - replaced with: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:42,051 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:42,051 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:42,052 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:42,052 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,053 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:42,053 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,054 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:42,054 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:42,055 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,055 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:42,055 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:42,056 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:42,056 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,057 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:42,057 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:42,058 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:42,058 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:42,061 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,061 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:42,062 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:42,062 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:42,062 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:42,063 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:42,063 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:42,064 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,064 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:42,065 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:42,066 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:42,067 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:42,067 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:42,068 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:42,069 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,069 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:42,070 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,070 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:42,071 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:42,072 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,072 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:42,072 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:42,073 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:42,074 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,074 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:42,075 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:42,076 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,076 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:42,077 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:42,078 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:42,078 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:42,079 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,079 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:42,080 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:42,080 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,081 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:42,082 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:42,082 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,083 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:42,084 - numba.core.ssa - DEBUG - replaced with: hi.1 = n\n", - "2024-09-12 10:50:42,084 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:42,085 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:42,085 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,086 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:42,087 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:42,087 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:42,088 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,088 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:42,089 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:42,089 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,090 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:42,090 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:42,091 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:42,092 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:42,092 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:42,093 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,093 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:42,094 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:42,095 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:42,095 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,096 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:42,096 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0\n", - "2024-09-12 10:50:42,097 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:42,098 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:42,098 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,099 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:42,099 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:42,100 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:42,101 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,101 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:42,102 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:42,102 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,103 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,104 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:42,104 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:42,105 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:42,105 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f2dc32ecf70>)\n", - "2024-09-12 10:50:42,106 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:42,107 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,107 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:42,108 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,109 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:42,109 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:42,110 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,110 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:42,111 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:42,111 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,112 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:42,113 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,113 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:42,114 - numba.core.ssa - DEBUG - replaced with: hi.3 = mid\n", - "2024-09-12 10:50:42,115 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,115 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:42,116 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,117 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:42,117 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:42,118 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:42,118 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,119 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:42,119 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:42,120 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,121 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,121 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:42,122 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:42,123 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 68: [],\n", - " 96: [],\n", - " 142: []})\n", - "2024-09-12 10:50:42,123 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:42,124 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,124 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:42,125 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:42,125 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:42,126 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:42,127 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:42,127 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:42,128 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:42,128 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:42,129 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,130 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:42,131 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,131 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:42,132 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:42,132 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,132 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:42,133 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:42,134 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:42,135 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,135 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:42,135 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:42,136 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:42,136 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:42,137 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,137 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:42,138 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:42,138 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:42,140 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:42,140 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:42,141 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:42,141 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,142 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:42,143 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:42,143 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:42,144 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:42,144 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:42,144 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:42,145 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,145 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:42,146 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,146 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:42,147 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:42,148 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,149 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:42,149 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:42,150 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:42,151 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,151 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:42,152 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:42,152 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,153 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:42,153 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:42,154 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:42,154 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:42,154 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,155 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:42,155 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:42,157 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,158 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:42,158 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:42,158 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,159 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-09-12 10:50:42,159 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:42,160 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:42,160 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,161 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:42,161 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:42,163 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$82compare_op.3 = hi < n\n", - "2024-09-12 10:50:42,163 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-09-12 10:50:42,164 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-09-12 10:50:42,164 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:42,165 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:42,165 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-09-12 10:50:42,165 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:42,166 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:42,166 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,167 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:42,168 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:42,169 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,169 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:42,170 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:42,170 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:42,171 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-09-12 10:50:42,171 - numba.core.ssa - DEBUG - idom 74 from label 86\n", - "2024-09-12 10:50:42,172 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:42,172 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-09-12 10:50:42,172 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-09-12 10:50:42,174 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:42,174 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:42,175 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-09-12 10:50:42,175 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:42,176 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:42,176 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:42,177 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:42,177 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,177 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:42,178 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:42,178 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:42,179 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,179 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-09-12 10:50:42,180 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:42,180 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:42,181 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,181 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:42,182 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:42,182 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:42,184 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-09-12 10:50:42,185 - numba.core.ssa - DEBUG - insert phi node hi.4 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-09-12 10:50:42,185 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:42,186 - numba.core.ssa - DEBUG - incoming_def hi.2 = $phi96.0\n", - "2024-09-12 10:50:42,186 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-09-12 10:50:42,187 - numba.core.ssa - DEBUG - incoming_def hi.1 = n\n", - "2024-09-12 10:50:42,187 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi.4 > lo.3\n", - "2024-09-12 10:50:42,188 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:42,188 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,190 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:42,190 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:42,191 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,191 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,192 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:42,193 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:42,193 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-09-12 10:50:42,194 - numba.core.ssa - DEBUG - insert phi node hi.5 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-09-12 10:50:42,194 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-09-12 10:50:42,195 - numba.core.ssa - DEBUG - incoming_def hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:42,196 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-09-12 10:50:42,196 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-09-12 10:50:42,197 - numba.core.ssa - DEBUG - insert phi node hi.6 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-09-12 10:50:42,197 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-09-12 10:50:42,198 - numba.core.ssa - DEBUG - find_def_from_top label 132\n", - "2024-09-12 10:50:42,198 - numba.core.ssa - DEBUG - idom 106 from label 132\n", - "2024-09-12 10:50:42,199 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-09-12 10:50:42,199 - numba.core.ssa - DEBUG - incoming_def hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-09-12 10:50:42,200 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-09-12 10:50:42,200 - numba.core.ssa - DEBUG - incoming_def hi.3 = mid\n", - "2024-09-12 10:50:42,201 - numba.core.ssa - DEBUG - incoming_def hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:42,201 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi.5\n", - "2024-09-12 10:50:42,202 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:42,202 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:42,203 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f2dc32ecf70>)\n", - "2024-09-12 10:50:42,203 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:42,204 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,204 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:42,205 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,205 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:42,206 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:42,206 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,208 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:42,209 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:42,210 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,210 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:42,211 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,211 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-09-12 10:50:42,212 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,212 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:42,213 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,213 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:42,214 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:42,214 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:42,215 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi.6 > lo.5\n", - "2024-09-12 10:50:42,215 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:42,216 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,216 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:42,216 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:42,217 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,217 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,218 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:42,218 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:42,219 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi96.0\n", - "2024-09-12 10:50:42,219 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:42,220 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,220 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:42,223 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:42,223 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:42,224 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:42,224 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:42,225 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:42,226 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:42,226 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:42,227 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,227 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:42,228 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,228 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:42,229 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:42,229 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,229 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:42,230 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:42,230 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:42,231 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,231 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:42,232 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:42,232 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:42,233 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:42,233 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,234 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:42,234 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:42,237 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:42,237 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:42,238 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:42,238 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:42,238 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,239 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:42,239 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:42,240 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:42,240 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:42,241 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:42,241 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:42,242 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,242 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:42,243 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,243 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:42,244 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:42,246 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,246 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:42,247 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:42,247 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:42,248 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,248 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:42,249 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:42,250 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,250 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:42,251 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:42,251 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:42,252 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:42,252 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,252 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:42,254 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:42,254 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,255 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:42,255 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:42,256 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,257 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-09-12 10:50:42,257 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:42,258 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:42,258 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,259 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:42,259 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:42,260 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:42,261 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,261 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:42,262 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:42,262 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,263 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:42,264 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:42,264 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:42,265 - numba.core.ssa - DEBUG - first assign: $phi96.0\n", - "2024-09-12 10:50:42,266 - numba.core.ssa - DEBUG - replaced with: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:42,266 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:42,267 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:42,267 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,267 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:42,268 - numba.core.ssa - DEBUG - replaced with: $phi96.0.1 = n\n", - "2024-09-12 10:50:42,269 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:42,270 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:42,270 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,271 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-09-12 10:50:42,271 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:42,272 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:42,272 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,273 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:42,274 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:42,274 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-09-12 10:50:42,275 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:42,275 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,276 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:42,277 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:42,277 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,278 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,279 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,279 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-09-12 10:50:42,280 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:42,280 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:42,281 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f2dc32ecf70>)\n", - "2024-09-12 10:50:42,282 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:42,282 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,282 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:42,283 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,283 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:42,284 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:42,284 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,285 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:42,285 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:42,286 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,287 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:42,288 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,288 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-09-12 10:50:42,289 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,289 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:42,290 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,290 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:42,291 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:42,292 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-09-12 10:50:42,292 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:42,293 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,293 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:42,294 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:42,294 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,295 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,295 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:42,296 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:42,297 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {86: [],\n", - " 94: []})\n", - "2024-09-12 10:50:42,298 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:42,298 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,299 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:42,299 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:42,300 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:42,300 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:42,301 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:42,301 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:42,302 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:42,302 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:42,302 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,303 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:42,303 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,304 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:42,304 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:42,305 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,305 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:42,306 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:42,308 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:42,309 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,309 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:42,310 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:42,311 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:42,311 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:42,312 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,312 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:42,313 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:42,313 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:42,314 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:42,314 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:42,315 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:42,315 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,316 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:42,317 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:42,317 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:42,318 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:42,318 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:42,319 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:42,319 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,320 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:42,320 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,321 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:42,321 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:42,321 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,322 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:42,322 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:42,323 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:42,323 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,324 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:42,324 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:42,325 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,327 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:42,328 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:42,328 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:42,329 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:42,329 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,329 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:42,330 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:42,330 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,331 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:42,331 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:42,333 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,333 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-09-12 10:50:42,334 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:42,334 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:42,335 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,336 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:42,336 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:42,337 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:42,338 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,338 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:42,339 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:42,339 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,340 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:42,340 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:42,341 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:42,341 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:42,342 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:42,342 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,344 - numba.core.ssa - DEBUG - on stmt: $phi96.0.1 = n\n", - "2024-09-12 10:50:42,344 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:42,344 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:42,345 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,345 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-09-12 10:50:42,346 - numba.core.ssa - DEBUG - find_def var='$phi96.0' stmt=hi.2 = $phi96.0\n", - "2024-09-12 10:50:42,346 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:42,348 - numba.core.ssa - DEBUG - insert phi node $phi96.0.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:42,348 - numba.core.ssa - DEBUG - find_def_from_bottom label 94\n", - "2024-09-12 10:50:42,348 - numba.core.ssa - DEBUG - incoming_def $phi96.0.1 = n\n", - "2024-09-12 10:50:42,349 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-09-12 10:50:42,349 - numba.core.ssa - DEBUG - incoming_def $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:42,350 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0.2\n", - "2024-09-12 10:50:42,350 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:42,352 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:42,352 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,352 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:42,353 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:42,354 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-09-12 10:50:42,354 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:42,355 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,356 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:42,356 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:42,357 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,357 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,358 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,358 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-09-12 10:50:42,359 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:42,359 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:42,360 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: at 0x7f2dc32ecf70>)\n", - "2024-09-12 10:50:42,361 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:42,362 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,362 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:42,362 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,363 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:42,363 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:42,364 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,364 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:42,365 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:42,365 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,366 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:42,366 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,367 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-09-12 10:50:42,368 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:42,369 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:42,369 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,370 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:42,370 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:42,371 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-09-12 10:50:42,371 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:42,373 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,373 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:42,374 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:42,374 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,375 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:42,375 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:42,376 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:42,591 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=451)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=452)\n", - " 4\tLOAD_ATTR(arg=1, lineno=452)\n", - " 6\tLOAD_FAST(arg=1, lineno=452)\n", - " 8\tLOAD_FAST(arg=2, lineno=452)\n", - " 10\tLOAD_CONST(arg=1, lineno=452)\n", - " 12\tCALL_FUNCTION_KW(arg=2, lineno=452)\n", - " 14\tRETURN_VALUE(arg=None, lineno=452)\n", - "2024-09-12 10:50:42,592 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:42,593 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:42,593 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:42,594 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=451)\n", - "2024-09-12 10:50:42,595 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,595 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=452)\n", - "2024-09-12 10:50:42,596 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,597 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=452)\n", - "2024-09-12 10:50:42,597 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:42,598 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=452)\n", - "2024-09-12 10:50:42,598 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-09-12 10:50:42,599 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_FAST(arg=2, lineno=452)\n", - "2024-09-12 10:50:42,600 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$item_type6.2']\n", - "2024-09-12 10:50:42,600 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_CONST(arg=1, lineno=452)\n", - "2024-09-12 10:50:42,601 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$item_type6.2', '$allocated8.3']\n", - "2024-09-12 10:50:42,601 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=CALL_FUNCTION_KW(arg=2, lineno=452)\n", - "2024-09-12 10:50:42,602 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1', '$item_type6.2', '$allocated8.3', '$const10.4']\n", - "2024-09-12 10:50:42,603 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=RETURN_VALUE(arg=None, lineno=452)\n", - "2024-09-12 10:50:42,603 - numba.core.byteflow - DEBUG - stack ['$12call_function_kw.5']\n", - "2024-09-12 10:50:42,604 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:42,605 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:42,605 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:42,606 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:42,606 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:42,607 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:42,608 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:42,608 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:42,609 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:42,609 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'res': '$item_type6.2'}), (8, {'res': '$allocated8.3'}), (10, {'res': '$const10.4'}), (12, {'func': '$4load_attr.1', 'args': ['$item_type6.2', '$allocated8.3'], 'names': '$const10.4', 'res': '$12call_function_kw.5'}), (14, {'retval': '$12call_function_kw.5', 'castval': '$14return_value.6'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:42,610 - numba.core.interpreter - DEBUG - label 0:\n", - " cls = arg(0, name=cls) ['cls']\n", - " item_type = arg(1, name=item_type) ['item_type']\n", - " allocated = arg(2, name=allocated) ['allocated']\n", - " $2load_global.0 = global(listobject: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=new_list) ['$2load_global.0', '$4load_attr.1']\n", - " $12call_function_kw.5 = call $4load_attr.1(item_type, func=$4load_attr.1, args=[Var(item_type, typedlist.py:451)], kws=[('allocated', Var(allocated, typedlist.py:451))], vararg=None, varkwarg=None, target=None) ['$12call_function_kw.5', '$4load_attr.1', 'allocated', 'item_type']\n", - " $14return_value.6 = cast(value=$12call_function_kw.5) ['$12call_function_kw.5', '$14return_value.6']\n", - " return $14return_value.6 ['$14return_value.6']\n", - "\n", - "2024-09-12 10:50:42,616 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:42,617 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:42,618 - numba.core.ssa - DEBUG - on stmt: cls = arg(0, name=cls)\n", - "2024-09-12 10:50:42,618 - numba.core.ssa - DEBUG - on stmt: item_type = arg(1, name=item_type)\n", - "2024-09-12 10:50:42,619 - numba.core.ssa - DEBUG - on stmt: allocated = arg(2, name=allocated)\n", - "2024-09-12 10:50:42,620 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(listobject: )\n", - "2024-09-12 10:50:42,620 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=new_list)\n", - "2024-09-12 10:50:42,621 - numba.core.ssa - DEBUG - on stmt: $12call_function_kw.5 = call $4load_attr.1(item_type, func=$4load_attr.1, args=[Var(item_type, typedlist.py:451)], kws=[('allocated', Var(allocated, typedlist.py:451))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:42,622 - numba.core.ssa - DEBUG - on stmt: $14return_value.6 = cast(value=$12call_function_kw.5)\n", - "2024-09-12 10:50:42,622 - numba.core.ssa - DEBUG - on stmt: return $14return_value.6\n", - "2024-09-12 10:50:42,623 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$12call_function_kw.5': [],\n", - " '$14return_value.6': [],\n", - " '$2load_global.0': [],\n", - " '$4load_attr.1': [],\n", - " 'allocated': [],\n", - " 'cls': [],\n", - " 'item_type': []})\n", - "2024-09-12 10:50:42,624 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:42,890 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=610)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=638)\n", - " 4\tLOAD_FAST(arg=0, lineno=638)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=638)\n", - " 8\tLOAD_CONST(arg=1, lineno=638)\n", - " 10\tCOMPARE_OP(arg=1, lineno=638)\n", - " 12\tPOP_JUMP_IF_FALSE(arg=12, lineno=638)\n", - " 14\tLOAD_FAST(arg=0, lineno=639)\n", - " 16\tLOAD_FAST(arg=1, lineno=639)\n", - " 18\tBUILD_TUPLE(arg=2, lineno=639)\n", - " 20\tRETURN_VALUE(arg=None, lineno=639)\n", - "> 22\tLOAD_GLOBAL(arg=1, lineno=641)\n", - " 24\tLOAD_ATTR(arg=2, lineno=641)\n", - " 26\tLOAD_ATTR(arg=3, lineno=641)\n", - " 28\tLOAD_METHOD(arg=4, lineno=641)\n", - " 30\tLOAD_GLOBAL(arg=1, lineno=641)\n", - " 32\tLOAD_ATTR(arg=5, lineno=641)\n", - " 34\tLOAD_ATTR(arg=6, lineno=641)\n", - " 36\tCALL_METHOD(arg=1, lineno=641)\n", - " 38\tSTORE_FAST(arg=2, lineno=641)\n", - " 40\tLOAD_FAST(arg=2, lineno=642)\n", - " 42\tLOAD_METHOD(arg=7, lineno=642)\n", - " 44\tLOAD_FAST(arg=0, lineno=642)\n", - " 46\tLOAD_CONST(arg=2, lineno=642)\n", - " 48\tBINARY_SUBSCR(arg=None, lineno=642)\n", - " 50\tCALL_METHOD(arg=1, lineno=642)\n", - " 52\tPOP_TOP(arg=None, lineno=642)\n", - " 54\tLOAD_GLOBAL(arg=1, lineno=643)\n", - " 56\tLOAD_ATTR(arg=2, lineno=643)\n", - " 58\tLOAD_ATTR(arg=3, lineno=643)\n", - " 60\tLOAD_METHOD(arg=4, lineno=643)\n", - " 62\tLOAD_GLOBAL(arg=1, lineno=643)\n", - " 64\tLOAD_ATTR(arg=5, lineno=643)\n", - " 66\tLOAD_ATTR(arg=6, lineno=643)\n", - " 68\tCALL_METHOD(arg=1, lineno=643)\n", - " 70\tSTORE_FAST(arg=3, lineno=643)\n", - " 72\tLOAD_GLOBAL(arg=8, lineno=645)\n", - " 74\tLOAD_CONST(arg=1, lineno=645)\n", - " 76\tLOAD_GLOBAL(arg=0, lineno=645)\n", - " 78\tLOAD_FAST(arg=0, lineno=645)\n", - " 80\tCALL_FUNCTION(arg=1, lineno=645)\n", - " 82\tCALL_FUNCTION(arg=2, lineno=645)\n", - " 84\tGET_ITER(arg=None, lineno=645)\n", - "> 86\tFOR_ITER(arg=28, lineno=645)\n", - " 88\tSTORE_FAST(arg=4, lineno=645)\n", - " 90\tLOAD_FAST(arg=0, lineno=646)\n", - " 92\tLOAD_FAST(arg=4, lineno=646)\n", - " 94\tBINARY_SUBSCR(arg=None, lineno=646)\n", - " 96\tLOAD_FAST(arg=1, lineno=646)\n", - " 98\tLOAD_FAST(arg=4, lineno=646)\n", - " 100\tLOAD_CONST(arg=1, lineno=646)\n", - " 102\tBINARY_SUBTRACT(arg=None, lineno=646)\n", - " 104\tBINARY_SUBSCR(arg=None, lineno=646)\n", - " 106\tCOMPARE_OP(arg=3, lineno=646)\n", - " 108\tPOP_JUMP_IF_FALSE(arg=72, lineno=646)\n", - " 110\tLOAD_FAST(arg=2, lineno=647)\n", - " 112\tLOAD_METHOD(arg=7, lineno=647)\n", - " 114\tLOAD_FAST(arg=0, lineno=647)\n", - " 116\tLOAD_FAST(arg=4, lineno=647)\n", - " 118\tBINARY_SUBSCR(arg=None, lineno=647)\n", - " 120\tCALL_METHOD(arg=1, lineno=647)\n", - " 122\tPOP_TOP(arg=None, lineno=647)\n", - " 124\tLOAD_FAST(arg=3, lineno=648)\n", - " 126\tLOAD_METHOD(arg=7, lineno=648)\n", - " 128\tLOAD_FAST(arg=1, lineno=648)\n", - " 130\tLOAD_FAST(arg=4, lineno=648)\n", - " 132\tLOAD_CONST(arg=1, lineno=648)\n", - " 134\tBINARY_SUBTRACT(arg=None, lineno=648)\n", - " 136\tBINARY_SUBSCR(arg=None, lineno=648)\n", - " 138\tCALL_METHOD(arg=1, lineno=648)\n", - " 140\tPOP_TOP(arg=None, lineno=648)\n", - "> 142\tJUMP_ABSOLUTE(arg=44, lineno=648)\n", - "> 144\tLOAD_FAST(arg=3, lineno=650)\n", - " 146\tLOAD_METHOD(arg=7, lineno=650)\n", - " 148\tLOAD_FAST(arg=1, lineno=650)\n", - " 150\tLOAD_CONST(arg=3, lineno=650)\n", - " 152\tBINARY_SUBSCR(arg=None, lineno=650)\n", - " 154\tCALL_METHOD(arg=1, lineno=650)\n", - " 156\tPOP_TOP(arg=None, lineno=650)\n", - " 158\tLOAD_FAST(arg=2, lineno=652)\n", - " 160\tLOAD_FAST(arg=3, lineno=652)\n", - " 162\tBUILD_TUPLE(arg=2, lineno=652)\n", - " 164\tRETURN_VALUE(arg=None, lineno=652)\n", - "2024-09-12 10:50:42,891 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:42,892 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:42,893 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:42,893 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=610)\n", - "2024-09-12 10:50:42,894 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,894 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=638)\n", - "2024-09-12 10:50:42,895 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,896 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=638)\n", - "2024-09-12 10:50:42,896 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:42,897 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=638)\n", - "2024-09-12 10:50:42,897 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$starts_old4.1']\n", - "2024-09-12 10:50:42,898 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_CONST(arg=1, lineno=638)\n", - "2024-09-12 10:50:42,898 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-09-12 10:50:42,899 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=COMPARE_OP(arg=1, lineno=638)\n", - "2024-09-12 10:50:42,900 - numba.core.byteflow - DEBUG - stack ['$6call_function.2', '$const8.3']\n", - "2024-09-12 10:50:42,901 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=POP_JUMP_IF_FALSE(arg=12, lineno=638)\n", - "2024-09-12 10:50:42,901 - numba.core.byteflow - DEBUG - stack ['$10compare_op.4']\n", - "2024-09-12 10:50:42,902 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=14, stack=(), blockstack=(), npush=0), Edge(pc=22, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:42,903 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=14 nstack_initial=0), State(pc_initial=22 nstack_initial=0)])\n", - "2024-09-12 10:50:42,903 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:42,904 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=14 nstack_initial=0)\n", - "2024-09-12 10:50:42,905 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=0, lineno=639)\n", - "2024-09-12 10:50:42,905 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,906 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=1, lineno=639)\n", - "2024-09-12 10:50:42,906 - numba.core.byteflow - DEBUG - stack ['$starts_old14.0']\n", - "2024-09-12 10:50:42,907 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=BUILD_TUPLE(arg=2, lineno=639)\n", - "2024-09-12 10:50:42,908 - numba.core.byteflow - DEBUG - stack ['$starts_old14.0', '$stops_old16.1']\n", - "2024-09-12 10:50:42,908 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=RETURN_VALUE(arg=None, lineno=639)\n", - "2024-09-12 10:50:42,909 - numba.core.byteflow - DEBUG - stack ['$18build_tuple.2']\n", - "2024-09-12 10:50:42,909 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:42,910 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=22 nstack_initial=0)])\n", - "2024-09-12 10:50:42,910 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:42,911 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=22 nstack_initial=0)\n", - "2024-09-12 10:50:42,912 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_GLOBAL(arg=1, lineno=641)\n", - "2024-09-12 10:50:42,912 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,913 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_ATTR(arg=2, lineno=641)\n", - "2024-09-12 10:50:42,914 - numba.core.byteflow - DEBUG - stack ['$22load_global.0']\n", - "2024-09-12 10:50:42,914 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_ATTR(arg=3, lineno=641)\n", - "2024-09-12 10:50:42,915 - numba.core.byteflow - DEBUG - stack ['$24load_attr.1']\n", - "2024-09-12 10:50:42,916 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_METHOD(arg=4, lineno=641)\n", - "2024-09-12 10:50:42,916 - numba.core.byteflow - DEBUG - stack ['$26load_attr.2']\n", - "2024-09-12 10:50:42,917 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_GLOBAL(arg=1, lineno=641)\n", - "2024-09-12 10:50:42,917 - numba.core.byteflow - DEBUG - stack ['$28load_method.3']\n", - "2024-09-12 10:50:42,918 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_ATTR(arg=5, lineno=641)\n", - "2024-09-12 10:50:42,919 - numba.core.byteflow - DEBUG - stack ['$28load_method.3', '$30load_global.4']\n", - "2024-09-12 10:50:42,919 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_ATTR(arg=6, lineno=641)\n", - "2024-09-12 10:50:42,920 - numba.core.byteflow - DEBUG - stack ['$28load_method.3', '$32load_attr.5']\n", - "2024-09-12 10:50:42,920 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=CALL_METHOD(arg=1, lineno=641)\n", - "2024-09-12 10:50:42,921 - numba.core.byteflow - DEBUG - stack ['$28load_method.3', '$34load_attr.6']\n", - "2024-09-12 10:50:42,922 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=STORE_FAST(arg=2, lineno=641)\n", - "2024-09-12 10:50:42,922 - numba.core.byteflow - DEBUG - stack ['$36call_method.7']\n", - "2024-09-12 10:50:42,923 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_FAST(arg=2, lineno=642)\n", - "2024-09-12 10:50:42,924 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,924 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_METHOD(arg=7, lineno=642)\n", - "2024-09-12 10:50:42,925 - numba.core.byteflow - DEBUG - stack ['$starts40.8']\n", - "2024-09-12 10:50:42,926 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=LOAD_FAST(arg=0, lineno=642)\n", - "2024-09-12 10:50:42,926 - numba.core.byteflow - DEBUG - stack ['$42load_method.9']\n", - "2024-09-12 10:50:42,927 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_CONST(arg=2, lineno=642)\n", - "2024-09-12 10:50:42,928 - numba.core.byteflow - DEBUG - stack ['$42load_method.9', '$starts_old44.10']\n", - "2024-09-12 10:50:42,928 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=BINARY_SUBSCR(arg=None, lineno=642)\n", - "2024-09-12 10:50:42,929 - numba.core.byteflow - DEBUG - stack ['$42load_method.9', '$starts_old44.10', '$const46.11']\n", - "2024-09-12 10:50:42,929 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=CALL_METHOD(arg=1, lineno=642)\n", - "2024-09-12 10:50:42,930 - numba.core.byteflow - DEBUG - stack ['$42load_method.9', '$48binary_subscr.12']\n", - "2024-09-12 10:50:42,931 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=POP_TOP(arg=None, lineno=642)\n", - "2024-09-12 10:50:42,932 - numba.core.byteflow - DEBUG - stack ['$50call_method.13']\n", - "2024-09-12 10:50:42,932 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=LOAD_GLOBAL(arg=1, lineno=643)\n", - "2024-09-12 10:50:42,933 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,933 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_ATTR(arg=2, lineno=643)\n", - "2024-09-12 10:50:42,934 - numba.core.byteflow - DEBUG - stack ['$54load_global.14']\n", - "2024-09-12 10:50:42,935 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_ATTR(arg=3, lineno=643)\n", - "2024-09-12 10:50:42,935 - numba.core.byteflow - DEBUG - stack ['$56load_attr.15']\n", - "2024-09-12 10:50:42,936 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_METHOD(arg=4, lineno=643)\n", - "2024-09-12 10:50:42,937 - numba.core.byteflow - DEBUG - stack ['$58load_attr.16']\n", - "2024-09-12 10:50:42,937 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_GLOBAL(arg=1, lineno=643)\n", - "2024-09-12 10:50:42,938 - numba.core.byteflow - DEBUG - stack ['$60load_method.17']\n", - "2024-09-12 10:50:42,938 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_ATTR(arg=5, lineno=643)\n", - "2024-09-12 10:50:42,939 - numba.core.byteflow - DEBUG - stack ['$60load_method.17', '$62load_global.18']\n", - "2024-09-12 10:50:42,940 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_ATTR(arg=6, lineno=643)\n", - "2024-09-12 10:50:42,941 - numba.core.byteflow - DEBUG - stack ['$60load_method.17', '$64load_attr.19']\n", - "2024-09-12 10:50:42,941 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=CALL_METHOD(arg=1, lineno=643)\n", - "2024-09-12 10:50:42,942 - numba.core.byteflow - DEBUG - stack ['$60load_method.17', '$66load_attr.20']\n", - "2024-09-12 10:50:42,943 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=STORE_FAST(arg=3, lineno=643)\n", - "2024-09-12 10:50:42,944 - numba.core.byteflow - DEBUG - stack ['$68call_method.21']\n", - "2024-09-12 10:50:42,945 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=LOAD_GLOBAL(arg=8, lineno=645)\n", - "2024-09-12 10:50:42,945 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,946 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=1, lineno=645)\n", - "2024-09-12 10:50:42,947 - numba.core.byteflow - DEBUG - stack ['$72load_global.22']\n", - "2024-09-12 10:50:42,948 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=LOAD_GLOBAL(arg=0, lineno=645)\n", - "2024-09-12 10:50:42,948 - numba.core.byteflow - DEBUG - stack ['$72load_global.22', '$const74.23']\n", - "2024-09-12 10:50:42,949 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=0, lineno=645)\n", - "2024-09-12 10:50:42,950 - numba.core.byteflow - DEBUG - stack ['$72load_global.22', '$const74.23', '$76load_global.24']\n", - "2024-09-12 10:50:42,950 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=CALL_FUNCTION(arg=1, lineno=645)\n", - "2024-09-12 10:50:42,951 - numba.core.byteflow - DEBUG - stack ['$72load_global.22', '$const74.23', '$76load_global.24', '$starts_old78.25']\n", - "2024-09-12 10:50:42,952 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=CALL_FUNCTION(arg=2, lineno=645)\n", - "2024-09-12 10:50:42,953 - numba.core.byteflow - DEBUG - stack ['$72load_global.22', '$const74.23', '$80call_function.26']\n", - "2024-09-12 10:50:42,954 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=GET_ITER(arg=None, lineno=645)\n", - "2024-09-12 10:50:42,954 - numba.core.byteflow - DEBUG - stack ['$82call_function.27']\n", - "2024-09-12 10:50:42,955 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=86, stack=('$84get_iter.28',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:42,956 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=1)])\n", - "2024-09-12 10:50:42,957 - numba.core.byteflow - DEBUG - stack: ['$phi86.0']\n", - "2024-09-12 10:50:42,957 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=86 nstack_initial=1)\n", - "2024-09-12 10:50:42,958 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=FOR_ITER(arg=28, lineno=645)\n", - "2024-09-12 10:50:42,959 - numba.core.byteflow - DEBUG - stack ['$phi86.0']\n", - "2024-09-12 10:50:42,960 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=144, stack=(), blockstack=(), npush=0), Edge(pc=88, stack=('$phi86.0', '$86for_iter.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:42,961 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=144 nstack_initial=0), State(pc_initial=88 nstack_initial=2)])\n", - "2024-09-12 10:50:42,962 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:42,962 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=144 nstack_initial=0)\n", - "2024-09-12 10:50:42,963 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=LOAD_FAST(arg=3, lineno=650)\n", - "2024-09-12 10:50:42,964 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,965 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_METHOD(arg=7, lineno=650)\n", - "2024-09-12 10:50:42,965 - numba.core.byteflow - DEBUG - stack ['$stops144.0']\n", - "2024-09-12 10:50:42,966 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=1, lineno=650)\n", - "2024-09-12 10:50:42,967 - numba.core.byteflow - DEBUG - stack ['$146load_method.1']\n", - "2024-09-12 10:50:42,968 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=LOAD_CONST(arg=3, lineno=650)\n", - "2024-09-12 10:50:42,969 - numba.core.byteflow - DEBUG - stack ['$146load_method.1', '$stops_old148.2']\n", - "2024-09-12 10:50:42,969 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=BINARY_SUBSCR(arg=None, lineno=650)\n", - "2024-09-12 10:50:42,970 - numba.core.byteflow - DEBUG - stack ['$146load_method.1', '$stops_old148.2', '$const150.3']\n", - "2024-09-12 10:50:42,971 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=CALL_METHOD(arg=1, lineno=650)\n", - "2024-09-12 10:50:42,972 - numba.core.byteflow - DEBUG - stack ['$146load_method.1', '$152binary_subscr.4']\n", - "2024-09-12 10:50:42,973 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=POP_TOP(arg=None, lineno=650)\n", - "2024-09-12 10:50:42,973 - numba.core.byteflow - DEBUG - stack ['$154call_method.5']\n", - "2024-09-12 10:50:42,974 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=LOAD_FAST(arg=2, lineno=652)\n", - "2024-09-12 10:50:42,975 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:42,976 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=LOAD_FAST(arg=3, lineno=652)\n", - "2024-09-12 10:50:42,977 - numba.core.byteflow - DEBUG - stack ['$starts158.6']\n", - "2024-09-12 10:50:42,977 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=BUILD_TUPLE(arg=2, lineno=652)\n", - "2024-09-12 10:50:42,978 - numba.core.byteflow - DEBUG - stack ['$starts158.6', '$stops160.7']\n", - "2024-09-12 10:50:42,979 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=RETURN_VALUE(arg=None, lineno=652)\n", - "2024-09-12 10:50:42,980 - numba.core.byteflow - DEBUG - stack ['$162build_tuple.8']\n", - "2024-09-12 10:50:42,980 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:42,981 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=88 nstack_initial=2)])\n", - "2024-09-12 10:50:42,982 - numba.core.byteflow - DEBUG - stack: ['$phi88.0', '$phi88.1']\n", - "2024-09-12 10:50:42,983 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=88 nstack_initial=2)\n", - "2024-09-12 10:50:42,984 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=STORE_FAST(arg=4, lineno=645)\n", - "2024-09-12 10:50:42,984 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$phi88.1']\n", - "2024-09-12 10:50:42,985 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=LOAD_FAST(arg=0, lineno=646)\n", - "2024-09-12 10:50:42,986 - numba.core.byteflow - DEBUG - stack ['$phi88.0']\n", - "2024-09-12 10:50:42,987 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=LOAD_FAST(arg=4, lineno=646)\n", - "2024-09-12 10:50:42,987 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$starts_old90.2']\n", - "2024-09-12 10:50:42,988 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=BINARY_SUBSCR(arg=None, lineno=646)\n", - "2024-09-12 10:50:42,989 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$starts_old90.2', '$i92.3']\n", - "2024-09-12 10:50:42,990 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=LOAD_FAST(arg=1, lineno=646)\n", - "2024-09-12 10:50:42,990 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$94binary_subscr.4']\n", - "2024-09-12 10:50:42,991 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=4, lineno=646)\n", - "2024-09-12 10:50:42,992 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$94binary_subscr.4', '$stops_old96.5']\n", - "2024-09-12 10:50:42,993 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_CONST(arg=1, lineno=646)\n", - "2024-09-12 10:50:42,993 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$94binary_subscr.4', '$stops_old96.5', '$i98.6']\n", - "2024-09-12 10:50:42,994 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=BINARY_SUBTRACT(arg=None, lineno=646)\n", - "2024-09-12 10:50:42,995 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$94binary_subscr.4', '$stops_old96.5', '$i98.6', '$const100.7']\n", - "2024-09-12 10:50:42,996 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=BINARY_SUBSCR(arg=None, lineno=646)\n", - "2024-09-12 10:50:42,996 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$94binary_subscr.4', '$stops_old96.5', '$102binary_subtract.8']\n", - "2024-09-12 10:50:42,997 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=COMPARE_OP(arg=3, lineno=646)\n", - "2024-09-12 10:50:42,998 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$94binary_subscr.4', '$104binary_subscr.9']\n", - "2024-09-12 10:50:42,999 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=POP_JUMP_IF_FALSE(arg=72, lineno=646)\n", - "2024-09-12 10:50:43,000 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$106compare_op.10']\n", - "2024-09-12 10:50:43,000 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=110, stack=('$phi88.0',), blockstack=(), npush=0), Edge(pc=142, stack=('$phi88.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,001 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=110 nstack_initial=1), State(pc_initial=142 nstack_initial=1)])\n", - "2024-09-12 10:50:43,002 - numba.core.byteflow - DEBUG - stack: ['$phi110.0']\n", - "2024-09-12 10:50:43,003 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=110 nstack_initial=1)\n", - "2024-09-12 10:50:43,003 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=LOAD_FAST(arg=2, lineno=647)\n", - "2024-09-12 10:50:43,004 - numba.core.byteflow - DEBUG - stack ['$phi110.0']\n", - "2024-09-12 10:50:43,005 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_METHOD(arg=7, lineno=647)\n", - "2024-09-12 10:50:43,006 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$starts110.1']\n", - "2024-09-12 10:50:43,006 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=LOAD_FAST(arg=0, lineno=647)\n", - "2024-09-12 10:50:43,007 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$112load_method.2']\n", - "2024-09-12 10:50:43,008 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=LOAD_FAST(arg=4, lineno=647)\n", - "2024-09-12 10:50:43,008 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$112load_method.2', '$starts_old114.3']\n", - "2024-09-12 10:50:43,009 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=BINARY_SUBSCR(arg=None, lineno=647)\n", - "2024-09-12 10:50:43,010 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$112load_method.2', '$starts_old114.3', '$i116.4']\n", - "2024-09-12 10:50:43,011 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=CALL_METHOD(arg=1, lineno=647)\n", - "2024-09-12 10:50:43,011 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$112load_method.2', '$118binary_subscr.5']\n", - "2024-09-12 10:50:43,012 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=POP_TOP(arg=None, lineno=647)\n", - "2024-09-12 10:50:43,013 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$120call_method.6']\n", - "2024-09-12 10:50:43,014 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=LOAD_FAST(arg=3, lineno=648)\n", - "2024-09-12 10:50:43,014 - numba.core.byteflow - DEBUG - stack ['$phi110.0']\n", - "2024-09-12 10:50:43,015 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_METHOD(arg=7, lineno=648)\n", - "2024-09-12 10:50:43,016 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$stops124.7']\n", - "2024-09-12 10:50:43,016 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=LOAD_FAST(arg=1, lineno=648)\n", - "2024-09-12 10:50:43,017 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$126load_method.8']\n", - "2024-09-12 10:50:43,018 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=LOAD_FAST(arg=4, lineno=648)\n", - "2024-09-12 10:50:43,019 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$126load_method.8', '$stops_old128.9']\n", - "2024-09-12 10:50:43,019 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_CONST(arg=1, lineno=648)\n", - "2024-09-12 10:50:43,020 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$126load_method.8', '$stops_old128.9', '$i130.10']\n", - "2024-09-12 10:50:43,021 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=BINARY_SUBTRACT(arg=None, lineno=648)\n", - "2024-09-12 10:50:43,022 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$126load_method.8', '$stops_old128.9', '$i130.10', '$const132.11']\n", - "2024-09-12 10:50:43,022 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BINARY_SUBSCR(arg=None, lineno=648)\n", - "2024-09-12 10:50:43,023 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$126load_method.8', '$stops_old128.9', '$134binary_subtract.12']\n", - "2024-09-12 10:50:43,024 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=CALL_METHOD(arg=1, lineno=648)\n", - "2024-09-12 10:50:43,024 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$126load_method.8', '$136binary_subscr.13']\n", - "2024-09-12 10:50:43,025 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=POP_TOP(arg=None, lineno=648)\n", - "2024-09-12 10:50:43,026 - numba.core.byteflow - DEBUG - stack ['$phi110.0', '$138call_method.14']\n", - "2024-09-12 10:50:43,027 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=142, stack=('$phi110.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,027 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=142 nstack_initial=1), State(pc_initial=142 nstack_initial=1)])\n", - "2024-09-12 10:50:43,028 - numba.core.byteflow - DEBUG - stack: ['$phi142.0']\n", - "2024-09-12 10:50:43,029 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=142 nstack_initial=1)\n", - "2024-09-12 10:50:43,029 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=JUMP_ABSOLUTE(arg=44, lineno=648)\n", - "2024-09-12 10:50:43,030 - numba.core.byteflow - DEBUG - stack ['$phi142.0']\n", - "2024-09-12 10:50:43,031 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=86, stack=('$phi142.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,032 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=142 nstack_initial=1), State(pc_initial=86 nstack_initial=1)])\n", - "2024-09-12 10:50:43,032 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=1)])\n", - "2024-09-12 10:50:43,033 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:43,034 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=14 nstack_initial=0): set(),\n", - " State(pc_initial=22 nstack_initial=0): set(),\n", - " State(pc_initial=86 nstack_initial=1): {'$phi86.0'},\n", - " State(pc_initial=88 nstack_initial=2): {'$phi88.1'},\n", - " State(pc_initial=110 nstack_initial=1): set(),\n", - " State(pc_initial=142 nstack_initial=1): set(),\n", - " State(pc_initial=144 nstack_initial=0): set()})\n", - "2024-09-12 10:50:43,035 - numba.core.byteflow - DEBUG - defmap: {'$phi86.0': State(pc_initial=22 nstack_initial=0),\n", - " '$phi88.1': State(pc_initial=86 nstack_initial=1)}\n", - "2024-09-12 10:50:43,036 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi110.0': {('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi142.0': {('$phi110.0',\n", - " State(pc_initial=110 nstack_initial=1)),\n", - " ('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi86.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0)),\n", - " ('$phi142.0',\n", - " State(pc_initial=142 nstack_initial=1))},\n", - " '$phi88.0': {('$phi86.0', State(pc_initial=86 nstack_initial=1))},\n", - " '$phi88.1': {('$86for_iter.2',\n", - " State(pc_initial=86 nstack_initial=1))}})\n", - "2024-09-12 10:50:43,037 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi110.0': {('$phi86.0', State(pc_initial=86 nstack_initial=1))},\n", - " '$phi142.0': {('$phi86.0', State(pc_initial=86 nstack_initial=1))},\n", - " '$phi86.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0)),\n", - " ('$phi86.0', State(pc_initial=86 nstack_initial=1))},\n", - " '$phi88.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0))},\n", - " '$phi88.1': {('$86for_iter.2',\n", - " State(pc_initial=86 nstack_initial=1))}})\n", - "2024-09-12 10:50:43,038 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi110.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0))},\n", - " '$phi142.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0))},\n", - " '$phi86.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0))},\n", - " '$phi88.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0))},\n", - " '$phi88.1': {('$86for_iter.2',\n", - " State(pc_initial=86 nstack_initial=1))}})\n", - "2024-09-12 10:50:43,039 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi110.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0))},\n", - " '$phi142.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0))},\n", - " '$phi86.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0))},\n", - " '$phi88.0': {('$84get_iter.28',\n", - " State(pc_initial=22 nstack_initial=0))},\n", - " '$phi88.1': {('$86for_iter.2',\n", - " State(pc_initial=86 nstack_initial=1))}})\n", - "2024-09-12 10:50:43,040 - numba.core.byteflow - DEBUG - keep phismap: {'$phi86.0': {('$84get_iter.28', State(pc_initial=22 nstack_initial=0))},\n", - " '$phi88.1': {('$86for_iter.2', State(pc_initial=86 nstack_initial=1))}}\n", - "2024-09-12 10:50:43,041 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=22 nstack_initial=0): {'$phi86.0': '$84get_iter.28'},\n", - " State(pc_initial=86 nstack_initial=1): {'$phi88.1': '$86for_iter.2'}})\n", - "2024-09-12 10:50:43,042 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:43,042 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$starts_old4.1'}), (6, {'func': '$2load_global.0', 'args': ['$starts_old4.1'], 'res': '$6call_function.2'}), (8, {'res': '$const8.3'}), (10, {'lhs': '$6call_function.2', 'rhs': '$const8.3', 'res': '$10compare_op.4'}), (12, {'pred': '$10compare_op.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={14: (), 22: ()})\n", - "2024-09-12 10:50:43,043 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=14 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((14, {'res': '$starts_old14.0'}), (16, {'res': '$stops_old16.1'}), (18, {'items': ['$starts_old14.0', '$stops_old16.1'], 'res': '$18build_tuple.2'}), (20, {'retval': '$18build_tuple.2', 'castval': '$20return_value.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:43,044 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=22 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((22, {'res': '$22load_global.0'}), (24, {'item': '$22load_global.0', 'res': '$24load_attr.1'}), (26, {'item': '$24load_attr.1', 'res': '$26load_attr.2'}), (28, {'item': '$26load_attr.2', 'res': '$28load_method.3'}), (30, {'res': '$30load_global.4'}), (32, {'item': '$30load_global.4', 'res': '$32load_attr.5'}), (34, {'item': '$32load_attr.5', 'res': '$34load_attr.6'}), (36, {'func': '$28load_method.3', 'args': ['$34load_attr.6'], 'res': '$36call_method.7'}), (38, {'value': '$36call_method.7'}), (40, {'res': '$starts40.8'}), (42, {'item': '$starts40.8', 'res': '$42load_method.9'}), (44, {'res': '$starts_old44.10'}), (46, {'res': '$const46.11'}), (48, {'index': '$const46.11', 'target': '$starts_old44.10', 'res': '$48binary_subscr.12'}), (50, {'func': '$42load_method.9', 'args': ['$48binary_subscr.12'], 'res': '$50call_method.13'}), (54, {'res': '$54load_global.14'}), (56, {'item': '$54load_global.14', 'res': '$56load_attr.15'}), (58, {'item': '$56load_attr.15', 'res': '$58load_attr.16'}), (60, {'item': '$58load_attr.16', 'res': '$60load_method.17'}), (62, {'res': '$62load_global.18'}), (64, {'item': '$62load_global.18', 'res': '$64load_attr.19'}), (66, {'item': '$64load_attr.19', 'res': '$66load_attr.20'}), (68, {'func': '$60load_method.17', 'args': ['$66load_attr.20'], 'res': '$68call_method.21'}), (70, {'value': '$68call_method.21'}), (72, {'res': '$72load_global.22'}), (74, {'res': '$const74.23'}), (76, {'res': '$76load_global.24'}), (78, {'res': '$starts_old78.25'}), (80, {'func': '$76load_global.24', 'args': ['$starts_old78.25'], 'res': '$80call_function.26'}), (82, {'func': '$72load_global.22', 'args': ['$const74.23', '$80call_function.26'], 'res': '$82call_function.27'}), (84, {'value': '$82call_function.27', 'res': '$84get_iter.28'})), outgoing_phis={'$phi86.0': '$84get_iter.28'}, blockstack=(), active_try_block=None, outgoing_edgepushed={86: ('$84get_iter.28',)})\n", - "2024-09-12 10:50:43,045 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=86 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((86, {'iterator': '$phi86.0', 'pair': '$86for_iter.1', 'indval': '$86for_iter.2', 'pred': '$86for_iter.3'}),), outgoing_phis={'$phi88.1': '$86for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={144: (), 88: ('$phi86.0', '$86for_iter.2')})\n", - "2024-09-12 10:50:43,046 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=88 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((88, {'value': '$phi88.1'}), (90, {'res': '$starts_old90.2'}), (92, {'res': '$i92.3'}), (94, {'index': '$i92.3', 'target': '$starts_old90.2', 'res': '$94binary_subscr.4'}), (96, {'res': '$stops_old96.5'}), (98, {'res': '$i98.6'}), (100, {'res': '$const100.7'}), (102, {'lhs': '$i98.6', 'rhs': '$const100.7', 'res': '$102binary_subtract.8'}), (104, {'index': '$102binary_subtract.8', 'target': '$stops_old96.5', 'res': '$104binary_subscr.9'}), (106, {'lhs': '$94binary_subscr.4', 'rhs': '$104binary_subscr.9', 'res': '$106compare_op.10'}), (108, {'pred': '$106compare_op.10'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={110: ('$phi88.0',), 142: ('$phi88.0',)})\n", - "2024-09-12 10:50:43,046 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=110 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((110, {'res': '$starts110.1'}), (112, {'item': '$starts110.1', 'res': '$112load_method.2'}), (114, {'res': '$starts_old114.3'}), (116, {'res': '$i116.4'}), (118, {'index': '$i116.4', 'target': '$starts_old114.3', 'res': '$118binary_subscr.5'}), (120, {'func': '$112load_method.2', 'args': ['$118binary_subscr.5'], 'res': '$120call_method.6'}), (124, {'res': '$stops124.7'}), (126, {'item': '$stops124.7', 'res': '$126load_method.8'}), (128, {'res': '$stops_old128.9'}), (130, {'res': '$i130.10'}), (132, {'res': '$const132.11'}), (134, {'lhs': '$i130.10', 'rhs': '$const132.11', 'res': '$134binary_subtract.12'}), (136, {'index': '$134binary_subtract.12', 'target': '$stops_old128.9', 'res': '$136binary_subscr.13'}), (138, {'func': '$126load_method.8', 'args': ['$136binary_subscr.13'], 'res': '$138call_method.14'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={142: ('$phi110.0',)})\n", - "2024-09-12 10:50:43,047 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=142 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((142, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={86: ('$phi142.0',)})\n", - "2024-09-12 10:50:43,048 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=144 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((144, {'res': '$stops144.0'}), (146, {'item': '$stops144.0', 'res': '$146load_method.1'}), (148, {'res': '$stops_old148.2'}), (150, {'res': '$const150.3'}), (152, {'index': '$const150.3', 'target': '$stops_old148.2', 'res': '$152binary_subscr.4'}), (154, {'func': '$146load_method.1', 'args': ['$152binary_subscr.4'], 'res': '$154call_method.5'}), (158, {'res': '$starts158.6'}), (160, {'res': '$stops160.7'}), (162, {'items': ['$starts158.6', '$stops160.7'], 'res': '$162build_tuple.8'}), (164, {'retval': '$162build_tuple.8', 'castval': '$164return_value.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:43,053 - numba.core.interpreter - DEBUG - label 0:\n", - " starts_old = arg(0, name=starts_old) ['starts_old']\n", - " stops_old = arg(1, name=stops_old) ['stops_old']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " $6call_function.2 = call $2load_global.0(starts_old, func=$2load_global.0, args=[Var(starts_old, indexing.py:610)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', '$6call_function.2', 'starts_old']\n", - " $const8.3 = const(int, 1) ['$const8.3']\n", - " $10compare_op.4 = $6call_function.2 <= $const8.3 ['$10compare_op.4', '$6call_function.2', '$const8.3']\n", - " bool12 = global(bool: ) ['bool12']\n", - " $12pred = call bool12($10compare_op.4, func=bool12, args=(Var($10compare_op.4, indexing.py:638),), kws=(), vararg=None, varkwarg=None, target=None) ['$10compare_op.4', '$12pred', 'bool12']\n", - " branch $12pred, 14, 22 ['$12pred']\n", - "label 14:\n", - " $18build_tuple.2 = build_tuple(items=[Var(starts_old, indexing.py:610), Var(stops_old, indexing.py:610)]) ['$18build_tuple.2', 'starts_old', 'stops_old']\n", - " $20return_value.3 = cast(value=$18build_tuple.2) ['$18build_tuple.2', '$20return_value.3']\n", - " return $20return_value.3 ['$20return_value.3']\n", - "label 22:\n", - " $22load_global.0 = global(numba: ) ['$22load_global.0']\n", - " $24load_attr.1 = getattr(value=$22load_global.0, attr=typed) ['$22load_global.0', '$24load_attr.1']\n", - " $26load_attr.2 = getattr(value=$24load_attr.1, attr=List) ['$24load_attr.1', '$26load_attr.2']\n", - " $28load_method.3 = getattr(value=$26load_attr.2, attr=empty_list) ['$26load_attr.2', '$28load_method.3']\n", - " $30load_global.4 = global(numba: ) ['$30load_global.4']\n", - " $32load_attr.5 = getattr(value=$30load_global.4, attr=types) ['$30load_global.4', '$32load_attr.5']\n", - " $34load_attr.6 = getattr(value=$32load_attr.5, attr=intp) ['$32load_attr.5', '$34load_attr.6']\n", - " starts = call $28load_method.3($34load_attr.6, func=$28load_method.3, args=[Var($34load_attr.6, indexing.py:641)], kws=(), vararg=None, varkwarg=None, target=None) ['$28load_method.3', '$34load_attr.6', 'starts']\n", - " $42load_method.9 = getattr(value=starts, attr=append) ['$42load_method.9', 'starts']\n", - " $const46.11 = const(int, 0) ['$const46.11']\n", - " $48binary_subscr.12 = getitem(value=starts_old, index=$const46.11, fn=) ['$48binary_subscr.12', '$const46.11', 'starts_old']\n", - " $50call_method.13 = call $42load_method.9($48binary_subscr.12, func=$42load_method.9, args=[Var($48binary_subscr.12, indexing.py:642)], kws=(), vararg=None, varkwarg=None, target=None) ['$42load_method.9', '$48binary_subscr.12', '$50call_method.13']\n", - " $54load_global.14 = global(numba: ) ['$54load_global.14']\n", - " $56load_attr.15 = getattr(value=$54load_global.14, attr=typed) ['$54load_global.14', '$56load_attr.15']\n", - " $58load_attr.16 = getattr(value=$56load_attr.15, attr=List) ['$56load_attr.15', '$58load_attr.16']\n", - " $60load_method.17 = getattr(value=$58load_attr.16, attr=empty_list) ['$58load_attr.16', '$60load_method.17']\n", - " $62load_global.18 = global(numba: ) ['$62load_global.18']\n", - " $64load_attr.19 = getattr(value=$62load_global.18, attr=types) ['$62load_global.18', '$64load_attr.19']\n", - " $66load_attr.20 = getattr(value=$64load_attr.19, attr=intp) ['$64load_attr.19', '$66load_attr.20']\n", - " stops = call $60load_method.17($66load_attr.20, func=$60load_method.17, args=[Var($66load_attr.20, indexing.py:643)], kws=(), vararg=None, varkwarg=None, target=None) ['$60load_method.17', '$66load_attr.20', 'stops']\n", - " $72load_global.22 = global(range: ) ['$72load_global.22']\n", - " $const74.23 = const(int, 1) ['$const74.23']\n", - " $76load_global.24 = global(len: ) ['$76load_global.24']\n", - " $80call_function.26 = call $76load_global.24(starts_old, func=$76load_global.24, args=[Var(starts_old, indexing.py:610)], kws=(), vararg=None, varkwarg=None, target=None) ['$76load_global.24', '$80call_function.26', 'starts_old']\n", - " $82call_function.27 = call $72load_global.22($const74.23, $80call_function.26, func=$72load_global.22, args=[Var($const74.23, indexing.py:645), Var($80call_function.26, indexing.py:645)], kws=(), vararg=None, varkwarg=None, target=None) ['$72load_global.22', '$80call_function.26', '$82call_function.27', '$const74.23']\n", - " $84get_iter.28 = getiter(value=$82call_function.27) ['$82call_function.27', '$84get_iter.28']\n", - " $phi86.0 = $84get_iter.28 ['$84get_iter.28', '$phi86.0']\n", - " jump 86 []\n", - "label 86:\n", - " $86for_iter.1 = iternext(value=$phi86.0) ['$86for_iter.1', '$phi86.0']\n", - " $86for_iter.2 = pair_first(value=$86for_iter.1) ['$86for_iter.1', '$86for_iter.2']\n", - " $86for_iter.3 = pair_second(value=$86for_iter.1) ['$86for_iter.1', '$86for_iter.3']\n", - " $phi88.1 = $86for_iter.2 ['$86for_iter.2', '$phi88.1']\n", - " branch $86for_iter.3, 88, 144 ['$86for_iter.3']\n", - "label 88:\n", - " i = $phi88.1 ['$phi88.1', 'i']\n", - " $94binary_subscr.4 = getitem(value=starts_old, index=i, fn=) ['$94binary_subscr.4', 'i', 'starts_old']\n", - " $const100.7 = const(int, 1) ['$const100.7']\n", - " $102binary_subtract.8 = i - $const100.7 ['$102binary_subtract.8', '$const100.7', 'i']\n", - " $104binary_subscr.9 = getitem(value=stops_old, index=$102binary_subtract.8, fn=) ['$102binary_subtract.8', '$104binary_subscr.9', 'stops_old']\n", - " $106compare_op.10 = $94binary_subscr.4 != $104binary_subscr.9 ['$104binary_subscr.9', '$106compare_op.10', '$94binary_subscr.4']\n", - " bool108 = global(bool: ) ['bool108']\n", - " $108pred = call bool108($106compare_op.10, func=bool108, args=(Var($106compare_op.10, indexing.py:646),), kws=(), vararg=None, varkwarg=None, target=None) ['$106compare_op.10', '$108pred', 'bool108']\n", - " branch $108pred, 110, 142 ['$108pred']\n", - "label 110:\n", - " $112load_method.2 = getattr(value=starts, attr=append) ['$112load_method.2', 'starts']\n", - " $118binary_subscr.5 = getitem(value=starts_old, index=i, fn=) ['$118binary_subscr.5', 'i', 'starts_old']\n", - " $120call_method.6 = call $112load_method.2($118binary_subscr.5, func=$112load_method.2, args=[Var($118binary_subscr.5, indexing.py:647)], kws=(), vararg=None, varkwarg=None, target=None) ['$112load_method.2', '$118binary_subscr.5', '$120call_method.6']\n", - " $126load_method.8 = getattr(value=stops, attr=append) ['$126load_method.8', 'stops']\n", - " $const132.11 = const(int, 1) ['$const132.11']\n", - " $134binary_subtract.12 = i - $const132.11 ['$134binary_subtract.12', '$const132.11', 'i']\n", - " $136binary_subscr.13 = getitem(value=stops_old, index=$134binary_subtract.12, fn=) ['$134binary_subtract.12', '$136binary_subscr.13', 'stops_old']\n", - " $138call_method.14 = call $126load_method.8($136binary_subscr.13, func=$126load_method.8, args=[Var($136binary_subscr.13, indexing.py:648)], kws=(), vararg=None, varkwarg=None, target=None) ['$126load_method.8', '$136binary_subscr.13', '$138call_method.14']\n", - " jump 142 []\n", - "label 142:\n", - " jump 86 []\n", - "label 144:\n", - " $146load_method.1 = getattr(value=stops, attr=append) ['$146load_method.1', 'stops']\n", - " $const150.3 = const(int, -1) ['$const150.3']\n", - " $152binary_subscr.4 = getitem(value=stops_old, index=$const150.3, fn=) ['$152binary_subscr.4', '$const150.3', 'stops_old']\n", - " $154call_method.5 = call $146load_method.1($152binary_subscr.4, func=$146load_method.1, args=[Var($152binary_subscr.4, indexing.py:650)], kws=(), vararg=None, varkwarg=None, target=None) ['$146load_method.1', '$152binary_subscr.4', '$154call_method.5']\n", - " $162build_tuple.8 = build_tuple(items=[Var(starts, indexing.py:641), Var(stops, indexing.py:643)]) ['$162build_tuple.8', 'starts', 'stops']\n", - " $164return_value.9 = cast(value=$162build_tuple.8) ['$162build_tuple.8', '$164return_value.9']\n", - " return $164return_value.9 ['$164return_value.9']\n", - "\n", - "2024-09-12 10:50:43,131 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:43,132 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:43,133 - numba.core.ssa - DEBUG - on stmt: starts_old = arg(0, name=starts_old)\n", - "2024-09-12 10:50:43,134 - numba.core.ssa - DEBUG - on stmt: stops_old = arg(1, name=stops_old)\n", - "2024-09-12 10:50:43,135 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-09-12 10:50:43,135 - numba.core.ssa - DEBUG - on stmt: $6call_function.2 = call $2load_global.0(starts_old, func=$2load_global.0, args=[Var(starts_old, indexing.py:610)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,136 - numba.core.ssa - DEBUG - on stmt: $const8.3 = const(int, 1)\n", - "2024-09-12 10:50:43,137 - numba.core.ssa - DEBUG - on stmt: $10compare_op.4 = $6call_function.2 <= $const8.3\n", - "2024-09-12 10:50:43,138 - numba.core.ssa - DEBUG - on stmt: bool12 = global(bool: )\n", - "2024-09-12 10:50:43,138 - numba.core.ssa - DEBUG - on stmt: $12pred = call bool12($10compare_op.4, func=bool12, args=(Var($10compare_op.4, indexing.py:638),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,139 - numba.core.ssa - DEBUG - on stmt: branch $12pred, 14, 22\n", - "2024-09-12 10:50:43,140 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 14\n", - "2024-09-12 10:50:43,140 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:43,141 - numba.core.ssa - DEBUG - on stmt: $18build_tuple.2 = build_tuple(items=[Var(starts_old, indexing.py:610), Var(stops_old, indexing.py:610)])\n", - "2024-09-12 10:50:43,142 - numba.core.ssa - DEBUG - on stmt: $20return_value.3 = cast(value=$18build_tuple.2)\n", - "2024-09-12 10:50:43,143 - numba.core.ssa - DEBUG - on stmt: return $20return_value.3\n", - "2024-09-12 10:50:43,143 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 22\n", - "2024-09-12 10:50:43,144 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:43,145 - numba.core.ssa - DEBUG - on stmt: $22load_global.0 = global(numba: )\n", - "2024-09-12 10:50:43,146 - numba.core.ssa - DEBUG - on stmt: $24load_attr.1 = getattr(value=$22load_global.0, attr=typed)\n", - "2024-09-12 10:50:43,146 - numba.core.ssa - DEBUG - on stmt: $26load_attr.2 = getattr(value=$24load_attr.1, attr=List)\n", - "2024-09-12 10:50:43,147 - numba.core.ssa - DEBUG - on stmt: $28load_method.3 = getattr(value=$26load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:43,148 - numba.core.ssa - DEBUG - on stmt: $30load_global.4 = global(numba: )\n", - "2024-09-12 10:50:43,149 - numba.core.ssa - DEBUG - on stmt: $32load_attr.5 = getattr(value=$30load_global.4, attr=types)\n", - "2024-09-12 10:50:43,149 - numba.core.ssa - DEBUG - on stmt: $34load_attr.6 = getattr(value=$32load_attr.5, attr=intp)\n", - "2024-09-12 10:50:43,150 - numba.core.ssa - DEBUG - on stmt: starts = call $28load_method.3($34load_attr.6, func=$28load_method.3, args=[Var($34load_attr.6, indexing.py:641)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,151 - numba.core.ssa - DEBUG - on stmt: $42load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:43,152 - numba.core.ssa - DEBUG - on stmt: $const46.11 = const(int, 0)\n", - "2024-09-12 10:50:43,152 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.12 = static_getitem(value=starts_old, index=0, index_var=$const46.11, fn=)\n", - "2024-09-12 10:50:43,153 - numba.core.ssa - DEBUG - on stmt: $50call_method.13 = call $42load_method.9($48binary_subscr.12, func=$42load_method.9, args=[Var($48binary_subscr.12, indexing.py:642)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,154 - numba.core.ssa - DEBUG - on stmt: $54load_global.14 = global(numba: )\n", - "2024-09-12 10:50:43,155 - numba.core.ssa - DEBUG - on stmt: $56load_attr.15 = getattr(value=$54load_global.14, attr=typed)\n", - "2024-09-12 10:50:43,155 - numba.core.ssa - DEBUG - on stmt: $58load_attr.16 = getattr(value=$56load_attr.15, attr=List)\n", - "2024-09-12 10:50:43,156 - numba.core.ssa - DEBUG - on stmt: $60load_method.17 = getattr(value=$58load_attr.16, attr=empty_list)\n", - "2024-09-12 10:50:43,157 - numba.core.ssa - DEBUG - on stmt: $62load_global.18 = global(numba: )\n", - "2024-09-12 10:50:43,158 - numba.core.ssa - DEBUG - on stmt: $64load_attr.19 = getattr(value=$62load_global.18, attr=types)\n", - "2024-09-12 10:50:43,159 - numba.core.ssa - DEBUG - on stmt: $66load_attr.20 = getattr(value=$64load_attr.19, attr=intp)\n", - "2024-09-12 10:50:43,159 - numba.core.ssa - DEBUG - on stmt: stops = call $60load_method.17($66load_attr.20, func=$60load_method.17, args=[Var($66load_attr.20, indexing.py:643)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,160 - numba.core.ssa - DEBUG - on stmt: $72load_global.22 = global(range: )\n", - "2024-09-12 10:50:43,161 - numba.core.ssa - DEBUG - on stmt: $const74.23 = const(int, 1)\n", - "2024-09-12 10:50:43,162 - numba.core.ssa - DEBUG - on stmt: $76load_global.24 = global(len: )\n", - "2024-09-12 10:50:43,163 - numba.core.ssa - DEBUG - on stmt: $80call_function.26 = call $76load_global.24(starts_old, func=$76load_global.24, args=[Var(starts_old, indexing.py:610)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,164 - numba.core.ssa - DEBUG - on stmt: $82call_function.27 = call $72load_global.22($const74.23, $80call_function.26, func=$72load_global.22, args=[Var($const74.23, indexing.py:645), Var($80call_function.26, indexing.py:645)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,164 - numba.core.ssa - DEBUG - on stmt: $84get_iter.28 = getiter(value=$82call_function.27)\n", - "2024-09-12 10:50:43,165 - numba.core.ssa - DEBUG - on stmt: $phi86.0 = $84get_iter.28\n", - "2024-09-12 10:50:43,166 - numba.core.ssa - DEBUG - on stmt: jump 86\n", - "2024-09-12 10:50:43,167 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 86\n", - "2024-09-12 10:50:43,167 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:43,168 - numba.core.ssa - DEBUG - on stmt: $86for_iter.1 = iternext(value=$phi86.0)\n", - "2024-09-12 10:50:43,169 - numba.core.ssa - DEBUG - on stmt: $86for_iter.2 = pair_first(value=$86for_iter.1)\n", - "2024-09-12 10:50:43,170 - numba.core.ssa - DEBUG - on stmt: $86for_iter.3 = pair_second(value=$86for_iter.1)\n", - "2024-09-12 10:50:43,171 - numba.core.ssa - DEBUG - on stmt: $phi88.1 = $86for_iter.2\n", - "2024-09-12 10:50:43,171 - numba.core.ssa - DEBUG - on stmt: branch $86for_iter.3, 88, 144\n", - "2024-09-12 10:50:43,172 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 88\n", - "2024-09-12 10:50:43,173 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:43,174 - numba.core.ssa - DEBUG - on stmt: i = $phi88.1\n", - "2024-09-12 10:50:43,175 - numba.core.ssa - DEBUG - on stmt: $94binary_subscr.4 = getitem(value=starts_old, index=i, fn=)\n", - "2024-09-12 10:50:43,175 - numba.core.ssa - DEBUG - on stmt: $const100.7 = const(int, 1)\n", - "2024-09-12 10:50:43,176 - numba.core.ssa - DEBUG - on stmt: $102binary_subtract.8 = i - $const100.7\n", - "2024-09-12 10:50:43,177 - numba.core.ssa - DEBUG - on stmt: $104binary_subscr.9 = getitem(value=stops_old, index=$102binary_subtract.8, fn=)\n", - "2024-09-12 10:50:43,178 - numba.core.ssa - DEBUG - on stmt: $106compare_op.10 = $94binary_subscr.4 != $104binary_subscr.9\n", - "2024-09-12 10:50:43,179 - numba.core.ssa - DEBUG - on stmt: bool108 = global(bool: )\n", - "2024-09-12 10:50:43,179 - numba.core.ssa - DEBUG - on stmt: $108pred = call bool108($106compare_op.10, func=bool108, args=(Var($106compare_op.10, indexing.py:646),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,180 - numba.core.ssa - DEBUG - on stmt: branch $108pred, 110, 142\n", - "2024-09-12 10:50:43,181 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 110\n", - "2024-09-12 10:50:43,182 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:43,183 - numba.core.ssa - DEBUG - on stmt: $112load_method.2 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:43,183 - numba.core.ssa - DEBUG - on stmt: $118binary_subscr.5 = getitem(value=starts_old, index=i, fn=)\n", - "2024-09-12 10:50:43,184 - numba.core.ssa - DEBUG - on stmt: $120call_method.6 = call $112load_method.2($118binary_subscr.5, func=$112load_method.2, args=[Var($118binary_subscr.5, indexing.py:647)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,185 - numba.core.ssa - DEBUG - on stmt: $126load_method.8 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:43,186 - numba.core.ssa - DEBUG - on stmt: $const132.11 = const(int, 1)\n", - "2024-09-12 10:50:43,186 - numba.core.ssa - DEBUG - on stmt: $134binary_subtract.12 = i - $const132.11\n", - "2024-09-12 10:50:43,187 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.13 = getitem(value=stops_old, index=$134binary_subtract.12, fn=)\n", - "2024-09-12 10:50:43,188 - numba.core.ssa - DEBUG - on stmt: $138call_method.14 = call $126load_method.8($136binary_subscr.13, func=$126load_method.8, args=[Var($136binary_subscr.13, indexing.py:648)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,189 - numba.core.ssa - DEBUG - on stmt: jump 142\n", - "2024-09-12 10:50:43,189 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 142\n", - "2024-09-12 10:50:43,190 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:43,191 - numba.core.ssa - DEBUG - on stmt: jump 86\n", - "2024-09-12 10:50:43,192 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 144\n", - "2024-09-12 10:50:43,192 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:43,193 - numba.core.ssa - DEBUG - on stmt: $146load_method.1 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:43,194 - numba.core.ssa - DEBUG - on stmt: $const150.3 = const(int, -1)\n", - "2024-09-12 10:50:43,195 - numba.core.ssa - DEBUG - on stmt: $152binary_subscr.4 = static_getitem(value=stops_old, index=-1, index_var=$const150.3, fn=)\n", - "2024-09-12 10:50:43,195 - numba.core.ssa - DEBUG - on stmt: $154call_method.5 = call $146load_method.1($152binary_subscr.4, func=$146load_method.1, args=[Var($152binary_subscr.4, indexing.py:650)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,196 - numba.core.ssa - DEBUG - on stmt: $162build_tuple.8 = build_tuple(items=[Var(starts, indexing.py:641), Var(stops, indexing.py:643)])\n", - "2024-09-12 10:50:43,197 - numba.core.ssa - DEBUG - on stmt: $164return_value.9 = cast(value=$162build_tuple.8)\n", - "2024-09-12 10:50:43,198 - numba.core.ssa - DEBUG - on stmt: return $164return_value.9\n", - "2024-09-12 10:50:43,200 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102binary_subtract.8': [],\n", - " '$104binary_subscr.9': [],\n", - " '$106compare_op.10': [],\n", - " '$108pred': [],\n", - " '$10compare_op.4': [],\n", - " '$112load_method.2': [],\n", - " '$118binary_subscr.5': [],\n", - " '$120call_method.6': [],\n", - " '$126load_method.8': [],\n", - " '$12pred': [],\n", - " '$134binary_subtract.12': [],\n", - " '$136binary_subscr.13': [],\n", - " '$138call_method.14': [],\n", - " '$146load_method.1': [],\n", - " '$152binary_subscr.4': [],\n", - " '$154call_method.5': [],\n", - " '$162build_tuple.8': [],\n", - " '$164return_value.9': [],\n", - " '$18build_tuple.2': [],\n", - " '$20return_value.3': [],\n", - " '$22load_global.0': [],\n", - " '$24load_attr.1': [],\n", - " '$26load_attr.2': [],\n", - " '$28load_method.3': [],\n", - " '$2load_global.0': [],\n", - " '$30load_global.4': [],\n", - " '$32load_attr.5': [],\n", - " '$34load_attr.6': [],\n", - " '$42load_method.9': [],\n", - " '$48binary_subscr.12': [],\n", - " '$50call_method.13': [],\n", - " '$54load_global.14': [],\n", - " '$56load_attr.15': [],\n", - " '$58load_attr.16': [],\n", - " '$60load_method.17': [],\n", - " '$62load_global.18': [],\n", - " '$64load_attr.19': [],\n", - " '$66load_attr.20': [],\n", - " '$6call_function.2': [],\n", - " '$72load_global.22': [],\n", - " '$76load_global.24': [],\n", - " '$80call_function.26': [],\n", - " '$82call_function.27': [],\n", - " '$84get_iter.28': [],\n", - " '$86for_iter.1': [],\n", - " '$86for_iter.2': [],\n", - " '$86for_iter.3': [],\n", - " '$94binary_subscr.4': [],\n", - " '$const100.7': [],\n", - " '$const132.11': [],\n", - " '$const150.3': [],\n", - " '$const46.11': [],\n", - " '$const74.23': [],\n", - " '$const8.3': [],\n", - " '$phi86.0': [],\n", - " '$phi88.1': [],\n", - " 'bool108': [],\n", - " 'bool12': [],\n", - " 'i': [],\n", - " 'starts': [],\n", - " 'starts_old': [],\n", - " 'stops': [],\n", - " 'stops_old': []})\n", - "2024-09-12 10:50:43,201 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:43,813 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=5394)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=5395)\n", - " 4\tLOAD_FAST(arg=0, lineno=5395)\n", - " 6\tLOAD_FAST(arg=1, lineno=5395)\n", - " 8\tCALL_FUNCTION(arg=2, lineno=5395)\n", - " 10\tRETURN_VALUE(arg=None, lineno=5395)\n", - "2024-09-12 10:50:43,814 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:43,815 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:43,815 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:43,816 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=5394)\n", - "2024-09-12 10:50:43,816 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:43,817 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=5395)\n", - "2024-09-12 10:50:43,818 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:43,818 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=5395)\n", - "2024-09-12 10:50:43,819 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:43,820 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=5395)\n", - "2024-09-12 10:50:43,820 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$object4.1']\n", - "2024-09-12 10:50:43,821 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_FUNCTION(arg=2, lineno=5395)\n", - "2024-09-12 10:50:43,821 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$object4.1', '$dtype6.2']\n", - "2024-09-12 10:50:43,822 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=RETURN_VALUE(arg=None, lineno=5395)\n", - "2024-09-12 10:50:43,823 - numba.core.byteflow - DEBUG - stack ['$8call_function.3']\n", - "2024-09-12 10:50:43,823 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:43,824 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:43,825 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:43,825 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:43,826 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:43,826 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:43,827 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:43,828 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:43,828 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:43,829 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$object4.1'}), (6, {'res': '$dtype6.2'}), (8, {'func': '$2load_global.0', 'args': ['$object4.1', '$dtype6.2'], 'res': '$8call_function.3'}), (10, {'retval': '$8call_function.3', 'castval': '$10return_value.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:43,830 - numba.core.interpreter - DEBUG - label 0:\n", - " object = arg(0, name=object) ['object']\n", - " dtype = arg(1, name=dtype) ['dtype']\n", - " $2load_global.0 = global(np_array: ) ['$2load_global.0']\n", - " $8call_function.3 = call $2load_global.0(object, dtype, func=$2load_global.0, args=[Var(object, arrayobj.py:5394), Var(dtype, arrayobj.py:5394)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', '$8call_function.3', 'dtype', 'object']\n", - " $10return_value.4 = cast(value=$8call_function.3) ['$10return_value.4', '$8call_function.3']\n", - " return $10return_value.4 ['$10return_value.4']\n", - "\n", - "2024-09-12 10:50:43,836 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:43,836 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:43,837 - numba.core.ssa - DEBUG - on stmt: object = arg(0, name=object)\n", - "2024-09-12 10:50:43,838 - numba.core.ssa - DEBUG - on stmt: dtype = arg(1, name=dtype)\n", - "2024-09-12 10:50:43,838 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np_array: )\n", - "2024-09-12 10:50:43,839 - numba.core.ssa - DEBUG - on stmt: $8call_function.3 = call $2load_global.0(object, dtype, func=$2load_global.0, args=[Var(object, arrayobj.py:5394), Var(dtype, arrayobj.py:5394)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:43,839 - numba.core.ssa - DEBUG - on stmt: $10return_value.4 = cast(value=$8call_function.3)\n", - "2024-09-12 10:50:43,840 - numba.core.ssa - DEBUG - on stmt: return $10return_value.4\n", - "2024-09-12 10:50:43,841 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10return_value.4': [],\n", - " '$2load_global.0': [],\n", - " '$8call_function.3': [],\n", - " 'dtype': [],\n", - " 'object': []})\n", - "2024-09-12 10:50:43,842 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:43,887 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=553)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=586)\n", - " 4\tLOAD_ATTR(arg=1, lineno=586)\n", - " 6\tLOAD_ATTR(arg=2, lineno=586)\n", - " 8\tLOAD_METHOD(arg=3, lineno=586)\n", - " 10\tLOAD_GLOBAL(arg=0, lineno=586)\n", - " 12\tLOAD_ATTR(arg=4, lineno=586)\n", - " 14\tLOAD_ATTR(arg=5, lineno=586)\n", - " 16\tCALL_METHOD(arg=1, lineno=586)\n", - " 18\tSTORE_FAST(arg=4, lineno=586)\n", - " 20\tLOAD_GLOBAL(arg=6, lineno=589)\n", - " 22\tLOAD_GLOBAL(arg=7, lineno=589)\n", - " 24\tLOAD_FAST(arg=0, lineno=589)\n", - " 26\tCALL_FUNCTION(arg=1, lineno=589)\n", - " 28\tCALL_FUNCTION(arg=1, lineno=589)\n", - " 30\tGET_ITER(arg=None, lineno=589)\n", - "> 32\tFOR_ITER(arg=100, lineno=589)\n", - " 34\tSTORE_FAST(arg=5, lineno=589)\n", - " 36\tLOAD_GLOBAL(arg=6, lineno=591)\n", - " 38\tLOAD_FAST(arg=0, lineno=591)\n", - " 40\tLOAD_FAST(arg=5, lineno=591)\n", - " 42\tBINARY_SUBSCR(arg=None, lineno=591)\n", - " 44\tLOAD_FAST(arg=1, lineno=591)\n", - " 46\tLOAD_FAST(arg=5, lineno=591)\n", - " 48\tBINARY_SUBSCR(arg=None, lineno=591)\n", - " 50\tCALL_FUNCTION(arg=2, lineno=591)\n", - " 52\tGET_ITER(arg=None, lineno=591)\n", - "> 54\tFOR_ITER(arg=88, lineno=591)\n", - " 56\tSTORE_FAST(arg=6, lineno=591)\n", - " 58\tLOAD_CONST(arg=1, lineno=592)\n", - " 60\tSTORE_FAST(arg=7, lineno=592)\n", - " 62\tLOAD_GLOBAL(arg=6, lineno=595)\n", - " 64\tLOAD_GLOBAL(arg=7, lineno=595)\n", - " 66\tLOAD_FAST(arg=3, lineno=595)\n", - " 68\tCALL_FUNCTION(arg=1, lineno=595)\n", - " 70\tCALL_FUNCTION(arg=1, lineno=595)\n", - " 72\tGET_ITER(arg=None, lineno=595)\n", - "> 74\tFOR_ITER(arg=70, lineno=595)\n", - " 76\tSTORE_FAST(arg=8, lineno=595)\n", - " 78\tLOAD_FAST(arg=3, lineno=596)\n", - " 80\tLOAD_FAST(arg=8, lineno=596)\n", - " 82\tBINARY_SUBSCR(arg=None, lineno=596)\n", - " 84\tSTORE_FAST(arg=9, lineno=596)\n", - " 86\tLOAD_FAST(arg=2, lineno=597)\n", - " 88\tLOAD_FAST(arg=8, lineno=597)\n", - " 90\tLOAD_FAST(arg=6, lineno=597)\n", - " 92\tBUILD_TUPLE(arg=2, lineno=597)\n", - " 94\tBINARY_SUBSCR(arg=None, lineno=597)\n", - " 96\tSTORE_FAST(arg=10, lineno=597)\n", - " 98\tLOAD_FAST(arg=7, lineno=599)\n", - " 100\tLOAD_FAST(arg=10, lineno=599)\n", - " 102\tLOAD_FAST(arg=9, lineno=599)\n", - " 104\tLOAD_CONST(arg=2, lineno=599)\n", - " 106\tBINARY_SUBSCR(arg=None, lineno=599)\n", - " 108\tBINARY_SUBTRACT(arg=None, lineno=599)\n", - " 110\tLOAD_FAST(arg=9, lineno=599)\n", - " 112\tLOAD_CONST(arg=3, lineno=599)\n", - " 114\tBINARY_SUBSCR(arg=None, lineno=599)\n", - " 116\tBINARY_MODULO(arg=None, lineno=599)\n", - " 118\tLOAD_CONST(arg=2, lineno=599)\n", - " 120\tCOMPARE_OP(arg=2, lineno=599)\n", - " 122\tJUMP_IF_FALSE_OR_POP(arg=106, lineno=599)\n", - " 124\tLOAD_FAST(arg=9, lineno=600)\n", - " 126\tLOAD_CONST(arg=3, lineno=600)\n", - " 128\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 130\tLOAD_CONST(arg=2, lineno=600)\n", - " 132\tCOMPARE_OP(arg=4, lineno=600)\n", - " 134\tPOP_JUMP_IF_FALSE(arg=85, lineno=600)\n", - " 136\tLOAD_FAST(arg=9, lineno=600)\n", - " 138\tLOAD_CONST(arg=2, lineno=600)\n", - " 140\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 142\tLOAD_FAST(arg=10, lineno=600)\n", - " 144\tDUP_TOP(arg=None, lineno=600)\n", - " 146\tROT_THREE(arg=None, lineno=600)\n", - " 148\tCOMPARE_OP(arg=1, lineno=600)\n", - " 150\tJUMP_IF_FALSE_OR_POP(arg=82, lineno=600)\n", - " 152\tLOAD_FAST(arg=9, lineno=600)\n", - " 154\tLOAD_CONST(arg=4, lineno=600)\n", - " 156\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 158\tCOMPARE_OP(arg=0, lineno=600)\n", - " 160\tJUMP_FORWARD(arg=2, lineno=600)\n", - "> 162\tROT_TWO(arg=None, lineno=600)\n", - " 164\tPOP_TOP(arg=None, lineno=600)\n", - "> 166\tJUMP_IF_TRUE_OR_POP(arg=106, lineno=600)\n", - "> 168\tLOAD_FAST(arg=9, lineno=600)\n", - " 170\tLOAD_CONST(arg=3, lineno=600)\n", - " 172\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 174\tLOAD_CONST(arg=2, lineno=600)\n", - " 176\tCOMPARE_OP(arg=0, lineno=600)\n", - " 178\tJUMP_IF_FALSE_OR_POP(arg=106, lineno=600)\n", - " 180\tLOAD_FAST(arg=9, lineno=600)\n", - " 182\tLOAD_CONST(arg=2, lineno=600)\n", - " 184\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 186\tLOAD_FAST(arg=10, lineno=600)\n", - " 188\tDUP_TOP(arg=None, lineno=600)\n", - " 190\tROT_THREE(arg=None, lineno=600)\n", - " 192\tCOMPARE_OP(arg=5, lineno=600)\n", - " 194\tJUMP_IF_FALSE_OR_POP(arg=104, lineno=600)\n", - " 196\tLOAD_FAST(arg=9, lineno=600)\n", - " 198\tLOAD_CONST(arg=4, lineno=600)\n", - " 200\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 202\tCOMPARE_OP(arg=4, lineno=600)\n", - " 204\tJUMP_FORWARD(arg=2, lineno=600)\n", - "> 206\tROT_TWO(arg=None, lineno=600)\n", - " 208\tPOP_TOP(arg=None, lineno=600)\n", - "> 210\tINPLACE_AND(arg=None, lineno=599)\n", - " 212\tSTORE_FAST(arg=7, lineno=599)\n", - " 214\tJUMP_ABSOLUTE(arg=38, lineno=599)\n", - "> 216\tLOAD_FAST(arg=7, lineno=604)\n", - " 218\tPOP_JUMP_IF_FALSE(arg=116, lineno=604)\n", - " 220\tLOAD_FAST(arg=4, lineno=605)\n", - " 222\tLOAD_METHOD(arg=8, lineno=605)\n", - " 224\tLOAD_FAST(arg=6, lineno=605)\n", - " 226\tCALL_METHOD(arg=1, lineno=605)\n", - " 228\tPOP_TOP(arg=None, lineno=605)\n", - "> 230\tJUMP_ABSOLUTE(arg=28, lineno=605)\n", - "> 232\tJUMP_ABSOLUTE(arg=17, lineno=591)\n", - "> 234\tLOAD_FAST(arg=4, lineno=607)\n", - " 236\tRETURN_VALUE(arg=None, lineno=607)\n", - "2024-09-12 10:50:43,888 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:43,888 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:43,889 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:43,890 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=553)\n", - "2024-09-12 10:50:43,890 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:43,891 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=586)\n", - "2024-09-12 10:50:43,891 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:43,892 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=586)\n", - "2024-09-12 10:50:43,893 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:43,893 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_ATTR(arg=2, lineno=586)\n", - "2024-09-12 10:50:43,894 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-09-12 10:50:43,895 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=3, lineno=586)\n", - "2024-09-12 10:50:43,895 - numba.core.byteflow - DEBUG - stack ['$6load_attr.2']\n", - "2024-09-12 10:50:43,896 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=0, lineno=586)\n", - "2024-09-12 10:50:43,896 - numba.core.byteflow - DEBUG - stack ['$8load_method.3']\n", - "2024-09-12 10:50:43,897 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=4, lineno=586)\n", - "2024-09-12 10:50:43,898 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$10load_global.4']\n", - "2024-09-12 10:50:43,898 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_ATTR(arg=5, lineno=586)\n", - "2024-09-12 10:50:43,899 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$12load_attr.5']\n", - "2024-09-12 10:50:43,899 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=CALL_METHOD(arg=1, lineno=586)\n", - "2024-09-12 10:50:43,900 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$14load_attr.6']\n", - "2024-09-12 10:50:43,901 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=STORE_FAST(arg=4, lineno=586)\n", - "2024-09-12 10:50:43,901 - numba.core.byteflow - DEBUG - stack ['$16call_method.7']\n", - "2024-09-12 10:50:43,902 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_GLOBAL(arg=6, lineno=589)\n", - "2024-09-12 10:50:43,903 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:43,903 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_GLOBAL(arg=7, lineno=589)\n", - "2024-09-12 10:50:43,904 - numba.core.byteflow - DEBUG - stack ['$20load_global.8']\n", - "2024-09-12 10:50:43,904 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_FAST(arg=0, lineno=589)\n", - "2024-09-12 10:50:43,905 - numba.core.byteflow - DEBUG - stack ['$20load_global.8', '$22load_global.9']\n", - "2024-09-12 10:50:43,906 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=CALL_FUNCTION(arg=1, lineno=589)\n", - "2024-09-12 10:50:43,907 - numba.core.byteflow - DEBUG - stack ['$20load_global.8', '$22load_global.9', '$starts24.10']\n", - "2024-09-12 10:50:43,907 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=CALL_FUNCTION(arg=1, lineno=589)\n", - "2024-09-12 10:50:43,908 - numba.core.byteflow - DEBUG - stack ['$20load_global.8', '$26call_function.11']\n", - "2024-09-12 10:50:43,909 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=GET_ITER(arg=None, lineno=589)\n", - "2024-09-12 10:50:43,909 - numba.core.byteflow - DEBUG - stack ['$28call_function.12']\n", - "2024-09-12 10:50:43,910 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=32, stack=('$30get_iter.13',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,910 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=1)])\n", - "2024-09-12 10:50:43,911 - numba.core.byteflow - DEBUG - stack: ['$phi32.0']\n", - "2024-09-12 10:50:43,912 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=32 nstack_initial=1)\n", - "2024-09-12 10:50:43,912 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=FOR_ITER(arg=100, lineno=589)\n", - "2024-09-12 10:50:43,913 - numba.core.byteflow - DEBUG - stack ['$phi32.0']\n", - "2024-09-12 10:50:43,914 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=234, stack=(), blockstack=(), npush=0), Edge(pc=34, stack=('$phi32.0', '$32for_iter.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,914 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=234 nstack_initial=0), State(pc_initial=34 nstack_initial=2)])\n", - "2024-09-12 10:50:43,915 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:43,916 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=234 nstack_initial=0)\n", - "2024-09-12 10:50:43,919 - numba.core.byteflow - DEBUG - dispatch pc=234, inst=LOAD_FAST(arg=4, lineno=607)\n", - "2024-09-12 10:50:43,920 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:43,921 - numba.core.byteflow - DEBUG - dispatch pc=236, inst=RETURN_VALUE(arg=None, lineno=607)\n", - "2024-09-12 10:50:43,921 - numba.core.byteflow - DEBUG - stack ['$mask234.0']\n", - "2024-09-12 10:50:43,922 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:43,923 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=34 nstack_initial=2)])\n", - "2024-09-12 10:50:43,924 - numba.core.byteflow - DEBUG - stack: ['$phi34.0', '$phi34.1']\n", - "2024-09-12 10:50:43,924 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=34 nstack_initial=2)\n", - "2024-09-12 10:50:43,925 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=STORE_FAST(arg=5, lineno=589)\n", - "2024-09-12 10:50:43,926 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$phi34.1']\n", - "2024-09-12 10:50:43,927 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_GLOBAL(arg=6, lineno=591)\n", - "2024-09-12 10:50:43,927 - numba.core.byteflow - DEBUG - stack ['$phi34.0']\n", - "2024-09-12 10:50:43,928 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_FAST(arg=0, lineno=591)\n", - "2024-09-12 10:50:43,929 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2']\n", - "2024-09-12 10:50:43,929 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_FAST(arg=5, lineno=591)\n", - "2024-09-12 10:50:43,930 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$starts38.3']\n", - "2024-09-12 10:50:43,931 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=BINARY_SUBSCR(arg=None, lineno=591)\n", - "2024-09-12 10:50:43,932 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$starts38.3', '$i40.4']\n", - "2024-09-12 10:50:43,933 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=LOAD_FAST(arg=1, lineno=591)\n", - "2024-09-12 10:50:43,933 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$42binary_subscr.5']\n", - "2024-09-12 10:50:43,934 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=5, lineno=591)\n", - "2024-09-12 10:50:43,935 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$42binary_subscr.5', '$stops44.6']\n", - "2024-09-12 10:50:43,936 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=BINARY_SUBSCR(arg=None, lineno=591)\n", - "2024-09-12 10:50:43,936 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$42binary_subscr.5', '$stops44.6', '$i46.7']\n", - "2024-09-12 10:50:43,937 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=CALL_FUNCTION(arg=2, lineno=591)\n", - "2024-09-12 10:50:43,938 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$42binary_subscr.5', '$48binary_subscr.8']\n", - "2024-09-12 10:50:43,939 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=GET_ITER(arg=None, lineno=591)\n", - "2024-09-12 10:50:43,939 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$50call_function.9']\n", - "2024-09-12 10:50:43,940 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=54, stack=('$phi34.0', '$52get_iter.10'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,941 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=2)])\n", - "2024-09-12 10:50:43,942 - numba.core.byteflow - DEBUG - stack: ['$phi54.0', '$phi54.1']\n", - "2024-09-12 10:50:43,943 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=2)\n", - "2024-09-12 10:50:43,943 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=FOR_ITER(arg=88, lineno=591)\n", - "2024-09-12 10:50:43,944 - numba.core.byteflow - DEBUG - stack ['$phi54.0', '$phi54.1']\n", - "2024-09-12 10:50:43,945 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=232, stack=('$phi54.0',), blockstack=(), npush=0), Edge(pc=56, stack=('$phi54.0', '$phi54.1', '$54for_iter.3'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,946 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=232 nstack_initial=1), State(pc_initial=56 nstack_initial=3)])\n", - "2024-09-12 10:50:43,947 - numba.core.byteflow - DEBUG - stack: ['$phi232.0']\n", - "2024-09-12 10:50:43,947 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=232 nstack_initial=1)\n", - "2024-09-12 10:50:43,948 - numba.core.byteflow - DEBUG - dispatch pc=232, inst=JUMP_ABSOLUTE(arg=17, lineno=591)\n", - "2024-09-12 10:50:43,949 - numba.core.byteflow - DEBUG - stack ['$phi232.0']\n", - "2024-09-12 10:50:43,950 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=32, stack=('$phi232.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,950 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=3), State(pc_initial=32 nstack_initial=1)])\n", - "2024-09-12 10:50:43,951 - numba.core.byteflow - DEBUG - stack: ['$phi56.0', '$phi56.1', '$phi56.2']\n", - "2024-09-12 10:50:43,952 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=3)\n", - "2024-09-12 10:50:43,953 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=STORE_FAST(arg=6, lineno=591)\n", - "2024-09-12 10:50:43,954 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$phi56.2']\n", - "2024-09-12 10:50:43,954 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_CONST(arg=1, lineno=592)\n", - "2024-09-12 10:50:43,955 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1']\n", - "2024-09-12 10:50:43,956 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=STORE_FAST(arg=7, lineno=592)\n", - "2024-09-12 10:50:43,973 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$const58.3']\n", - "2024-09-12 10:50:43,974 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_GLOBAL(arg=6, lineno=595)\n", - "2024-09-12 10:50:43,974 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1']\n", - "2024-09-12 10:50:43,975 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_GLOBAL(arg=7, lineno=595)\n", - "2024-09-12 10:50:43,976 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$62load_global.4']\n", - "2024-09-12 10:50:43,976 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_FAST(arg=3, lineno=595)\n", - "2024-09-12 10:50:43,977 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$62load_global.4', '$64load_global.5']\n", - "2024-09-12 10:50:43,978 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=CALL_FUNCTION(arg=1, lineno=595)\n", - "2024-09-12 10:50:43,978 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$62load_global.4', '$64load_global.5', '$indices66.6']\n", - "2024-09-12 10:50:43,979 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=CALL_FUNCTION(arg=1, lineno=595)\n", - "2024-09-12 10:50:43,979 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$62load_global.4', '$68call_function.7']\n", - "2024-09-12 10:50:43,980 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=GET_ITER(arg=None, lineno=595)\n", - "2024-09-12 10:50:43,981 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$70call_function.8']\n", - "2024-09-12 10:50:43,981 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=74, stack=('$phi56.0', '$phi56.1', '$72get_iter.9'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,982 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=1), State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:43,983 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:43,983 - numba.core.byteflow - DEBUG - stack: ['$phi74.0', '$phi74.1', '$phi74.2']\n", - "2024-09-12 10:50:43,984 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=3)\n", - "2024-09-12 10:50:43,985 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=FOR_ITER(arg=70, lineno=595)\n", - "2024-09-12 10:50:43,985 - numba.core.byteflow - DEBUG - stack ['$phi74.0', '$phi74.1', '$phi74.2']\n", - "2024-09-12 10:50:43,986 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=216, stack=('$phi74.0', '$phi74.1'), blockstack=(), npush=0), Edge(pc=76, stack=('$phi74.0', '$phi74.1', '$phi74.2', '$74for_iter.4'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,987 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=216 nstack_initial=2), State(pc_initial=76 nstack_initial=4)])\n", - "2024-09-12 10:50:43,987 - numba.core.byteflow - DEBUG - stack: ['$phi216.0', '$phi216.1']\n", - "2024-09-12 10:50:43,988 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=216 nstack_initial=2)\n", - "2024-09-12 10:50:43,989 - numba.core.byteflow - DEBUG - dispatch pc=216, inst=LOAD_FAST(arg=7, lineno=604)\n", - "2024-09-12 10:50:43,989 - numba.core.byteflow - DEBUG - stack ['$phi216.0', '$phi216.1']\n", - "2024-09-12 10:50:43,990 - numba.core.byteflow - DEBUG - dispatch pc=218, inst=POP_JUMP_IF_FALSE(arg=116, lineno=604)\n", - "2024-09-12 10:50:43,991 - numba.core.byteflow - DEBUG - stack ['$phi216.0', '$phi216.1', '$match216.2']\n", - "2024-09-12 10:50:43,991 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=220, stack=('$phi216.0', '$phi216.1'), blockstack=(), npush=0), Edge(pc=230, stack=('$phi216.0', '$phi216.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:43,992 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=76 nstack_initial=4), State(pc_initial=220 nstack_initial=2), State(pc_initial=230 nstack_initial=2)])\n", - "2024-09-12 10:50:43,993 - numba.core.byteflow - DEBUG - stack: ['$phi76.0', '$phi76.1', '$phi76.2', '$phi76.3']\n", - "2024-09-12 10:50:43,993 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=76 nstack_initial=4)\n", - "2024-09-12 10:50:43,994 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=STORE_FAST(arg=8, lineno=595)\n", - "2024-09-12 10:50:43,995 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$phi76.3']\n", - "2024-09-12 10:50:43,995 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=3, lineno=596)\n", - "2024-09-12 10:50:43,996 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2']\n", - "2024-09-12 10:50:43,997 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_FAST(arg=8, lineno=596)\n", - "2024-09-12 10:50:43,997 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$indices78.4']\n", - "2024-09-12 10:50:43,998 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=BINARY_SUBSCR(arg=None, lineno=596)\n", - "2024-09-12 10:50:43,999 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$indices78.4', '$k80.5']\n", - "2024-09-12 10:50:43,999 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=STORE_FAST(arg=9, lineno=596)\n", - "2024-09-12 10:50:44,000 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$82binary_subscr.6']\n", - "2024-09-12 10:50:44,001 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=2, lineno=597)\n", - "2024-09-12 10:50:44,001 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2']\n", - "2024-09-12 10:50:44,002 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_FAST(arg=8, lineno=597)\n", - "2024-09-12 10:50:44,002 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$coords86.7']\n", - "2024-09-12 10:50:44,003 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=LOAD_FAST(arg=6, lineno=597)\n", - "2024-09-12 10:50:44,004 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$coords86.7', '$k88.8']\n", - "2024-09-12 10:50:44,004 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=BUILD_TUPLE(arg=2, lineno=597)\n", - "2024-09-12 10:50:44,005 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$coords86.7', '$k88.8', '$j90.9']\n", - "2024-09-12 10:50:44,006 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=BINARY_SUBSCR(arg=None, lineno=597)\n", - "2024-09-12 10:50:44,006 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$coords86.7', '$92build_tuple.10']\n", - "2024-09-12 10:50:44,007 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=STORE_FAST(arg=10, lineno=597)\n", - "2024-09-12 10:50:44,008 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$94binary_subscr.11']\n", - "2024-09-12 10:50:44,008 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=7, lineno=599)\n", - "2024-09-12 10:50:44,009 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2']\n", - "2024-09-12 10:50:44,010 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=10, lineno=599)\n", - "2024-09-12 10:50:44,010 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12']\n", - "2024-09-12 10:50:44,011 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=LOAD_FAST(arg=9, lineno=599)\n", - "2024-09-12 10:50:44,012 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$elem100.13']\n", - "2024-09-12 10:50:44,012 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=LOAD_CONST(arg=2, lineno=599)\n", - "2024-09-12 10:50:44,013 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$elem100.13', '$idx102.14']\n", - "2024-09-12 10:50:44,013 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=BINARY_SUBSCR(arg=None, lineno=599)\n", - "2024-09-12 10:50:44,014 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$elem100.13', '$idx102.14', '$const104.15']\n", - "2024-09-12 10:50:44,015 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=BINARY_SUBTRACT(arg=None, lineno=599)\n", - "2024-09-12 10:50:44,015 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$elem100.13', '$106binary_subscr.16']\n", - "2024-09-12 10:50:44,016 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=LOAD_FAST(arg=9, lineno=599)\n", - "2024-09-12 10:50:44,017 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$108binary_subtract.17']\n", - "2024-09-12 10:50:44,017 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=3, lineno=599)\n", - "2024-09-12 10:50:44,018 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$108binary_subtract.17', '$idx110.18']\n", - "2024-09-12 10:50:44,019 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BINARY_SUBSCR(arg=None, lineno=599)\n", - "2024-09-12 10:50:44,019 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$108binary_subtract.17', '$idx110.18', '$const112.19']\n", - "2024-09-12 10:50:44,020 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=BINARY_MODULO(arg=None, lineno=599)\n", - "2024-09-12 10:50:44,021 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$108binary_subtract.17', '$114binary_subscr.20']\n", - "2024-09-12 10:50:44,021 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_CONST(arg=2, lineno=599)\n", - "2024-09-12 10:50:44,022 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$116binary_modulo.21']\n", - "2024-09-12 10:50:44,022 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=COMPARE_OP(arg=2, lineno=599)\n", - "2024-09-12 10:50:44,023 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$116binary_modulo.21', '$const118.22']\n", - "2024-09-12 10:50:44,024 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=JUMP_IF_FALSE_OR_POP(arg=106, lineno=599)\n", - "2024-09-12 10:50:44,024 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$120compare_op.23']\n", - "2024-09-12 10:50:44,025 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=124, stack=('$phi76.0', '$phi76.1', '$phi76.2', '$match98.12'), blockstack=(), npush=0), Edge(pc=210, stack=('$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$120compare_op.23'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,026 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=220 nstack_initial=2), State(pc_initial=230 nstack_initial=2), State(pc_initial=124 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,026 - numba.core.byteflow - DEBUG - stack: ['$phi220.0', '$phi220.1']\n", - "2024-09-12 10:50:44,027 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=220 nstack_initial=2)\n", - "2024-09-12 10:50:44,028 - numba.core.byteflow - DEBUG - dispatch pc=220, inst=LOAD_FAST(arg=4, lineno=605)\n", - "2024-09-12 10:50:44,028 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1']\n", - "2024-09-12 10:50:44,029 - numba.core.byteflow - DEBUG - dispatch pc=222, inst=LOAD_METHOD(arg=8, lineno=605)\n", - "2024-09-12 10:50:44,029 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$mask220.2']\n", - "2024-09-12 10:50:44,030 - numba.core.byteflow - DEBUG - dispatch pc=224, inst=LOAD_FAST(arg=6, lineno=605)\n", - "2024-09-12 10:50:44,031 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$222load_method.3']\n", - "2024-09-12 10:50:44,031 - numba.core.byteflow - DEBUG - dispatch pc=226, inst=CALL_METHOD(arg=1, lineno=605)\n", - "2024-09-12 10:50:44,032 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$222load_method.3', '$j224.4']\n", - "2024-09-12 10:50:44,032 - numba.core.byteflow - DEBUG - dispatch pc=228, inst=POP_TOP(arg=None, lineno=605)\n", - "2024-09-12 10:50:44,033 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$226call_method.5']\n", - "2024-09-12 10:50:44,034 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=230, stack=('$phi220.0', '$phi220.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,034 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=230 nstack_initial=2), State(pc_initial=124 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=230 nstack_initial=2)])\n", - "2024-09-12 10:50:44,035 - numba.core.byteflow - DEBUG - stack: ['$phi230.0', '$phi230.1']\n", - "2024-09-12 10:50:44,036 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=230 nstack_initial=2)\n", - "2024-09-12 10:50:44,036 - numba.core.byteflow - DEBUG - dispatch pc=230, inst=JUMP_ABSOLUTE(arg=28, lineno=605)\n", - "2024-09-12 10:50:44,037 - numba.core.byteflow - DEBUG - stack ['$phi230.0', '$phi230.1']\n", - "2024-09-12 10:50:44,037 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=54, stack=('$phi230.0', '$phi230.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,038 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=124 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=230 nstack_initial=2), State(pc_initial=54 nstack_initial=2)])\n", - "2024-09-12 10:50:44,039 - numba.core.byteflow - DEBUG - stack: ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3']\n", - "2024-09-12 10:50:44,039 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=124 nstack_initial=4)\n", - "2024-09-12 10:50:44,040 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:44,040 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3']\n", - "2024-09-12 10:50:44,041 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_CONST(arg=3, lineno=600)\n", - "2024-09-12 10:50:44,042 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$idx124.4']\n", - "2024-09-12 10:50:44,042 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,043 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$idx124.4', '$const126.5']\n", - "2024-09-12 10:50:44,044 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=LOAD_CONST(arg=2, lineno=600)\n", - "2024-09-12 10:50:44,044 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$128binary_subscr.6']\n", - "2024-09-12 10:50:44,045 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=COMPARE_OP(arg=4, lineno=600)\n", - "2024-09-12 10:50:44,046 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$128binary_subscr.6', '$const130.7']\n", - "2024-09-12 10:50:44,046 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=POP_JUMP_IF_FALSE(arg=85, lineno=600)\n", - "2024-09-12 10:50:44,047 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$132compare_op.8']\n", - "2024-09-12 10:50:44,048 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=136, stack=('$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3'), blockstack=(), npush=0), Edge(pc=168, stack=('$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,048 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5), State(pc_initial=230 nstack_initial=2), State(pc_initial=54 nstack_initial=2), State(pc_initial=136 nstack_initial=4), State(pc_initial=168 nstack_initial=4)])\n", - "2024-09-12 10:50:44,049 - numba.core.byteflow - DEBUG - stack: ['$phi210.0', '$phi210.1', '$phi210.2', '$phi210.3', '$phi210.4']\n", - "2024-09-12 10:50:44,050 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=210 nstack_initial=5)\n", - "2024-09-12 10:50:44,050 - numba.core.byteflow - DEBUG - dispatch pc=210, inst=INPLACE_AND(arg=None, lineno=599)\n", - "2024-09-12 10:50:44,051 - numba.core.byteflow - DEBUG - stack ['$phi210.0', '$phi210.1', '$phi210.2', '$phi210.3', '$phi210.4']\n", - "2024-09-12 10:50:44,051 - numba.core.byteflow - DEBUG - dispatch pc=212, inst=STORE_FAST(arg=7, lineno=599)\n", - "2024-09-12 10:50:44,052 - numba.core.byteflow - DEBUG - stack ['$phi210.0', '$phi210.1', '$phi210.2', '$210inplace_and.5']\n", - "2024-09-12 10:50:44,053 - numba.core.byteflow - DEBUG - dispatch pc=214, inst=JUMP_ABSOLUTE(arg=38, lineno=599)\n", - "2024-09-12 10:50:44,053 - numba.core.byteflow - DEBUG - stack ['$phi210.0', '$phi210.1', '$phi210.2']\n", - "2024-09-12 10:50:44,054 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=74, stack=('$phi210.0', '$phi210.1', '$phi210.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,055 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=230 nstack_initial=2), State(pc_initial=54 nstack_initial=2), State(pc_initial=136 nstack_initial=4), State(pc_initial=168 nstack_initial=4), State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:44,055 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=2), State(pc_initial=136 nstack_initial=4), State(pc_initial=168 nstack_initial=4), State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:44,056 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=136 nstack_initial=4), State(pc_initial=168 nstack_initial=4), State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:44,057 - numba.core.byteflow - DEBUG - stack: ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3']\n", - "2024-09-12 10:50:44,057 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=136 nstack_initial=4)\n", - "2024-09-12 10:50:44,058 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:44,058 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3']\n", - "2024-09-12 10:50:44,059 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=LOAD_CONST(arg=2, lineno=600)\n", - "2024-09-12 10:50:44,060 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$idx136.4']\n", - "2024-09-12 10:50:44,060 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,061 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$idx136.4', '$const138.5']\n", - "2024-09-12 10:50:44,062 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=10, lineno=600)\n", - "2024-09-12 10:50:44,062 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$140binary_subscr.6']\n", - "2024-09-12 10:50:44,063 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=DUP_TOP(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,064 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$140binary_subscr.6', '$elem142.7']\n", - "2024-09-12 10:50:44,064 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=ROT_THREE(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,065 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$140binary_subscr.6', '$elem142.7', '$144dup_top.8']\n", - "2024-09-12 10:50:44,066 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=COMPARE_OP(arg=1, lineno=600)\n", - "2024-09-12 10:50:44,066 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8', '$140binary_subscr.6', '$elem142.7']\n", - "2024-09-12 10:50:44,067 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=JUMP_IF_FALSE_OR_POP(arg=82, lineno=600)\n", - "2024-09-12 10:50:44,067 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8', '$148compare_op.9']\n", - "2024-09-12 10:50:44,068 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=152, stack=('$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8'), blockstack=(), npush=0), Edge(pc=162, stack=('$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8', '$148compare_op.9'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,069 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=168 nstack_initial=4), State(pc_initial=74 nstack_initial=3), State(pc_initial=152 nstack_initial=5), State(pc_initial=162 nstack_initial=6)])\n", - "2024-09-12 10:50:44,069 - numba.core.byteflow - DEBUG - stack: ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3']\n", - "2024-09-12 10:50:44,070 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=168 nstack_initial=4)\n", - "2024-09-12 10:50:44,071 - numba.core.byteflow - DEBUG - dispatch pc=168, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:44,071 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3']\n", - "2024-09-12 10:50:44,072 - numba.core.byteflow - DEBUG - dispatch pc=170, inst=LOAD_CONST(arg=3, lineno=600)\n", - "2024-09-12 10:50:44,072 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$idx168.4']\n", - "2024-09-12 10:50:44,073 - numba.core.byteflow - DEBUG - dispatch pc=172, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,074 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$idx168.4', '$const170.5']\n", - "2024-09-12 10:50:44,074 - numba.core.byteflow - DEBUG - dispatch pc=174, inst=LOAD_CONST(arg=2, lineno=600)\n", - "2024-09-12 10:50:44,075 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$172binary_subscr.6']\n", - "2024-09-12 10:50:44,076 - numba.core.byteflow - DEBUG - dispatch pc=176, inst=COMPARE_OP(arg=0, lineno=600)\n", - "2024-09-12 10:50:44,076 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$172binary_subscr.6', '$const174.7']\n", - "2024-09-12 10:50:44,077 - numba.core.byteflow - DEBUG - dispatch pc=178, inst=JUMP_IF_FALSE_OR_POP(arg=106, lineno=600)\n", - "2024-09-12 10:50:44,077 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$176compare_op.8']\n", - "2024-09-12 10:50:44,078 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=180, stack=('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3'), blockstack=(), npush=0), Edge(pc=210, stack=('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$176compare_op.8'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,079 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=3), State(pc_initial=152 nstack_initial=5), State(pc_initial=162 nstack_initial=6), State(pc_initial=180 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,079 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=152 nstack_initial=5), State(pc_initial=162 nstack_initial=6), State(pc_initial=180 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,080 - numba.core.byteflow - DEBUG - stack: ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4']\n", - "2024-09-12 10:50:44,081 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=152 nstack_initial=5)\n", - "2024-09-12 10:50:44,081 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:44,082 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4']\n", - "2024-09-12 10:50:44,082 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_CONST(arg=4, lineno=600)\n", - "2024-09-12 10:50:44,083 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4', '$idx152.5']\n", - "2024-09-12 10:50:44,084 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,084 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4', '$idx152.5', '$const154.6']\n", - "2024-09-12 10:50:44,085 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=COMPARE_OP(arg=0, lineno=600)\n", - "2024-09-12 10:50:44,085 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4', '$156binary_subscr.7']\n", - "2024-09-12 10:50:44,086 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=JUMP_FORWARD(arg=2, lineno=600)\n", - "2024-09-12 10:50:44,087 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$158compare_op.8']\n", - "2024-09-12 10:50:44,087 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=166, stack=('$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$158compare_op.8'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,088 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=162 nstack_initial=6), State(pc_initial=180 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=166 nstack_initial=5)])\n", - "2024-09-12 10:50:44,089 - numba.core.byteflow - DEBUG - stack: ['$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.4', '$phi162.5']\n", - "2024-09-12 10:50:44,089 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=162 nstack_initial=6)\n", - "2024-09-12 10:50:44,090 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=ROT_TWO(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,090 - numba.core.byteflow - DEBUG - stack ['$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.4', '$phi162.5']\n", - "2024-09-12 10:50:44,091 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=POP_TOP(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,092 - numba.core.byteflow - DEBUG - stack ['$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.5', '$phi162.4']\n", - "2024-09-12 10:50:44,092 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=166, stack=('$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.5'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,093 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=180 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=166 nstack_initial=5), State(pc_initial=166 nstack_initial=5)])\n", - "2024-09-12 10:50:44,094 - numba.core.byteflow - DEBUG - stack: ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3']\n", - "2024-09-12 10:50:44,094 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=180 nstack_initial=4)\n", - "2024-09-12 10:50:44,095 - numba.core.byteflow - DEBUG - dispatch pc=180, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:44,096 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3']\n", - "2024-09-12 10:50:44,096 - numba.core.byteflow - DEBUG - dispatch pc=182, inst=LOAD_CONST(arg=2, lineno=600)\n", - "2024-09-12 10:50:44,097 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$idx180.4']\n", - "2024-09-12 10:50:44,097 - numba.core.byteflow - DEBUG - dispatch pc=184, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,098 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$idx180.4', '$const182.5']\n", - "2024-09-12 10:50:44,099 - numba.core.byteflow - DEBUG - dispatch pc=186, inst=LOAD_FAST(arg=10, lineno=600)\n", - "2024-09-12 10:50:44,099 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$184binary_subscr.6']\n", - "2024-09-12 10:50:44,100 - numba.core.byteflow - DEBUG - dispatch pc=188, inst=DUP_TOP(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,100 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$184binary_subscr.6', '$elem186.7']\n", - "2024-09-12 10:50:44,101 - numba.core.byteflow - DEBUG - dispatch pc=190, inst=ROT_THREE(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,102 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$184binary_subscr.6', '$elem186.7', '$188dup_top.8']\n", - "2024-09-12 10:50:44,102 - numba.core.byteflow - DEBUG - dispatch pc=192, inst=COMPARE_OP(arg=5, lineno=600)\n", - "2024-09-12 10:50:44,103 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8', '$184binary_subscr.6', '$elem186.7']\n", - "2024-09-12 10:50:44,104 - numba.core.byteflow - DEBUG - dispatch pc=194, inst=JUMP_IF_FALSE_OR_POP(arg=104, lineno=600)\n", - "2024-09-12 10:50:44,104 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8', '$192compare_op.9']\n", - "2024-09-12 10:50:44,105 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=196, stack=('$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8'), blockstack=(), npush=0), Edge(pc=206, stack=('$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8', '$192compare_op.9'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,106 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5), State(pc_initial=166 nstack_initial=5), State(pc_initial=166 nstack_initial=5), State(pc_initial=196 nstack_initial=5), State(pc_initial=206 nstack_initial=6)])\n", - "2024-09-12 10:50:44,106 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=166 nstack_initial=5), State(pc_initial=166 nstack_initial=5), State(pc_initial=196 nstack_initial=5), State(pc_initial=206 nstack_initial=6)])\n", - "2024-09-12 10:50:44,107 - numba.core.byteflow - DEBUG - stack: ['$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$phi166.4']\n", - "2024-09-12 10:50:44,107 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=166 nstack_initial=5)\n", - "2024-09-12 10:50:44,108 - numba.core.byteflow - DEBUG - dispatch pc=166, inst=JUMP_IF_TRUE_OR_POP(arg=106, lineno=600)\n", - "2024-09-12 10:50:44,109 - numba.core.byteflow - DEBUG - stack ['$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$phi166.4']\n", - "2024-09-12 10:50:44,109 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=168, stack=('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3'), blockstack=(), npush=0), Edge(pc=210, stack=('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$phi166.4'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,110 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=166 nstack_initial=5), State(pc_initial=196 nstack_initial=5), State(pc_initial=206 nstack_initial=6), State(pc_initial=168 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,110 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=196 nstack_initial=5), State(pc_initial=206 nstack_initial=6), State(pc_initial=168 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,111 - numba.core.byteflow - DEBUG - stack: ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4']\n", - "2024-09-12 10:50:44,111 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=196 nstack_initial=5)\n", - "2024-09-12 10:50:44,112 - numba.core.byteflow - DEBUG - dispatch pc=196, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:44,113 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4']\n", - "2024-09-12 10:50:44,113 - numba.core.byteflow - DEBUG - dispatch pc=198, inst=LOAD_CONST(arg=4, lineno=600)\n", - "2024-09-12 10:50:44,114 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4', '$idx196.5']\n", - "2024-09-12 10:50:44,115 - numba.core.byteflow - DEBUG - dispatch pc=200, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,115 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4', '$idx196.5', '$const198.6']\n", - "2024-09-12 10:50:44,116 - numba.core.byteflow - DEBUG - dispatch pc=202, inst=COMPARE_OP(arg=4, lineno=600)\n", - "2024-09-12 10:50:44,116 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4', '$200binary_subscr.7']\n", - "2024-09-12 10:50:44,117 - numba.core.byteflow - DEBUG - dispatch pc=204, inst=JUMP_FORWARD(arg=2, lineno=600)\n", - "2024-09-12 10:50:44,118 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$202compare_op.8']\n", - "2024-09-12 10:50:44,118 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=210, stack=('$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$202compare_op.8'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,119 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=206 nstack_initial=6), State(pc_initial=168 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,146 - numba.core.byteflow - DEBUG - stack: ['$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.4', '$phi206.5']\n", - "2024-09-12 10:50:44,147 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=206 nstack_initial=6)\n", - "2024-09-12 10:50:44,147 - numba.core.byteflow - DEBUG - dispatch pc=206, inst=ROT_TWO(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,148 - numba.core.byteflow - DEBUG - stack ['$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.4', '$phi206.5']\n", - "2024-09-12 10:50:44,148 - numba.core.byteflow - DEBUG - dispatch pc=208, inst=POP_TOP(arg=None, lineno=600)\n", - "2024-09-12 10:50:44,149 - numba.core.byteflow - DEBUG - stack ['$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.5', '$phi206.4']\n", - "2024-09-12 10:50:44,149 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=210, stack=('$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.5'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:44,151 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=168 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,151 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,152 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,152 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:44,153 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:44,154 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=32 nstack_initial=1): {'$phi32.0'},\n", - " State(pc_initial=34 nstack_initial=2): {'$phi34.1'},\n", - " State(pc_initial=54 nstack_initial=2): {'$phi54.1'},\n", - " State(pc_initial=56 nstack_initial=3): {'$phi56.2'},\n", - " State(pc_initial=74 nstack_initial=3): {'$phi74.2'},\n", - " State(pc_initial=76 nstack_initial=4): {'$phi76.3'},\n", - " State(pc_initial=124 nstack_initial=4): set(),\n", - " State(pc_initial=136 nstack_initial=4): set(),\n", - " State(pc_initial=152 nstack_initial=5): {'$phi152.4'},\n", - " State(pc_initial=162 nstack_initial=6): set(),\n", - " State(pc_initial=166 nstack_initial=5): {'$phi166.4'},\n", - " State(pc_initial=168 nstack_initial=4): set(),\n", - " State(pc_initial=180 nstack_initial=4): set(),\n", - " State(pc_initial=196 nstack_initial=5): {'$phi196.4'},\n", - " State(pc_initial=206 nstack_initial=6): set(),\n", - " State(pc_initial=210 nstack_initial=5): {'$phi210.4', '$phi210.3'},\n", - " State(pc_initial=216 nstack_initial=2): set(),\n", - " State(pc_initial=220 nstack_initial=2): set(),\n", - " State(pc_initial=230 nstack_initial=2): set(),\n", - " State(pc_initial=232 nstack_initial=1): set(),\n", - " State(pc_initial=234 nstack_initial=0): set()})\n", - "2024-09-12 10:50:44,155 - numba.core.byteflow - DEBUG - defmap: {'$phi124.3': State(pc_initial=76 nstack_initial=4),\n", - " '$phi152.4': State(pc_initial=136 nstack_initial=4),\n", - " '$phi162.4': State(pc_initial=136 nstack_initial=4),\n", - " '$phi162.5': State(pc_initial=136 nstack_initial=4),\n", - " '$phi166.4': State(pc_initial=152 nstack_initial=5),\n", - " '$phi196.4': State(pc_initial=180 nstack_initial=4),\n", - " '$phi206.4': State(pc_initial=180 nstack_initial=4),\n", - " '$phi206.5': State(pc_initial=180 nstack_initial=4),\n", - " '$phi210.3': State(pc_initial=76 nstack_initial=4),\n", - " '$phi210.4': State(pc_initial=76 nstack_initial=4),\n", - " '$phi32.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi34.1': State(pc_initial=32 nstack_initial=1),\n", - " '$phi54.1': State(pc_initial=34 nstack_initial=2),\n", - " '$phi56.2': State(pc_initial=54 nstack_initial=2),\n", - " '$phi74.2': State(pc_initial=56 nstack_initial=3),\n", - " '$phi76.3': State(pc_initial=74 nstack_initial=3)}\n", - "2024-09-12 10:50:44,156 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi124.0': {('$phi76.0', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi124.1': {('$phi76.1', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi124.2': {('$phi76.2', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi124.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi136.0': {('$phi124.0',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi136.1': {('$phi124.1',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi136.2': {('$phi124.2',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi136.3': {('$phi124.3',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi152.0': {('$phi136.0',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi152.1': {('$phi136.1',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi152.2': {('$phi136.2',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi152.3': {('$phi136.3',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi152.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.0': {('$phi136.0',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.1': {('$phi136.1',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.2': {('$phi136.2',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.3': {('$phi136.3',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.5': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.0': {('$phi152.0',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.0',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi166.1': {('$phi152.1',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.1',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi166.2': {('$phi152.2',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.2',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi166.3': {('$phi152.3',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.3',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi166.4': {('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.5',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi168.0': {('$phi124.0',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=5))},\n", - " '$phi168.1': {('$phi124.1',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=5))},\n", - " '$phi168.2': {('$phi124.2',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi166.2',\n", - " State(pc_initial=166 nstack_initial=5))},\n", - " '$phi168.3': {('$phi124.3',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi166.3',\n", - " State(pc_initial=166 nstack_initial=5))},\n", - " '$phi180.0': {('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=4))},\n", - " '$phi180.1': {('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=4))},\n", - " '$phi180.2': {('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=4))},\n", - " '$phi180.3': {('$phi168.3',\n", - " State(pc_initial=168 nstack_initial=4))},\n", - " '$phi196.0': {('$phi180.0',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi196.1': {('$phi180.1',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi196.2': {('$phi180.2',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi196.3': {('$phi180.3',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi196.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.0': {('$phi180.0',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.1': {('$phi180.1',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.2': {('$phi180.2',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.3': {('$phi180.3',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.5': {('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.0': {('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$phi196.0',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi206.0',\n", - " State(pc_initial=206 nstack_initial=6)),\n", - " ('$phi76.0', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.1': {('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$phi196.1',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi206.1',\n", - " State(pc_initial=206 nstack_initial=6)),\n", - " ('$phi76.1', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.2': {('$phi166.2',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$phi196.2',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi206.2',\n", - " State(pc_initial=206 nstack_initial=6)),\n", - " ('$phi76.2', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$phi166.3',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi168.3',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$phi196.3',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi206.3',\n", - " State(pc_initial=206 nstack_initial=6))},\n", - " '$phi210.4': {('$120compare_op.23',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$176compare_op.8',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$202compare_op.8',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi166.4',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi206.5',\n", - " State(pc_initial=206 nstack_initial=6))},\n", - " '$phi216.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi216.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi220.0': {('$phi216.0',\n", - " State(pc_initial=216 nstack_initial=2))},\n", - " '$phi220.1': {('$phi216.1',\n", - " State(pc_initial=216 nstack_initial=2))},\n", - " '$phi230.0': {('$phi216.0',\n", - " State(pc_initial=216 nstack_initial=2)),\n", - " ('$phi220.0',\n", - " State(pc_initial=220 nstack_initial=2))},\n", - " '$phi230.1': {('$phi216.1',\n", - " State(pc_initial=216 nstack_initial=2)),\n", - " ('$phi220.1',\n", - " State(pc_initial=220 nstack_initial=2))},\n", - " '$phi232.0': {('$phi54.0', State(pc_initial=54 nstack_initial=2))},\n", - " '$phi32.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi232.0',\n", - " State(pc_initial=232 nstack_initial=1))},\n", - " '$phi34.0': {('$phi32.0', State(pc_initial=32 nstack_initial=1))},\n", - " '$phi34.1': {('$32for_iter.2',\n", - " State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.0': {('$phi230.0', State(pc_initial=230 nstack_initial=2)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi54.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2)),\n", - " ('$phi230.1',\n", - " State(pc_initial=230 nstack_initial=2))},\n", - " '$phi56.0': {('$phi54.0', State(pc_initial=54 nstack_initial=2))},\n", - " '$phi56.1': {('$phi54.1', State(pc_initial=54 nstack_initial=2))},\n", - " '$phi56.2': {('$54for_iter.3',\n", - " State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.0': {('$phi210.0', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi74.1': {('$phi210.1', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi74.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3)),\n", - " ('$phi210.2',\n", - " State(pc_initial=210 nstack_initial=5))},\n", - " '$phi76.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi76.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi76.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4',\n", - " State(pc_initial=74 nstack_initial=3))}})\n", - "2024-09-12 10:50:44,162 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi124.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi124.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi124.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi124.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi136.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi136.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi136.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi136.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi152.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi152.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi152.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi162.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi162.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi162.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi162.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.5': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi166.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi166.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi166.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi166.4': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5))},\n", - " '$phi168.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi168.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi168.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi168.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi180.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi180.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi180.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi180.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi196.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi196.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi196.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi206.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi206.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi206.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi206.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.5': {('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi210.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi210.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi210.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.4': {('$120compare_op.23',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$176compare_op.8',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4)),\n", - " ('$202compare_op.8',\n", - " State(pc_initial=196 nstack_initial=5))},\n", - " '$phi216.0': {('$phi210.0',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi216.1': {('$phi210.1',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi220.0': {('$phi210.0',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi220.1': {('$phi210.1',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi230.0': {('$phi210.0',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi230.1': {('$phi210.1',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi232.0': {('$phi230.0',\n", - " State(pc_initial=230 nstack_initial=2)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi32.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi230.0', State(pc_initial=230 nstack_initial=2)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi34.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi230.0', State(pc_initial=230 nstack_initial=2)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi34.1': {('$32for_iter.2',\n", - " State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi210.0', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi54.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2)),\n", - " ('$phi210.1', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi56.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi210.0', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi56.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2)),\n", - " ('$phi210.1', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi56.2': {('$54for_iter.3',\n", - " State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi74.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2)),\n", - " ('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi74.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3)),\n", - " ('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi76.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi76.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi76.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4',\n", - " State(pc_initial=74 nstack_initial=3))}})\n", - "2024-09-12 10:50:44,166 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi124.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi124.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi124.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi124.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi136.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi136.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi136.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi136.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi152.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi152.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi152.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi162.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi162.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi162.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi162.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.5': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi166.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi166.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi166.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi166.4': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5))},\n", - " '$phi168.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi168.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi168.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi168.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi180.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi180.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi180.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi180.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi196.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi196.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi196.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi206.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi206.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi206.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi206.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.5': {('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi210.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi210.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi210.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.4': {('$120compare_op.23',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$176compare_op.8',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4)),\n", - " ('$202compare_op.8',\n", - " State(pc_initial=196 nstack_initial=5))},\n", - " '$phi216.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi216.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi220.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi220.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi230.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi230.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi232.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi32.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.1': {('$32for_iter.2',\n", - " State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi54.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi56.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.2': {('$54for_iter.3',\n", - " State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi74.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi74.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi76.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi76.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4',\n", - " State(pc_initial=74 nstack_initial=3))}})\n", - "2024-09-12 10:50:44,170 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi124.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi124.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi124.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi124.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi136.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi136.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi136.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi136.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi152.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi152.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi152.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi162.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi162.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi162.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi162.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.5': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi166.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi166.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi166.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi166.4': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5))},\n", - " '$phi168.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi168.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi168.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi168.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi180.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi180.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi180.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi180.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi196.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi196.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi196.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi206.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi206.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi206.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi206.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.5': {('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi210.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi210.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi210.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.4': {('$120compare_op.23',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$176compare_op.8',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4)),\n", - " ('$202compare_op.8',\n", - " State(pc_initial=196 nstack_initial=5))},\n", - " '$phi216.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi216.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi220.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi220.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi230.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi230.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi232.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi32.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.1': {('$32for_iter.2',\n", - " State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi54.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi56.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.2': {('$54for_iter.3',\n", - " State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi74.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi74.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi76.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi76.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4',\n", - " State(pc_initial=74 nstack_initial=3))}})\n", - "2024-09-12 10:50:44,184 - numba.core.byteflow - DEBUG - keep phismap: {'$phi152.4': {('$144dup_top.8', State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.4': {('$148compare_op.9', State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8', State(pc_initial=152 nstack_initial=5))},\n", - " '$phi196.4': {('$188dup_top.8', State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.3': {('$match98.12', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.4': {('$120compare_op.23', State(pc_initial=76 nstack_initial=4)),\n", - " ('$148compare_op.9', State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8', State(pc_initial=152 nstack_initial=5)),\n", - " ('$176compare_op.8', State(pc_initial=168 nstack_initial=4)),\n", - " ('$192compare_op.9', State(pc_initial=180 nstack_initial=4)),\n", - " ('$202compare_op.8', State(pc_initial=196 nstack_initial=5))},\n", - " '$phi32.0': {('$30get_iter.13', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.1': {('$32for_iter.2', State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.1': {('$52get_iter.10', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.2': {('$54for_iter.3', State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.2': {('$72get_iter.9', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4', State(pc_initial=74 nstack_initial=3))}}\n", - "2024-09-12 10:50:44,185 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi32.0': '$30get_iter.13'},\n", - " State(pc_initial=32 nstack_initial=1): {'$phi34.1': '$32for_iter.2'},\n", - " State(pc_initial=34 nstack_initial=2): {'$phi54.1': '$52get_iter.10'},\n", - " State(pc_initial=54 nstack_initial=2): {'$phi56.2': '$54for_iter.3'},\n", - " State(pc_initial=56 nstack_initial=3): {'$phi74.2': '$72get_iter.9'},\n", - " State(pc_initial=74 nstack_initial=3): {'$phi76.3': '$74for_iter.4'},\n", - " State(pc_initial=76 nstack_initial=4): {'$phi210.3': '$match98.12',\n", - " '$phi210.4': '$120compare_op.23'},\n", - " State(pc_initial=136 nstack_initial=4): {'$phi152.4': '$144dup_top.8',\n", - " '$phi166.4': '$148compare_op.9',\n", - " '$phi210.4': '$148compare_op.9'},\n", - " State(pc_initial=152 nstack_initial=5): {'$phi166.4': '$158compare_op.8',\n", - " '$phi210.4': '$158compare_op.8'},\n", - " State(pc_initial=168 nstack_initial=4): {'$phi210.4': '$176compare_op.8'},\n", - " State(pc_initial=180 nstack_initial=4): {'$phi196.4': '$188dup_top.8',\n", - " '$phi210.4': '$192compare_op.9'},\n", - " State(pc_initial=196 nstack_initial=5): {'$phi210.4': '$202compare_op.8'}})\n", - "2024-09-12 10:50:44,187 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:44,187 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'item': '$4load_attr.1', 'res': '$6load_attr.2'}), (8, {'item': '$6load_attr.2', 'res': '$8load_method.3'}), (10, {'res': '$10load_global.4'}), (12, {'item': '$10load_global.4', 'res': '$12load_attr.5'}), (14, {'item': '$12load_attr.5', 'res': '$14load_attr.6'}), (16, {'func': '$8load_method.3', 'args': ['$14load_attr.6'], 'res': '$16call_method.7'}), (18, {'value': '$16call_method.7'}), (20, {'res': '$20load_global.8'}), (22, {'res': '$22load_global.9'}), (24, {'res': '$starts24.10'}), (26, {'func': '$22load_global.9', 'args': ['$starts24.10'], 'res': '$26call_function.11'}), (28, {'func': '$20load_global.8', 'args': ['$26call_function.11'], 'res': '$28call_function.12'}), (30, {'value': '$28call_function.12', 'res': '$30get_iter.13'})), outgoing_phis={'$phi32.0': '$30get_iter.13'}, blockstack=(), active_try_block=None, outgoing_edgepushed={32: ('$30get_iter.13',)})\n", - "2024-09-12 10:50:44,188 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=32 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((32, {'iterator': '$phi32.0', 'pair': '$32for_iter.1', 'indval': '$32for_iter.2', 'pred': '$32for_iter.3'}),), outgoing_phis={'$phi34.1': '$32for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={234: (), 34: ('$phi32.0', '$32for_iter.2')})\n", - "2024-09-12 10:50:44,189 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=34 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((34, {'value': '$phi34.1'}), (36, {'res': '$36load_global.2'}), (38, {'res': '$starts38.3'}), (40, {'res': '$i40.4'}), (42, {'index': '$i40.4', 'target': '$starts38.3', 'res': '$42binary_subscr.5'}), (44, {'res': '$stops44.6'}), (46, {'res': '$i46.7'}), (48, {'index': '$i46.7', 'target': '$stops44.6', 'res': '$48binary_subscr.8'}), (50, {'func': '$36load_global.2', 'args': ['$42binary_subscr.5', '$48binary_subscr.8'], 'res': '$50call_function.9'}), (52, {'value': '$50call_function.9', 'res': '$52get_iter.10'})), outgoing_phis={'$phi54.1': '$52get_iter.10'}, blockstack=(), active_try_block=None, outgoing_edgepushed={54: ('$phi34.0', '$52get_iter.10')})\n", - "2024-09-12 10:50:44,189 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((54, {'iterator': '$phi54.1', 'pair': '$54for_iter.2', 'indval': '$54for_iter.3', 'pred': '$54for_iter.4'}),), outgoing_phis={'$phi56.2': '$54for_iter.3'}, blockstack=(), active_try_block=None, outgoing_edgepushed={232: ('$phi54.0',), 56: ('$phi54.0', '$phi54.1', '$54for_iter.3')})\n", - "2024-09-12 10:50:44,190 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((56, {'value': '$phi56.2'}), (58, {'res': '$const58.3'}), (60, {'value': '$const58.3'}), (62, {'res': '$62load_global.4'}), (64, {'res': '$64load_global.5'}), (66, {'res': '$indices66.6'}), (68, {'func': '$64load_global.5', 'args': ['$indices66.6'], 'res': '$68call_function.7'}), (70, {'func': '$62load_global.4', 'args': ['$68call_function.7'], 'res': '$70call_function.8'}), (72, {'value': '$70call_function.8', 'res': '$72get_iter.9'})), outgoing_phis={'$phi74.2': '$72get_iter.9'}, blockstack=(), active_try_block=None, outgoing_edgepushed={74: ('$phi56.0', '$phi56.1', '$72get_iter.9')})\n", - "2024-09-12 10:50:44,191 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((74, {'iterator': '$phi74.2', 'pair': '$74for_iter.3', 'indval': '$74for_iter.4', 'pred': '$74for_iter.5'}),), outgoing_phis={'$phi76.3': '$74for_iter.4'}, blockstack=(), active_try_block=None, outgoing_edgepushed={216: ('$phi74.0', '$phi74.1'), 76: ('$phi74.0', '$phi74.1', '$phi74.2', '$74for_iter.4')})\n", - "2024-09-12 10:50:44,192 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=76 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((76, {'value': '$phi76.3'}), (78, {'res': '$indices78.4'}), (80, {'res': '$k80.5'}), (82, {'index': '$k80.5', 'target': '$indices78.4', 'res': '$82binary_subscr.6'}), (84, {'value': '$82binary_subscr.6'}), (86, {'res': '$coords86.7'}), (88, {'res': '$k88.8'}), (90, {'res': '$j90.9'}), (92, {'items': ['$k88.8', '$j90.9'], 'res': '$92build_tuple.10'}), (94, {'index': '$92build_tuple.10', 'target': '$coords86.7', 'res': '$94binary_subscr.11'}), (96, {'value': '$94binary_subscr.11'}), (98, {'res': '$match98.12'}), (100, {'res': '$elem100.13'}), (102, {'res': '$idx102.14'}), (104, {'res': '$const104.15'}), (106, {'index': '$const104.15', 'target': '$idx102.14', 'res': '$106binary_subscr.16'}), (108, {'lhs': '$elem100.13', 'rhs': '$106binary_subscr.16', 'res': '$108binary_subtract.17'}), (110, {'res': '$idx110.18'}), (112, {'res': '$const112.19'}), (114, {'index': '$const112.19', 'target': '$idx110.18', 'res': '$114binary_subscr.20'}), (116, {'lhs': '$108binary_subtract.17', 'rhs': '$114binary_subscr.20', 'res': '$116binary_modulo.21'}), (118, {'res': '$const118.22'}), (120, {'lhs': '$116binary_modulo.21', 'rhs': '$const118.22', 'res': '$120compare_op.23'}), (122, {'pred': '$120compare_op.23'})), outgoing_phis={'$phi210.4': '$120compare_op.23', '$phi210.3': '$match98.12'}, blockstack=(), active_try_block=None, outgoing_edgepushed={124: ('$phi76.0', '$phi76.1', '$phi76.2', '$match98.12'), 210: ('$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$120compare_op.23')})\n", - "2024-09-12 10:50:44,193 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=124 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((124, {'res': '$idx124.4'}), (126, {'res': '$const126.5'}), (128, {'index': '$const126.5', 'target': '$idx124.4', 'res': '$128binary_subscr.6'}), (130, {'res': '$const130.7'}), (132, {'lhs': '$128binary_subscr.6', 'rhs': '$const130.7', 'res': '$132compare_op.8'}), (134, {'pred': '$132compare_op.8'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={136: ('$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3'), 168: ('$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3')})\n", - "2024-09-12 10:50:44,193 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=136 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((136, {'res': '$idx136.4'}), (138, {'res': '$const138.5'}), (140, {'index': '$const138.5', 'target': '$idx136.4', 'res': '$140binary_subscr.6'}), (142, {'res': '$elem142.7'}), (144, {'orig': ['$elem142.7'], 'duped': ['$144dup_top.8']}), (148, {'lhs': '$140binary_subscr.6', 'rhs': '$elem142.7', 'res': '$148compare_op.9'}), (150, {'pred': '$148compare_op.9'})), outgoing_phis={'$phi210.4': '$148compare_op.9', '$phi166.4': '$148compare_op.9', '$phi152.4': '$144dup_top.8'}, blockstack=(), active_try_block=None, outgoing_edgepushed={152: ('$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8'), 162: ('$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8', '$148compare_op.9')})\n", - "2024-09-12 10:50:44,194 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=152 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((152, {'res': '$idx152.5'}), (154, {'res': '$const154.6'}), (156, {'index': '$const154.6', 'target': '$idx152.5', 'res': '$156binary_subscr.7'}), (158, {'lhs': '$phi152.4', 'rhs': '$156binary_subscr.7', 'res': '$158compare_op.8'}), (160, {})), outgoing_phis={'$phi210.4': '$158compare_op.8', '$phi166.4': '$158compare_op.8'}, blockstack=(), active_try_block=None, outgoing_edgepushed={166: ('$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$158compare_op.8')})\n", - "2024-09-12 10:50:44,194 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=162 nstack_initial=6):\n", - "AdaptBlockInfo(insts=(), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={166: ('$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.5')})\n", - "2024-09-12 10:50:44,195 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=166 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((166, {'pred': '$phi166.4'}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={168: ('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3'), 210: ('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$phi166.4')})\n", - "2024-09-12 10:50:44,196 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=168 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((168, {'res': '$idx168.4'}), (170, {'res': '$const170.5'}), (172, {'index': '$const170.5', 'target': '$idx168.4', 'res': '$172binary_subscr.6'}), (174, {'res': '$const174.7'}), (176, {'lhs': '$172binary_subscr.6', 'rhs': '$const174.7', 'res': '$176compare_op.8'}), (178, {'pred': '$176compare_op.8'})), outgoing_phis={'$phi210.4': '$176compare_op.8'}, blockstack=(), active_try_block=None, outgoing_edgepushed={180: ('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3'), 210: ('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$176compare_op.8')})\n", - "2024-09-12 10:50:44,196 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=180 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((180, {'res': '$idx180.4'}), (182, {'res': '$const182.5'}), (184, {'index': '$const182.5', 'target': '$idx180.4', 'res': '$184binary_subscr.6'}), (186, {'res': '$elem186.7'}), (188, {'orig': ['$elem186.7'], 'duped': ['$188dup_top.8']}), (192, {'lhs': '$184binary_subscr.6', 'rhs': '$elem186.7', 'res': '$192compare_op.9'}), (194, {'pred': '$192compare_op.9'})), outgoing_phis={'$phi196.4': '$188dup_top.8', '$phi210.4': '$192compare_op.9'}, blockstack=(), active_try_block=None, outgoing_edgepushed={196: ('$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8'), 206: ('$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8', '$192compare_op.9')})\n", - "2024-09-12 10:50:44,197 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=196 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((196, {'res': '$idx196.5'}), (198, {'res': '$const198.6'}), (200, {'index': '$const198.6', 'target': '$idx196.5', 'res': '$200binary_subscr.7'}), (202, {'lhs': '$phi196.4', 'rhs': '$200binary_subscr.7', 'res': '$202compare_op.8'}), (204, {})), outgoing_phis={'$phi210.4': '$202compare_op.8'}, blockstack=(), active_try_block=None, outgoing_edgepushed={210: ('$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$202compare_op.8')})\n", - "2024-09-12 10:50:44,198 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=206 nstack_initial=6):\n", - "AdaptBlockInfo(insts=(), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={210: ('$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.5')})\n", - "2024-09-12 10:50:44,198 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=210 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((210, {'lhs': '$phi210.3', 'rhs': '$phi210.4', 'res': '$210inplace_and.5'}), (212, {'value': '$210inplace_and.5'}), (214, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={74: ('$phi210.0', '$phi210.1', '$phi210.2')})\n", - "2024-09-12 10:50:44,199 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=216 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((216, {'res': '$match216.2'}), (218, {'pred': '$match216.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={220: ('$phi216.0', '$phi216.1'), 230: ('$phi216.0', '$phi216.1')})\n", - "2024-09-12 10:50:44,200 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=220 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((220, {'res': '$mask220.2'}), (222, {'item': '$mask220.2', 'res': '$222load_method.3'}), (224, {'res': '$j224.4'}), (226, {'func': '$222load_method.3', 'args': ['$j224.4'], 'res': '$226call_method.5'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={230: ('$phi220.0', '$phi220.1')})\n", - "2024-09-12 10:50:44,201 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=230 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((230, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={54: ('$phi230.0', '$phi230.1')})\n", - "2024-09-12 10:50:44,201 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=232 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((232, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={32: ('$phi232.0',)})\n", - "2024-09-12 10:50:44,202 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=234 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((234, {'res': '$mask234.0'}), (236, {'retval': '$mask234.0', 'castval': '$236return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:44,211 - numba.core.interpreter - DEBUG - label 0:\n", - " starts = arg(0, name=starts) ['starts']\n", - " stops = arg(1, name=stops) ['stops']\n", - " coords = arg(2, name=coords) ['coords']\n", - " indices = arg(3, name=indices) ['indices']\n", - " $2load_global.0 = global(numba: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=typed) ['$2load_global.0', '$4load_attr.1']\n", - " $6load_attr.2 = getattr(value=$4load_attr.1, attr=List) ['$4load_attr.1', '$6load_attr.2']\n", - " $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list) ['$6load_attr.2', '$8load_method.3']\n", - " $10load_global.4 = global(numba: ) ['$10load_global.4']\n", - " $12load_attr.5 = getattr(value=$10load_global.4, attr=types) ['$10load_global.4', '$12load_attr.5']\n", - " $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp) ['$12load_attr.5', '$14load_attr.6']\n", - " mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None) ['$14load_attr.6', '$8load_method.3', 'mask']\n", - " $20load_global.8 = global(range: ) ['$20load_global.8']\n", - " $22load_global.9 = global(len: ) ['$22load_global.9']\n", - " $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None) ['$22load_global.9', '$26call_function.11', 'starts']\n", - " $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None) ['$20load_global.8', '$26call_function.11', '$28call_function.12']\n", - " $30get_iter.13 = getiter(value=$28call_function.12) ['$28call_function.12', '$30get_iter.13']\n", - " $phi32.0 = $30get_iter.13 ['$30get_iter.13', '$phi32.0']\n", - " jump 32 []\n", - "label 32:\n", - " $32for_iter.1 = iternext(value=$phi32.0) ['$32for_iter.1', '$phi32.0']\n", - " $32for_iter.2 = pair_first(value=$32for_iter.1) ['$32for_iter.1', '$32for_iter.2']\n", - " $32for_iter.3 = pair_second(value=$32for_iter.1) ['$32for_iter.1', '$32for_iter.3']\n", - " $phi34.1 = $32for_iter.2 ['$32for_iter.2', '$phi34.1']\n", - " branch $32for_iter.3, 34, 234 ['$32for_iter.3']\n", - "label 34:\n", - " i = $phi34.1 ['$phi34.1', 'i']\n", - " $36load_global.2 = global(range: ) ['$36load_global.2']\n", - " $42binary_subscr.5 = getitem(value=starts, index=i, fn=) ['$42binary_subscr.5', 'i', 'starts']\n", - " $48binary_subscr.8 = getitem(value=stops, index=i, fn=) ['$48binary_subscr.8', 'i', 'stops']\n", - " $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None) ['$36load_global.2', '$42binary_subscr.5', '$48binary_subscr.8', '$50call_function.9']\n", - " $52get_iter.10 = getiter(value=$50call_function.9) ['$50call_function.9', '$52get_iter.10']\n", - " $phi54.1 = $52get_iter.10 ['$52get_iter.10', '$phi54.1']\n", - " jump 54 []\n", - "label 54:\n", - " $54for_iter.2 = iternext(value=$phi54.1) ['$54for_iter.2', '$phi54.1']\n", - " $54for_iter.3 = pair_first(value=$54for_iter.2) ['$54for_iter.2', '$54for_iter.3']\n", - " $54for_iter.4 = pair_second(value=$54for_iter.2) ['$54for_iter.2', '$54for_iter.4']\n", - " $phi56.2 = $54for_iter.3 ['$54for_iter.3', '$phi56.2']\n", - " branch $54for_iter.4, 56, 232 ['$54for_iter.4']\n", - "label 56:\n", - " j = $phi56.2 ['$phi56.2', 'j']\n", - " match = const(bool, True) ['match']\n", - " $62load_global.4 = global(range: ) ['$62load_global.4']\n", - " $64load_global.5 = global(len: ) ['$64load_global.5']\n", - " $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None) ['$64load_global.5', '$68call_function.7', 'indices']\n", - " $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None) ['$62load_global.4', '$68call_function.7', '$70call_function.8']\n", - " $72get_iter.9 = getiter(value=$70call_function.8) ['$70call_function.8', '$72get_iter.9']\n", - " $phi74.2 = $72get_iter.9 ['$72get_iter.9', '$phi74.2']\n", - " jump 74 []\n", - "label 74:\n", - " $74for_iter.3 = iternext(value=$phi74.2) ['$74for_iter.3', '$phi74.2']\n", - " $74for_iter.4 = pair_first(value=$74for_iter.3) ['$74for_iter.3', '$74for_iter.4']\n", - " $74for_iter.5 = pair_second(value=$74for_iter.3) ['$74for_iter.3', '$74for_iter.5']\n", - " $phi76.3 = $74for_iter.4 ['$74for_iter.4', '$phi76.3']\n", - " branch $74for_iter.5, 76, 216 ['$74for_iter.5']\n", - "label 76:\n", - " k = $phi76.3 ['$phi76.3', 'k']\n", - " idx = getitem(value=indices, index=k, fn=) ['idx', 'indices', 'k']\n", - " $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)]) ['$92build_tuple.10', 'j', 'k']\n", - " elem = getitem(value=coords, index=$92build_tuple.10, fn=) ['$92build_tuple.10', 'coords', 'elem']\n", - " $const104.15 = const(int, 0) ['$const104.15']\n", - " $106binary_subscr.16 = getitem(value=idx, index=$const104.15, fn=) ['$106binary_subscr.16', '$const104.15', 'idx']\n", - " $108binary_subtract.17 = elem - $106binary_subscr.16 ['$106binary_subscr.16', '$108binary_subtract.17', 'elem']\n", - " $const112.19 = const(int, 2) ['$const112.19']\n", - " $114binary_subscr.20 = getitem(value=idx, index=$const112.19, fn=) ['$114binary_subscr.20', '$const112.19', 'idx']\n", - " $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20 ['$108binary_subtract.17', '$114binary_subscr.20', '$116binary_modulo.21']\n", - " $const118.22 = const(int, 0) ['$const118.22']\n", - " $120compare_op.23 = $116binary_modulo.21 == $const118.22 ['$116binary_modulo.21', '$120compare_op.23', '$const118.22']\n", - " bool122 = global(bool: ) ['bool122']\n", - " $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None) ['$120compare_op.23', '$122pred', 'bool122']\n", - " $phi210.4 = $120compare_op.23 ['$120compare_op.23', '$phi210.4']\n", - " $phi210.3 = match ['$phi210.3', 'match']\n", - " branch $122pred, 124, 210 ['$122pred']\n", - "label 124:\n", - " $const126.5 = const(int, 2) ['$const126.5']\n", - " $128binary_subscr.6 = getitem(value=idx, index=$const126.5, fn=) ['$128binary_subscr.6', '$const126.5', 'idx']\n", - " $const130.7 = const(int, 0) ['$const130.7']\n", - " $132compare_op.8 = $128binary_subscr.6 > $const130.7 ['$128binary_subscr.6', '$132compare_op.8', '$const130.7']\n", - " bool134 = global(bool: ) ['bool134']\n", - " $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$132compare_op.8', '$134pred', 'bool134']\n", - " branch $134pred, 136, 168 ['$134pred']\n", - "label 136:\n", - " $const138.5 = const(int, 0) ['$const138.5']\n", - " $140binary_subscr.6 = getitem(value=idx, index=$const138.5, fn=) ['$140binary_subscr.6', '$const138.5', 'idx']\n", - " $148compare_op.9 = $140binary_subscr.6 <= elem ['$140binary_subscr.6', '$148compare_op.9', 'elem']\n", - " bool150 = global(bool: ) ['bool150']\n", - " $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$148compare_op.9', '$150pred', 'bool150']\n", - " $phi210.4 = $148compare_op.9 ['$148compare_op.9', '$phi210.4']\n", - " $phi166.4 = $148compare_op.9 ['$148compare_op.9', '$phi166.4']\n", - " $phi152.4 = elem ['$phi152.4', 'elem']\n", - " branch $150pred, 152, 162 ['$150pred']\n", - "label 152:\n", - " $const154.6 = const(int, 1) ['$const154.6']\n", - " $156binary_subscr.7 = getitem(value=idx, index=$const154.6, fn=) ['$156binary_subscr.7', '$const154.6', 'idx']\n", - " $158compare_op.8 = $phi152.4 < $156binary_subscr.7 ['$156binary_subscr.7', '$158compare_op.8', '$phi152.4']\n", - " $phi210.4 = $158compare_op.8 ['$158compare_op.8', '$phi210.4']\n", - " $phi166.4 = $158compare_op.8 ['$158compare_op.8', '$phi166.4']\n", - " jump 166 []\n", - "label 162:\n", - " jump 166 []\n", - "label 166:\n", - " bool166 = global(bool: ) ['bool166']\n", - " $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$166pred', '$phi166.4', 'bool166']\n", - " branch $166pred, 210, 168 ['$166pred']\n", - "label 168:\n", - " $const170.5 = const(int, 2) ['$const170.5']\n", - " $172binary_subscr.6 = getitem(value=idx, index=$const170.5, fn=) ['$172binary_subscr.6', '$const170.5', 'idx']\n", - " $const174.7 = const(int, 0) ['$const174.7']\n", - " $176compare_op.8 = $172binary_subscr.6 < $const174.7 ['$172binary_subscr.6', '$176compare_op.8', '$const174.7']\n", - " bool178 = global(bool: ) ['bool178']\n", - " $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$176compare_op.8', '$178pred', 'bool178']\n", - " $phi210.4 = $176compare_op.8 ['$176compare_op.8', '$phi210.4']\n", - " branch $178pred, 180, 210 ['$178pred']\n", - "label 180:\n", - " $const182.5 = const(int, 0) ['$const182.5']\n", - " $184binary_subscr.6 = getitem(value=idx, index=$const182.5, fn=) ['$184binary_subscr.6', '$const182.5', 'idx']\n", - " $192compare_op.9 = $184binary_subscr.6 >= elem ['$184binary_subscr.6', '$192compare_op.9', 'elem']\n", - " bool194 = global(bool: ) ['bool194']\n", - " $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$192compare_op.9', '$194pred', 'bool194']\n", - " $phi196.4 = elem ['$phi196.4', 'elem']\n", - " $phi210.4 = $192compare_op.9 ['$192compare_op.9', '$phi210.4']\n", - " branch $194pred, 196, 206 ['$194pred']\n", - "label 196:\n", - " $const198.6 = const(int, 1) ['$const198.6']\n", - " $200binary_subscr.7 = getitem(value=idx, index=$const198.6, fn=) ['$200binary_subscr.7', '$const198.6', 'idx']\n", - " $202compare_op.8 = $phi196.4 > $200binary_subscr.7 ['$200binary_subscr.7', '$202compare_op.8', '$phi196.4']\n", - " $phi210.4 = $202compare_op.8 ['$202compare_op.8', '$phi210.4']\n", - " jump 210 []\n", - "label 206:\n", - " jump 210 []\n", - "label 210:\n", - " match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined) ['$phi210.3', '$phi210.4', 'match']\n", - " jump 74 []\n", - "label 216:\n", - " bool218 = global(bool: ) ['bool218']\n", - " $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None) ['$218pred', 'bool218', 'match']\n", - " branch $218pred, 220, 230 ['$218pred']\n", - "label 220:\n", - " $222load_method.3 = getattr(value=mask, attr=append) ['$222load_method.3', 'mask']\n", - " $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None) ['$222load_method.3', '$226call_method.5', 'j']\n", - " jump 230 []\n", - "label 230:\n", - " jump 54 []\n", - "label 232:\n", - " jump 32 []\n", - "label 234:\n", - " $236return_value.1 = cast(value=mask) ['$236return_value.1', 'mask']\n", - " return $236return_value.1 ['$236return_value.1']\n", - "\n", - "2024-09-12 10:50:44,262 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:44,263 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,264 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:44,265 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:44,265 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:44,266 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:44,267 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:44,268 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:44,268 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:44,269 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:44,269 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:44,270 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:44,271 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:44,272 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,272 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:44,273 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:44,274 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,274 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,275 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:44,276 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:44,276 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,277 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 32\n", - "2024-09-12 10:50:44,278 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,278 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:44,279 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,280 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,280 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:44,281 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:44,282 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 34\n", - "2024-09-12 10:50:44,282 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,283 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:44,284 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:44,284 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:44,285 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:44,286 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,286 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:44,287 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:44,288 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,288 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-09-12 10:50:44,289 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,290 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:44,291 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,291 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,292 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:44,292 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:44,293 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-09-12 10:50:44,294 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,295 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:44,295 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:44,296 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:44,296 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:44,297 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,298 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,299 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:44,300 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:44,300 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,301 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-09-12 10:50:44,302 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,302 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:44,303 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,304 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,304 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:44,305 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:44,306 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 76\n", - "2024-09-12 10:50:44,306 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,307 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:44,308 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:44,308 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:44,309 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:44,310 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:44,310 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:44,311 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:44,312 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:44,312 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:44,313 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:44,314 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:44,314 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:44,315 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:44,316 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,316 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:44,317 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:44,318 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:44,318 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 124\n", - "2024-09-12 10:50:44,319 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,320 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:44,320 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:44,321 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:44,322 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:44,323 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:44,344 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,344 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:44,345 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 136\n", - "2024-09-12 10:50:44,345 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,346 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:44,347 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:44,347 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:44,348 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:44,348 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,349 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,350 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,350 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:44,351 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:44,351 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 152\n", - "2024-09-12 10:50:44,352 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,353 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:44,353 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:44,354 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:44,355 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $158compare_op.8\n", - "2024-09-12 10:50:44,355 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $158compare_op.8\n", - "2024-09-12 10:50:44,356 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,356 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 162\n", - "2024-09-12 10:50:44,357 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,357 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,358 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 166\n", - "2024-09-12 10:50:44,359 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,359 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:44,360 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,361 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:44,365 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 168\n", - "2024-09-12 10:50:44,366 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,366 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:44,367 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:44,367 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:44,368 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:44,369 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:44,369 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,370 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $176compare_op.8\n", - "2024-09-12 10:50:44,370 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:44,371 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 180\n", - "2024-09-12 10:50:44,372 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,372 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:44,373 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:44,373 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:44,374 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:44,375 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,375 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:44,376 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $192compare_op.9\n", - "2024-09-12 10:50:44,376 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:44,377 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 196\n", - "2024-09-12 10:50:44,378 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,378 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:44,379 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:44,379 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:44,380 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $202compare_op.8\n", - "2024-09-12 10:50:44,381 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,381 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 206\n", - "2024-09-12 10:50:44,382 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,382 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,383 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 210\n", - "2024-09-12 10:50:44,384 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,384 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:44,385 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,385 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 216\n", - "2024-09-12 10:50:44,386 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,387 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:44,387 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,388 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:44,388 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 220\n", - "2024-09-12 10:50:44,389 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,389 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:44,390 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,391 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:44,391 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 230\n", - "2024-09-12 10:50:44,392 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,392 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,393 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 232\n", - "2024-09-12 10:50:44,393 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,394 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,395 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 234\n", - "2024-09-12 10:50:44,395 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,396 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:44,396 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:44,407 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$106binary_subscr.16': [],\n", - " '$108binary_subtract.17': [],\n", - " '$10load_global.4': [],\n", - " '$114binary_subscr.20': [],\n", - " '$116binary_modulo.21': [],\n", - " '$120compare_op.23': [],\n", - " '$122pred': [],\n", - " '$128binary_subscr.6': [],\n", - " '$12load_attr.5': [],\n", - " '$132compare_op.8': [],\n", - " '$134pred': [],\n", - " '$140binary_subscr.6': [],\n", - " '$148compare_op.9': [],\n", - " '$14load_attr.6': [],\n", - " '$150pred': [],\n", - " '$156binary_subscr.7': [],\n", - " '$158compare_op.8': [],\n", - " '$166pred': [],\n", - " '$172binary_subscr.6': [],\n", - " '$176compare_op.8': [],\n", - " '$178pred': [],\n", - " '$184binary_subscr.6': [],\n", - " '$192compare_op.9': [],\n", - " '$194pred': [],\n", - " '$200binary_subscr.7': [],\n", - " '$202compare_op.8': [],\n", - " '$20load_global.8': [],\n", - " '$218pred': [],\n", - " '$222load_method.3': [],\n", - " '$226call_method.5': [],\n", - " '$22load_global.9': [],\n", - " '$236return_value.1': [],\n", - " '$26call_function.11': [],\n", - " '$28call_function.12': [],\n", - " '$2load_global.0': [],\n", - " '$30get_iter.13': [],\n", - " '$32for_iter.1': [],\n", - " '$32for_iter.2': [],\n", - " '$32for_iter.3': [],\n", - " '$36load_global.2': [],\n", - " '$42binary_subscr.5': [],\n", - " '$48binary_subscr.8': [],\n", - " '$4load_attr.1': [],\n", - " '$50call_function.9': [],\n", - " '$52get_iter.10': [],\n", - " '$54for_iter.2': [],\n", - " '$54for_iter.3': [],\n", - " '$54for_iter.4': [],\n", - " '$62load_global.4': [],\n", - " '$64load_global.5': [],\n", - " '$68call_function.7': [],\n", - " '$6load_attr.2': [],\n", - " '$70call_function.8': [],\n", - " '$72get_iter.9': [],\n", - " '$74for_iter.3': [],\n", - " '$74for_iter.4': [],\n", - " '$74for_iter.5': [],\n", - " '$8load_method.3': [],\n", - " '$92build_tuple.10': [],\n", - " '$const104.15': [],\n", - " '$const112.19': [],\n", - " '$const118.22': [],\n", - " '$const126.5': [],\n", - " '$const130.7': [],\n", - " '$const138.5': [],\n", - " '$const154.6': [],\n", - " '$const170.5': [],\n", - " '$const174.7': [],\n", - " '$const182.5': [],\n", - " '$const198.6': [],\n", - " '$phi152.4': [],\n", - " '$phi166.4': [,\n", - " ],\n", - " '$phi196.4': [],\n", - " '$phi210.3': [],\n", - " '$phi210.4': [,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ],\n", - " '$phi32.0': [],\n", - " '$phi34.1': [],\n", - " '$phi54.1': [],\n", - " '$phi56.2': [],\n", - " '$phi74.2': [],\n", - " '$phi76.3': [],\n", - " 'bool122': [],\n", - " 'bool134': [],\n", - " 'bool150': [],\n", - " 'bool166': [],\n", - " 'bool178': [],\n", - " 'bool194': [],\n", - " 'bool218': [],\n", - " 'coords': [],\n", - " 'elem': [],\n", - " 'i': [],\n", - " 'idx': [],\n", - " 'indices': [],\n", - " 'j': [],\n", - " 'k': [],\n", - " 'mask': [],\n", - " 'match': [,\n", - " ],\n", - " 'starts': [],\n", - " 'stops': []})\n", - "2024-09-12 10:50:44,408 - numba.core.ssa - DEBUG - SSA violators {'$phi210.4', '$phi166.4', 'match'}\n", - "2024-09-12 10:50:44,409 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi210.4\n", - "2024-09-12 10:50:44,409 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:44,410 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,410 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:44,411 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:44,411 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:44,412 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:44,413 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:44,413 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:44,414 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:44,414 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:44,415 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:44,415 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:44,416 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:44,419 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,419 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:44,420 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:44,420 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,421 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,422 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:44,422 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:44,423 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,423 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:44,424 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,424 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:44,425 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,425 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,428 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:44,428 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:44,429 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:44,429 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,430 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:44,431 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:44,432 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:44,432 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:44,433 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,434 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:44,435 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:44,435 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,436 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:44,436 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,437 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:44,437 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,438 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,438 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:44,439 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:44,441 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:44,441 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,442 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:44,443 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:44,443 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:44,444 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:44,444 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,445 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,445 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:44,446 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:44,446 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,447 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:44,448 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,449 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:44,449 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,450 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,452 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:44,453 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:44,453 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:44,454 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,454 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:44,455 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:44,455 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:44,456 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:44,457 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:44,457 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:44,458 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:44,459 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:44,460 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:44,461 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:44,461 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:44,462 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:44,462 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:44,463 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,463 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:44,464 - numba.core.ssa - DEBUG - first assign: $phi210.4\n", - "2024-09-12 10:50:44,466 - numba.core.ssa - DEBUG - replaced with: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:44,466 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:44,467 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:44,467 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:44,468 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,468 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:44,469 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:44,469 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:44,470 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:44,471 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:44,471 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,472 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:44,472 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:44,473 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,473 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:44,474 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:44,474 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:44,475 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:44,475 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,476 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,477 - numba.core.ssa - DEBUG - replaced with: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:44,477 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,478 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:44,478 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:44,479 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:44,479 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,480 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:44,480 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:44,481 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:44,481 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $158compare_op.8\n", - "2024-09-12 10:50:44,482 - numba.core.ssa - DEBUG - replaced with: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:44,483 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $158compare_op.8\n", - "2024-09-12 10:50:44,487 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,488 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:44,488 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,489 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,489 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:44,490 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,490 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:44,491 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,491 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:44,492 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:44,492 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,493 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:44,493 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:44,496 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:44,496 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:44,497 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:44,497 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,498 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $176compare_op.8\n", - "2024-09-12 10:50:44,499 - numba.core.ssa - DEBUG - replaced with: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:44,500 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:44,500 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:44,501 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,501 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:44,502 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:44,502 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:44,503 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:44,503 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,504 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:44,504 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $192compare_op.9\n", - "2024-09-12 10:50:44,505 - numba.core.ssa - DEBUG - replaced with: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:44,505 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:44,506 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:44,508 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,509 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:44,509 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:44,510 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:44,510 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $202compare_op.8\n", - "2024-09-12 10:50:44,511 - numba.core.ssa - DEBUG - replaced with: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:44,511 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,512 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:44,512 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,513 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,513 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:44,514 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,514 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:44,516 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,517 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:44,517 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,518 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:44,519 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,520 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:44,520 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:44,521 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,522 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:44,522 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,523 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:44,524 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:44,524 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,525 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,525 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:44,526 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,526 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,527 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:44,527 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,528 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:44,528 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:44,529 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {76: [],\n", - " 136: [],\n", - " 152: [],\n", - " 168: [],\n", - " 180: [],\n", - " 196: []})\n", - "2024-09-12 10:50:44,530 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:44,530 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,531 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:44,531 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:44,532 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:44,532 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:44,533 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:44,533 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:44,534 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:44,534 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:44,537 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:44,538 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:44,538 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:44,539 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,539 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:44,540 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:44,540 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,541 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,542 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:44,543 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:44,544 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,544 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:44,545 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,545 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:44,546 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,546 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,547 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:44,547 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:44,548 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:44,548 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,549 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:44,549 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:44,551 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:44,552 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:44,552 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,553 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:44,554 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:44,554 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,555 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:44,556 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,557 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:44,557 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,558 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,558 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:44,558 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:44,559 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:44,560 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,561 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:44,561 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:44,562 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:44,562 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:44,563 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,564 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,565 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:44,566 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:44,566 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,567 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:44,567 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,568 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:44,569 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,569 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,570 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:44,570 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:44,571 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:44,572 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,572 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:44,573 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:44,574 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:44,574 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:44,575 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:44,576 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:44,576 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:44,577 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:44,577 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:44,578 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:44,579 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:44,580 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:44,580 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:44,581 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,582 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:44,582 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:44,583 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:44,583 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:44,584 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,584 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:44,585 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:44,585 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:44,586 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:44,586 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:44,588 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,588 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:44,589 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:44,589 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,591 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:44,591 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:44,592 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:44,592 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:44,593 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,594 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:44,594 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,595 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:44,596 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:44,596 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:44,597 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,597 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:44,598 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:44,599 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:44,599 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:44,600 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $158compare_op.8\n", - "2024-09-12 10:50:44,600 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,601 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:44,602 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,602 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,603 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:44,603 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,604 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:44,604 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,605 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:44,605 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:44,606 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,606 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:44,607 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:44,607 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:44,608 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:44,610 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:44,610 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,611 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:44,611 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:44,612 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:44,613 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,613 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:44,614 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:44,614 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:44,615 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:44,615 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,616 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:44,617 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:44,618 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:44,618 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:44,619 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,619 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:44,620 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:44,620 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:44,621 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:44,622 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,622 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:44,623 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,624 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,624 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:44,625 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,625 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:44,626 - numba.core.ssa - DEBUG - find_def var='$phi210.4' stmt=match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:44,627 - numba.core.ssa - DEBUG - find_def_from_top label 210\n", - "2024-09-12 10:50:44,628 - numba.core.ssa - DEBUG - insert phi node $phi210.4.6 = phi(incoming_values=[], incoming_blocks=[]) at 210\n", - "2024-09-12 10:50:44,628 - numba.core.ssa - DEBUG - find_def_from_bottom label 196\n", - "2024-09-12 10:50:44,629 - numba.core.ssa - DEBUG - incoming_def $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:44,629 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-09-12 10:50:44,630 - numba.core.ssa - DEBUG - find_def_from_top label 166\n", - "2024-09-12 10:50:44,631 - numba.core.ssa - DEBUG - insert phi node $phi210.4.7 = phi(incoming_values=[], incoming_blocks=[]) at 166\n", - "2024-09-12 10:50:44,631 - numba.core.ssa - DEBUG - find_def_from_bottom label 152\n", - "2024-09-12 10:50:44,632 - numba.core.ssa - DEBUG - incoming_def $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:44,633 - numba.core.ssa - DEBUG - find_def_from_bottom label 162\n", - "2024-09-12 10:50:44,633 - numba.core.ssa - DEBUG - find_def_from_top label 162\n", - "2024-09-12 10:50:44,634 - numba.core.ssa - DEBUG - idom 136 from label 162\n", - "2024-09-12 10:50:44,634 - numba.core.ssa - DEBUG - find_def_from_bottom label 136\n", - "2024-09-12 10:50:44,635 - numba.core.ssa - DEBUG - incoming_def $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:44,636 - numba.core.ssa - DEBUG - incoming_def $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:44,636 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-09-12 10:50:44,637 - numba.core.ssa - DEBUG - incoming_def $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:44,637 - numba.core.ssa - DEBUG - find_def_from_bottom label 76\n", - "2024-09-12 10:50:44,638 - numba.core.ssa - DEBUG - incoming_def $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:44,639 - numba.core.ssa - DEBUG - find_def_from_bottom label 206\n", - "2024-09-12 10:50:44,639 - numba.core.ssa - DEBUG - find_def_from_top label 206\n", - "2024-09-12 10:50:44,640 - numba.core.ssa - DEBUG - idom 180 from label 206\n", - "2024-09-12 10:50:44,641 - numba.core.ssa - DEBUG - find_def_from_bottom label 180\n", - "2024-09-12 10:50:44,641 - numba.core.ssa - DEBUG - incoming_def $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:44,642 - numba.core.ssa - DEBUG - replaced with: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:44,642 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,643 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:44,644 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,644 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:44,645 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,645 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:44,646 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:44,647 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,647 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:44,648 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,648 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:44,649 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:44,650 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,650 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,651 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:44,651 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,652 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,653 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:44,653 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,654 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:44,654 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:44,655 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi166.4\n", - "2024-09-12 10:50:44,656 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:44,656 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,657 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:44,658 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:44,658 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:44,659 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:44,659 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:44,660 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:44,661 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:44,661 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:44,662 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:44,662 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:44,663 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:44,664 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,664 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:44,665 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:44,665 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,666 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,667 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:44,667 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:44,668 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,668 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:44,669 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,669 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:44,670 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,670 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,671 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:44,671 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:44,673 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:44,673 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,673 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:44,674 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:44,674 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:44,675 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:44,675 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,677 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:44,677 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:44,678 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,678 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:44,678 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,679 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:44,679 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,680 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,680 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:44,681 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:44,682 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:44,683 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,683 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:44,684 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:44,685 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:44,685 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:44,685 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,686 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,686 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:44,687 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:44,687 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,688 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:44,688 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,689 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:44,689 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,690 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,690 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:44,691 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:44,691 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:44,692 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,692 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:44,692 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:44,693 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:44,693 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:44,696 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:44,696 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:44,697 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:44,697 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:44,698 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:44,698 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:44,699 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:44,700 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:44,700 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:44,701 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,701 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:44,702 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:44,703 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:44,703 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:44,704 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,704 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:44,705 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:44,705 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:44,706 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:44,707 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:44,707 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,708 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:44,708 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:44,709 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,709 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:44,710 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:44,710 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:44,711 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:44,711 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,713 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:44,713 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,714 - numba.core.ssa - DEBUG - first assign: $phi166.4\n", - "2024-09-12 10:50:44,714 - numba.core.ssa - DEBUG - replaced with: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,715 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:44,715 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:44,715 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:44,716 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,716 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:44,717 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:44,718 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:44,719 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:44,719 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $158compare_op.8\n", - "2024-09-12 10:50:44,720 - numba.core.ssa - DEBUG - replaced with: $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:44,720 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,721 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:44,721 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,722 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,722 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:44,722 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,723 - numba.core.ssa - DEBUG - on stmt: $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:44,723 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:44,724 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,726 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:44,726 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:44,727 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,727 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:44,728 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:44,728 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:44,729 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:44,730 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:44,730 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,731 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:44,732 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:44,732 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:44,733 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,733 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:44,734 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:44,735 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:44,735 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:44,736 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,736 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:44,737 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:44,737 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:44,738 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:44,738 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,739 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:44,740 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:44,741 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:44,741 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:44,741 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,742 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:44,743 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,743 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,744 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:44,744 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,745 - numba.core.ssa - DEBUG - on stmt: $phi210.4.6 = phi(incoming_values=[Var($phi210.4.5, indexing.py:600), Var($phi210.4.7, indexing.py:599), Var($phi210.4.3, indexing.py:600), Var($phi210.4, indexing.py:599), Var($phi210.4.4, indexing.py:600)], incoming_blocks=[196, 166, 168, 76, 206])\n", - "2024-09-12 10:50:44,745 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:44,747 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,747 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:44,748 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,748 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:44,749 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,750 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:44,750 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:44,750 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,751 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:44,752 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,752 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:44,753 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:44,753 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,754 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,754 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:44,755 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,755 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,756 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:44,756 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,757 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:44,757 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:44,758 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {136: [],\n", - " 152: []})\n", - "2024-09-12 10:50:44,758 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:44,760 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,761 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:44,761 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:44,762 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:44,762 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:44,763 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:44,764 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:44,764 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:44,765 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:44,765 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:44,766 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:44,766 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:44,767 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,768 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:44,768 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:44,769 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,769 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,770 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:44,771 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:44,771 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,772 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:44,772 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,773 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:44,774 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,774 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,775 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:44,776 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:44,776 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:44,777 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,777 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:44,778 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:44,778 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:44,779 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:44,780 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,780 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:44,781 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:44,782 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,782 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:44,783 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,783 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:44,784 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,784 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,785 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:44,786 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:44,786 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:44,787 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,788 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:44,788 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:44,788 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:44,789 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:44,789 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,790 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,791 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:44,792 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:44,792 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,793 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:44,793 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,794 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:44,795 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,795 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,796 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:44,796 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:44,797 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:44,797 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,798 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:44,798 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:44,799 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:44,800 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:44,801 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:44,801 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:44,802 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:44,802 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:44,803 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:44,803 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:44,804 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:44,805 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:44,805 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:44,806 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,807 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:44,807 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:44,808 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:44,808 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:44,809 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,809 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:44,810 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:44,810 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:44,811 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:44,811 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:44,812 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,812 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:44,813 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:44,814 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,815 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:44,815 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:44,816 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:44,816 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:44,817 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,817 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:44,818 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,819 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:44,819 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:44,820 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:44,820 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,821 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:44,821 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:44,822 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:44,822 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:44,822 - numba.core.ssa - DEBUG - on stmt: $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:44,823 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,823 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:44,824 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,824 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,825 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:44,825 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,826 - numba.core.ssa - DEBUG - on stmt: $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:44,826 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:44,827 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,827 - numba.core.ssa - DEBUG - find_def var='$phi166.4' stmt=$166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,828 - numba.core.ssa - DEBUG - find_def_from_top label 166\n", - "2024-09-12 10:50:44,828 - numba.core.ssa - DEBUG - insert phi node $phi166.4.2 = phi(incoming_values=[], incoming_blocks=[]) at 166\n", - "2024-09-12 10:50:44,831 - numba.core.ssa - DEBUG - find_def_from_bottom label 152\n", - "2024-09-12 10:50:44,831 - numba.core.ssa - DEBUG - incoming_def $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:44,832 - numba.core.ssa - DEBUG - find_def_from_bottom label 162\n", - "2024-09-12 10:50:44,832 - numba.core.ssa - DEBUG - find_def_from_top label 162\n", - "2024-09-12 10:50:44,833 - numba.core.ssa - DEBUG - idom 136 from label 162\n", - "2024-09-12 10:50:44,833 - numba.core.ssa - DEBUG - find_def_from_bottom label 136\n", - "2024-09-12 10:50:44,833 - numba.core.ssa - DEBUG - incoming_def $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,835 - numba.core.ssa - DEBUG - replaced with: $166pred = call bool166($phi166.4.2, func=bool166, args=(Var($phi166.4.2, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,835 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:44,836 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:44,836 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,837 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:44,837 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:44,838 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:44,838 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:44,839 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:44,839 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,841 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:44,841 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:44,842 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:44,842 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,843 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:44,844 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:44,844 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:44,845 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:44,845 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,846 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:44,846 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:44,846 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:44,847 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:44,847 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,849 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:44,849 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:44,850 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:44,850 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:44,851 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,851 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:44,852 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,853 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,853 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:44,854 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,854 - numba.core.ssa - DEBUG - on stmt: $phi210.4.6 = phi(incoming_values=[Var($phi210.4.5, indexing.py:600), Var($phi210.4.7, indexing.py:599), Var($phi210.4.3, indexing.py:600), Var($phi210.4, indexing.py:599), Var($phi210.4.4, indexing.py:600)], incoming_blocks=[196, 166, 168, 76, 206])\n", - "2024-09-12 10:50:44,855 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:44,856 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,857 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:44,857 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,858 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:44,858 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,859 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:44,860 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:44,860 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,861 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:44,862 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,862 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:44,863 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:44,863 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,864 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,864 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:44,865 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,866 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,866 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:44,867 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,868 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:44,868 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:44,869 - numba.core.ssa - DEBUG - Fix SSA violator on var match\n", - "2024-09-12 10:50:44,869 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:44,870 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,871 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:44,871 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:44,872 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:44,872 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:44,873 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:44,873 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:44,874 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:44,875 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:44,875 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:44,876 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:44,877 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:44,877 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,878 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:44,878 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:44,879 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,880 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,880 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:44,881 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:44,882 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,882 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:44,883 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,883 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:44,884 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,884 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,884 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:44,885 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:44,885 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:44,886 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,887 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:44,888 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:44,888 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:44,889 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:44,890 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,890 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:44,891 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:44,891 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,891 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:44,892 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,892 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:44,893 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,894 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:44,895 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:44,895 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:44,896 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:44,896 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,897 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:44,897 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:44,898 - numba.core.ssa - DEBUG - first assign: match\n", - "2024-09-12 10:50:44,898 - numba.core.ssa - DEBUG - replaced with: match = const(bool, True)\n", - "2024-09-12 10:50:44,899 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:44,900 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:44,900 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,901 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,901 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:44,902 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:44,902 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,903 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:44,904 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,904 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:44,905 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,905 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:44,906 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:44,907 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:44,907 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:44,908 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,908 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:44,909 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:44,910 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:44,910 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:44,911 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:44,911 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:44,912 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:44,912 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:44,912 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:44,913 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:44,913 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:44,914 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:44,918 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:44,919 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,920 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:44,920 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:44,922 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:44,923 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:44,923 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,924 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:44,925 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:44,925 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:44,926 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:44,926 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:44,927 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,927 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:44,928 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:44,928 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,929 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:44,929 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:44,931 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:44,931 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:44,932 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,932 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:44,933 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:44,934 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:44,934 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:44,935 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:44,935 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,936 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:44,936 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:44,937 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:44,938 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:44,938 - numba.core.ssa - DEBUG - on stmt: $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:44,939 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,940 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:44,940 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,941 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:44,941 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:44,942 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,942 - numba.core.ssa - DEBUG - on stmt: $phi166.4.2 = phi(incoming_values=[Var($phi166.4.1, indexing.py:600), Var($phi166.4, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:44,943 - numba.core.ssa - DEBUG - on stmt: $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:44,944 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:44,944 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4.2, func=bool166, args=(Var($phi166.4.2, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,945 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:44,946 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:44,946 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,947 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:44,947 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:44,947 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:44,949 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:44,949 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:44,950 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,950 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:44,951 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:44,951 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:44,952 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,953 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:44,953 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:44,954 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:44,955 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:44,955 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,956 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:44,956 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:44,957 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:44,958 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:44,958 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,959 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:44,959 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:44,960 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:44,961 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:44,961 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,961 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:44,962 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,962 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:44,963 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:44,964 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,964 - numba.core.ssa - DEBUG - on stmt: $phi210.4.6 = phi(incoming_values=[Var($phi210.4.5, indexing.py:600), Var($phi210.4.7, indexing.py:599), Var($phi210.4.3, indexing.py:600), Var($phi210.4, indexing.py:599), Var($phi210.4.4, indexing.py:600)], incoming_blocks=[196, 166, 168, 76, 206])\n", - "2024-09-12 10:50:44,965 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:44,965 - numba.core.ssa - DEBUG - replaced with: match.1 = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:44,966 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:44,966 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:44,967 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,968 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:44,969 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,969 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:44,970 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:44,970 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,971 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:44,971 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,972 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:44,973 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:44,973 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,974 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:44,975 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:44,975 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,976 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,976 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:44,977 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,977 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:44,978 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:44,979 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {56: [],\n", - " 210: []})\n", - "2024-09-12 10:50:44,979 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:44,979 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,980 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:44,981 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:44,982 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:44,982 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:44,983 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:44,983 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:44,984 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:44,984 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:44,985 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:44,986 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:44,986 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:44,987 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,987 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:44,988 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:44,988 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,989 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:44,989 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:44,990 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:44,990 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:44,991 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:44,991 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,992 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:44,992 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,992 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:44,993 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:44,993 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:44,994 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:44,996 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:44,997 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:44,997 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:44,998 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:44,999 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:44,999 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,000 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:45,000 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:45,001 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:45,002 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:45,002 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,003 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:45,003 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:45,004 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:45,005 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:45,005 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:45,006 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:45,006 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,007 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:45,008 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:45,008 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:45,009 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:45,009 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,010 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,011 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:45,011 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:45,012 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:45,013 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:45,013 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,014 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:45,014 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:45,015 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:45,015 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:45,016 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:45,017 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:45,017 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,018 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:45,018 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:45,019 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:45,020 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:45,020 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:45,021 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:45,021 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:45,022 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:45,023 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:45,023 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:45,024 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:45,025 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:45,025 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:45,026 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,026 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:45,027 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:45,028 - numba.core.ssa - DEBUG - find_def var='match' stmt=$phi210.3 = match\n", - "2024-09-12 10:50:45,028 - numba.core.ssa - DEBUG - find_def_from_top label 76\n", - "2024-09-12 10:50:45,029 - numba.core.ssa - DEBUG - idom 74 from label 76\n", - "2024-09-12 10:50:45,029 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:45,030 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-09-12 10:50:45,030 - numba.core.ssa - DEBUG - insert phi node match.2 = phi(incoming_values=[], incoming_blocks=[]) at 74\n", - "2024-09-12 10:50:45,031 - numba.core.ssa - DEBUG - find_def_from_bottom label 56\n", - "2024-09-12 10:50:45,032 - numba.core.ssa - DEBUG - incoming_def match = const(bool, True)\n", - "2024-09-12 10:50:45,032 - numba.core.ssa - DEBUG - find_def_from_bottom label 210\n", - "2024-09-12 10:50:45,033 - numba.core.ssa - DEBUG - incoming_def match.1 = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:45,034 - numba.core.ssa - DEBUG - replaced with: $phi210.3 = match.2\n", - "2024-09-12 10:50:45,034 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:45,035 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:45,035 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,036 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:45,037 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:45,037 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:45,038 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:45,038 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:45,039 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,040 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:45,040 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:45,041 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,042 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:45,042 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:45,043 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:45,043 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:45,044 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,045 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:45,045 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:45,046 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:45,046 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:45,047 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:45,048 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,048 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:45,049 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:45,049 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:45,050 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:45,051 - numba.core.ssa - DEBUG - on stmt: $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:45,051 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:45,052 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:45,052 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,053 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:45,053 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:45,054 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,054 - numba.core.ssa - DEBUG - on stmt: $phi166.4.2 = phi(incoming_values=[Var($phi166.4.1, indexing.py:600), Var($phi166.4, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:45,055 - numba.core.ssa - DEBUG - on stmt: $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:45,055 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:45,056 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4.2, func=bool166, args=(Var($phi166.4.2, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,057 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:45,058 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:45,058 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,059 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:45,060 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:45,060 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:45,061 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:45,061 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:45,062 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,062 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:45,063 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:45,064 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:45,064 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,065 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:45,065 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:45,066 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:45,067 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:45,067 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,068 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:45,069 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:45,069 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:45,070 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:45,070 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,071 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:45,071 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:45,072 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:45,073 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:45,073 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:45,074 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:45,074 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,075 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:45,076 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:45,076 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,077 - numba.core.ssa - DEBUG - on stmt: $phi210.4.6 = phi(incoming_values=[Var($phi210.4.5, indexing.py:600), Var($phi210.4.7, indexing.py:599), Var($phi210.4.3, indexing.py:600), Var($phi210.4, indexing.py:599), Var($phi210.4.4, indexing.py:600)], incoming_blocks=[196, 166, 168, 76, 206])\n", - "2024-09-12 10:50:45,077 - numba.core.ssa - DEBUG - on stmt: match.1 = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:45,078 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:45,078 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:45,078 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,080 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:45,080 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,081 - numba.core.ssa - DEBUG - find_def var='match' stmt=$218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,081 - numba.core.ssa - DEBUG - find_def_from_top label 216\n", - "2024-09-12 10:50:45,082 - numba.core.ssa - DEBUG - idom 74 from label 216\n", - "2024-09-12 10:50:45,083 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:45,084 - numba.core.ssa - DEBUG - replaced with: $218pred = call bool218(match.2, func=bool218, args=(Var(match.2, indexing.py:595),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,084 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:45,085 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:45,085 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,085 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:45,087 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,087 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:45,088 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:45,088 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,089 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:45,089 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:45,090 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,090 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:45,091 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:45,092 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,092 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:45,093 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:45,446 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=655)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=657)\n", - " 4\tLOAD_FAST(arg=0, lineno=657)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=657)\n", - " 8\tSTORE_FAST(arg=1, lineno=657)\n", - " 10\tLOAD_GLOBAL(arg=1, lineno=658)\n", - " 12\tLOAD_ATTR(arg=2, lineno=658)\n", - " 14\tLOAD_FAST(arg=1, lineno=658)\n", - " 16\tLOAD_GLOBAL(arg=1, lineno=658)\n", - " 18\tLOAD_ATTR(arg=3, lineno=658)\n", - " 20\tLOAD_CONST(arg=1, lineno=658)\n", - " 22\tCALL_FUNCTION_KW(arg=2, lineno=658)\n", - " 24\tSTORE_FAST(arg=2, lineno=658)\n", - " 26\tLOAD_GLOBAL(arg=4, lineno=660)\n", - " 28\tLOAD_FAST(arg=1, lineno=660)\n", - " 30\tCALL_FUNCTION(arg=1, lineno=660)\n", - " 32\tGET_ITER(arg=None, lineno=660)\n", - "> 34\tFOR_ITER(arg=8, lineno=660)\n", - " 36\tSTORE_FAST(arg=3, lineno=660)\n", - " 38\tLOAD_FAST(arg=0, lineno=661)\n", - " 40\tLOAD_FAST(arg=3, lineno=661)\n", - " 42\tBINARY_SUBSCR(arg=None, lineno=661)\n", - " 44\tLOAD_FAST(arg=2, lineno=661)\n", - " 46\tLOAD_FAST(arg=3, lineno=661)\n", - " 48\tSTORE_SUBSCR(arg=None, lineno=661)\n", - " 50\tJUMP_ABSOLUTE(arg=18, lineno=661)\n", - "> 52\tLOAD_FAST(arg=2, lineno=663)\n", - " 54\tRETURN_VALUE(arg=None, lineno=663)\n", - "2024-09-12 10:50:45,448 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:45,448 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:45,449 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:45,450 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=655)\n", - "2024-09-12 10:50:45,450 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:45,451 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=657)\n", - "2024-09-12 10:50:45,452 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:45,452 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=657)\n", - "2024-09-12 10:50:45,453 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:45,453 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=657)\n", - "2024-09-12 10:50:45,454 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$x4.1']\n", - "2024-09-12 10:50:45,455 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=1, lineno=657)\n", - "2024-09-12 10:50:45,455 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-09-12 10:50:45,456 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=1, lineno=658)\n", - "2024-09-12 10:50:45,457 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:45,457 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=2, lineno=658)\n", - "2024-09-12 10:50:45,458 - numba.core.byteflow - DEBUG - stack ['$10load_global.3']\n", - "2024-09-12 10:50:45,458 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=1, lineno=658)\n", - "2024-09-12 10:50:45,459 - numba.core.byteflow - DEBUG - stack ['$12load_attr.4']\n", - "2024-09-12 10:50:45,460 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_GLOBAL(arg=1, lineno=658)\n", - "2024-09-12 10:50:45,460 - numba.core.byteflow - DEBUG - stack ['$12load_attr.4', '$n14.5']\n", - "2024-09-12 10:50:45,461 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_ATTR(arg=3, lineno=658)\n", - "2024-09-12 10:50:45,461 - numba.core.byteflow - DEBUG - stack ['$12load_attr.4', '$n14.5', '$16load_global.6']\n", - "2024-09-12 10:50:45,462 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_CONST(arg=1, lineno=658)\n", - "2024-09-12 10:50:45,463 - numba.core.byteflow - DEBUG - stack ['$12load_attr.4', '$n14.5', '$18load_attr.7']\n", - "2024-09-12 10:50:45,463 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=CALL_FUNCTION_KW(arg=2, lineno=658)\n", - "2024-09-12 10:50:45,464 - numba.core.byteflow - DEBUG - stack ['$12load_attr.4', '$n14.5', '$18load_attr.7', '$const20.8']\n", - "2024-09-12 10:50:45,465 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=STORE_FAST(arg=2, lineno=658)\n", - "2024-09-12 10:50:45,465 - numba.core.byteflow - DEBUG - stack ['$22call_function_kw.9']\n", - "2024-09-12 10:50:45,466 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_GLOBAL(arg=4, lineno=660)\n", - "2024-09-12 10:50:45,467 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:45,467 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_FAST(arg=1, lineno=660)\n", - "2024-09-12 10:50:45,468 - numba.core.byteflow - DEBUG - stack ['$26load_global.10']\n", - "2024-09-12 10:50:45,469 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=CALL_FUNCTION(arg=1, lineno=660)\n", - "2024-09-12 10:50:45,469 - numba.core.byteflow - DEBUG - stack ['$26load_global.10', '$n28.11']\n", - "2024-09-12 10:50:45,470 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=GET_ITER(arg=None, lineno=660)\n", - "2024-09-12 10:50:45,470 - numba.core.byteflow - DEBUG - stack ['$30call_function.12']\n", - "2024-09-12 10:50:45,471 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=34, stack=('$32get_iter.13',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:45,472 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=34 nstack_initial=1)])\n", - "2024-09-12 10:50:45,472 - numba.core.byteflow - DEBUG - stack: ['$phi34.0']\n", - "2024-09-12 10:50:45,473 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=34 nstack_initial=1)\n", - "2024-09-12 10:50:45,473 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=FOR_ITER(arg=8, lineno=660)\n", - "2024-09-12 10:50:45,474 - numba.core.byteflow - DEBUG - stack ['$phi34.0']\n", - "2024-09-12 10:50:45,475 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=52, stack=(), blockstack=(), npush=0), Edge(pc=36, stack=('$phi34.0', '$34for_iter.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:45,475 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=52 nstack_initial=0), State(pc_initial=36 nstack_initial=2)])\n", - "2024-09-12 10:50:45,476 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:45,476 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=52 nstack_initial=0)\n", - "2024-09-12 10:50:45,477 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=LOAD_FAST(arg=2, lineno=663)\n", - "2024-09-12 10:50:45,478 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:45,478 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=RETURN_VALUE(arg=None, lineno=663)\n", - "2024-09-12 10:50:45,479 - numba.core.byteflow - DEBUG - stack ['$a52.0']\n", - "2024-09-12 10:50:45,479 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:45,480 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=36 nstack_initial=2)])\n", - "2024-09-12 10:50:45,481 - numba.core.byteflow - DEBUG - stack: ['$phi36.0', '$phi36.1']\n", - "2024-09-12 10:50:45,481 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=36 nstack_initial=2)\n", - "2024-09-12 10:50:45,482 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=STORE_FAST(arg=3, lineno=660)\n", - "2024-09-12 10:50:45,482 - numba.core.byteflow - DEBUG - stack ['$phi36.0', '$phi36.1']\n", - "2024-09-12 10:50:45,483 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_FAST(arg=0, lineno=661)\n", - "2024-09-12 10:50:45,484 - numba.core.byteflow - DEBUG - stack ['$phi36.0']\n", - "2024-09-12 10:50:45,484 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_FAST(arg=3, lineno=661)\n", - "2024-09-12 10:50:45,485 - numba.core.byteflow - DEBUG - stack ['$phi36.0', '$x38.2']\n", - "2024-09-12 10:50:45,486 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=BINARY_SUBSCR(arg=None, lineno=661)\n", - "2024-09-12 10:50:45,486 - numba.core.byteflow - DEBUG - stack ['$phi36.0', '$x38.2', '$i40.3']\n", - "2024-09-12 10:50:45,487 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=LOAD_FAST(arg=2, lineno=661)\n", - "2024-09-12 10:50:45,487 - numba.core.byteflow - DEBUG - stack ['$phi36.0', '$42binary_subscr.4']\n", - "2024-09-12 10:50:45,488 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=3, lineno=661)\n", - "2024-09-12 10:50:45,489 - numba.core.byteflow - DEBUG - stack ['$phi36.0', '$42binary_subscr.4', '$a44.5']\n", - "2024-09-12 10:50:45,489 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=STORE_SUBSCR(arg=None, lineno=661)\n", - "2024-09-12 10:50:45,490 - numba.core.byteflow - DEBUG - stack ['$phi36.0', '$42binary_subscr.4', '$a44.5', '$i46.6']\n", - "2024-09-12 10:50:45,491 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=JUMP_ABSOLUTE(arg=18, lineno=661)\n", - "2024-09-12 10:50:45,491 - numba.core.byteflow - DEBUG - stack ['$phi36.0']\n", - "2024-09-12 10:50:45,492 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=34, stack=('$phi36.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:45,493 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=34 nstack_initial=1)])\n", - "2024-09-12 10:50:45,493 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:45,494 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=34 nstack_initial=1): {'$phi34.0'},\n", - " State(pc_initial=36 nstack_initial=2): {'$phi36.1'},\n", - " State(pc_initial=52 nstack_initial=0): set()})\n", - "2024-09-12 10:50:45,495 - numba.core.byteflow - DEBUG - defmap: {'$phi34.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi36.1': State(pc_initial=34 nstack_initial=1)}\n", - "2024-09-12 10:50:45,495 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi34.0': {('$32get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi36.0', State(pc_initial=36 nstack_initial=2))},\n", - " '$phi36.0': {('$phi34.0', State(pc_initial=34 nstack_initial=1))},\n", - " '$phi36.1': {('$34for_iter.2',\n", - " State(pc_initial=34 nstack_initial=1))}})\n", - "2024-09-12 10:50:45,496 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi34.0': {('$32get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=1))},\n", - " '$phi36.0': {('$32get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi36.1': {('$34for_iter.2',\n", - " State(pc_initial=34 nstack_initial=1))}})\n", - "2024-09-12 10:50:45,497 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi34.0': {('$32get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi36.0': {('$32get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi36.1': {('$34for_iter.2',\n", - " State(pc_initial=34 nstack_initial=1))}})\n", - "2024-09-12 10:50:45,498 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi34.0': {('$32get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi36.0': {('$32get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi36.1': {('$34for_iter.2',\n", - " State(pc_initial=34 nstack_initial=1))}})\n", - "2024-09-12 10:50:45,498 - numba.core.byteflow - DEBUG - keep phismap: {'$phi34.0': {('$32get_iter.13', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi36.1': {('$34for_iter.2', State(pc_initial=34 nstack_initial=1))}}\n", - "2024-09-12 10:50:45,499 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi34.0': '$32get_iter.13'},\n", - " State(pc_initial=34 nstack_initial=1): {'$phi36.1': '$34for_iter.2'}})\n", - "2024-09-12 10:50:45,500 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:45,501 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$x4.1'}), (6, {'func': '$2load_global.0', 'args': ['$x4.1'], 'res': '$6call_function.2'}), (8, {'value': '$6call_function.2'}), (10, {'res': '$10load_global.3'}), (12, {'item': '$10load_global.3', 'res': '$12load_attr.4'}), (14, {'res': '$n14.5'}), (16, {'res': '$16load_global.6'}), (18, {'item': '$16load_global.6', 'res': '$18load_attr.7'}), (20, {'res': '$const20.8'}), (22, {'func': '$12load_attr.4', 'args': ['$n14.5', '$18load_attr.7'], 'names': '$const20.8', 'res': '$22call_function_kw.9'}), (24, {'value': '$22call_function_kw.9'}), (26, {'res': '$26load_global.10'}), (28, {'res': '$n28.11'}), (30, {'func': '$26load_global.10', 'args': ['$n28.11'], 'res': '$30call_function.12'}), (32, {'value': '$30call_function.12', 'res': '$32get_iter.13'})), outgoing_phis={'$phi34.0': '$32get_iter.13'}, blockstack=(), active_try_block=None, outgoing_edgepushed={34: ('$32get_iter.13',)})\n", - "2024-09-12 10:50:45,502 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=34 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((34, {'iterator': '$phi34.0', 'pair': '$34for_iter.1', 'indval': '$34for_iter.2', 'pred': '$34for_iter.3'}),), outgoing_phis={'$phi36.1': '$34for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={52: (), 36: ('$phi34.0', '$34for_iter.2')})\n", - "2024-09-12 10:50:45,503 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=36 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((36, {'value': '$phi36.1'}), (38, {'res': '$x38.2'}), (40, {'res': '$i40.3'}), (42, {'index': '$i40.3', 'target': '$x38.2', 'res': '$42binary_subscr.4'}), (44, {'res': '$a44.5'}), (46, {'res': '$i46.6'}), (48, {'target': '$a44.5', 'index': '$i46.6', 'value': '$42binary_subscr.4'}), (50, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={34: ('$phi36.0',)})\n", - "2024-09-12 10:50:45,503 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=52 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((52, {'res': '$a52.0'}), (54, {'retval': '$a52.0', 'castval': '$54return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:45,509 - numba.core.interpreter - DEBUG - label 0:\n", - " x = arg(0, name=x) ['x']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " n = call $2load_global.0(x, func=$2load_global.0, args=[Var(x, indexing.py:655)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'n', 'x']\n", - " $10load_global.3 = global(np: ) ['$10load_global.3']\n", - " $12load_attr.4 = getattr(value=$10load_global.3, attr=empty) ['$10load_global.3', '$12load_attr.4']\n", - " $16load_global.6 = global(np: ) ['$16load_global.6']\n", - " $18load_attr.7 = getattr(value=$16load_global.6, attr=intp) ['$16load_global.6', '$18load_attr.7']\n", - " a = call $12load_attr.4(n, func=$12load_attr.4, args=[Var(n, indexing.py:657)], kws=[('dtype', Var($18load_attr.7, indexing.py:658))], vararg=None, varkwarg=None, target=None) ['$12load_attr.4', '$18load_attr.7', 'a', 'n']\n", - " $26load_global.10 = global(range: ) ['$26load_global.10']\n", - " $30call_function.12 = call $26load_global.10(n, func=$26load_global.10, args=[Var(n, indexing.py:657)], kws=(), vararg=None, varkwarg=None, target=None) ['$26load_global.10', '$30call_function.12', 'n']\n", - " $32get_iter.13 = getiter(value=$30call_function.12) ['$30call_function.12', '$32get_iter.13']\n", - " $phi34.0 = $32get_iter.13 ['$32get_iter.13', '$phi34.0']\n", - " jump 34 []\n", - "label 34:\n", - " $34for_iter.1 = iternext(value=$phi34.0) ['$34for_iter.1', '$phi34.0']\n", - " $34for_iter.2 = pair_first(value=$34for_iter.1) ['$34for_iter.1', '$34for_iter.2']\n", - " $34for_iter.3 = pair_second(value=$34for_iter.1) ['$34for_iter.1', '$34for_iter.3']\n", - " $phi36.1 = $34for_iter.2 ['$34for_iter.2', '$phi36.1']\n", - " branch $34for_iter.3, 36, 52 ['$34for_iter.3']\n", - "label 36:\n", - " i = $phi36.1 ['$phi36.1', 'i']\n", - " $42binary_subscr.4 = getitem(value=x, index=i, fn=) ['$42binary_subscr.4', 'i', 'x']\n", - " a[i] = $42binary_subscr.4 ['$42binary_subscr.4', 'a', 'i']\n", - " jump 34 []\n", - "label 52:\n", - " $54return_value.1 = cast(value=a) ['$54return_value.1', 'a']\n", - " return $54return_value.1 ['$54return_value.1']\n", - "\n", - "2024-09-12 10:50:45,525 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:45,526 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,527 - numba.core.ssa - DEBUG - on stmt: x = arg(0, name=x)\n", - "2024-09-12 10:50:45,528 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-09-12 10:50:45,529 - numba.core.ssa - DEBUG - on stmt: n = call $2load_global.0(x, func=$2load_global.0, args=[Var(x, indexing.py:655)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,529 - numba.core.ssa - DEBUG - on stmt: $10load_global.3 = global(np: )\n", - "2024-09-12 10:50:45,530 - numba.core.ssa - DEBUG - on stmt: $12load_attr.4 = getattr(value=$10load_global.3, attr=empty)\n", - "2024-09-12 10:50:45,531 - numba.core.ssa - DEBUG - on stmt: $16load_global.6 = global(np: )\n", - "2024-09-12 10:50:45,532 - numba.core.ssa - DEBUG - on stmt: $18load_attr.7 = getattr(value=$16load_global.6, attr=intp)\n", - "2024-09-12 10:50:45,533 - numba.core.ssa - DEBUG - on stmt: a = call $12load_attr.4(n, func=$12load_attr.4, args=[Var(n, indexing.py:657)], kws=[('dtype', Var($18load_attr.7, indexing.py:658))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,533 - numba.core.ssa - DEBUG - on stmt: $26load_global.10 = global(range: )\n", - "2024-09-12 10:50:45,534 - numba.core.ssa - DEBUG - on stmt: $30call_function.12 = call $26load_global.10(n, func=$26load_global.10, args=[Var(n, indexing.py:657)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,535 - numba.core.ssa - DEBUG - on stmt: $32get_iter.13 = getiter(value=$30call_function.12)\n", - "2024-09-12 10:50:45,536 - numba.core.ssa - DEBUG - on stmt: $phi34.0 = $32get_iter.13\n", - "2024-09-12 10:50:45,537 - numba.core.ssa - DEBUG - on stmt: jump 34\n", - "2024-09-12 10:50:45,538 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 34\n", - "2024-09-12 10:50:45,538 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,539 - numba.core.ssa - DEBUG - on stmt: $34for_iter.1 = iternext(value=$phi34.0)\n", - "2024-09-12 10:50:45,540 - numba.core.ssa - DEBUG - on stmt: $34for_iter.2 = pair_first(value=$34for_iter.1)\n", - "2024-09-12 10:50:45,541 - numba.core.ssa - DEBUG - on stmt: $34for_iter.3 = pair_second(value=$34for_iter.1)\n", - "2024-09-12 10:50:45,541 - numba.core.ssa - DEBUG - on stmt: $phi36.1 = $34for_iter.2\n", - "2024-09-12 10:50:45,542 - numba.core.ssa - DEBUG - on stmt: branch $34for_iter.3, 36, 52\n", - "2024-09-12 10:50:45,543 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 36\n", - "2024-09-12 10:50:45,544 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,544 - numba.core.ssa - DEBUG - on stmt: i = $phi36.1\n", - "2024-09-12 10:50:45,545 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.4 = getitem(value=x, index=i, fn=)\n", - "2024-09-12 10:50:45,546 - numba.core.ssa - DEBUG - on stmt: a[i] = $42binary_subscr.4\n", - "2024-09-12 10:50:45,547 - numba.core.ssa - DEBUG - on stmt: jump 34\n", - "2024-09-12 10:50:45,548 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 52\n", - "2024-09-12 10:50:45,548 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,549 - numba.core.ssa - DEBUG - on stmt: $54return_value.1 = cast(value=a)\n", - "2024-09-12 10:50:45,550 - numba.core.ssa - DEBUG - on stmt: return $54return_value.1\n", - "2024-09-12 10:50:45,551 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_global.3': [],\n", - " '$12load_attr.4': [],\n", - " '$16load_global.6': [],\n", - " '$18load_attr.7': [],\n", - " '$26load_global.10': [],\n", - " '$2load_global.0': [],\n", - " '$30call_function.12': [],\n", - " '$32get_iter.13': [],\n", - " '$34for_iter.1': [],\n", - " '$34for_iter.2': [],\n", - " '$34for_iter.3': [],\n", - " '$42binary_subscr.4': [],\n", - " '$54return_value.1': [],\n", - " '$phi34.0': [],\n", - " '$phi36.1': [],\n", - " 'a': [],\n", - " 'i': [],\n", - " 'n': [],\n", - " 'x': []})\n", - "2024-09-12 10:50:45,552 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:45,585 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=4369)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=4370)\n", - " 4\tLOAD_FAST(arg=0, lineno=4370)\n", - " 6\tLOAD_FAST(arg=1, lineno=4370)\n", - " 8\tLOAD_DEREF(arg=0, lineno=4370)\n", - " 10\tCALL_FUNCTION(arg=3, lineno=4370)\n", - " 12\tRETURN_VALUE(arg=None, lineno=4370)\n", - "2024-09-12 10:50:45,593 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:45,594 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:45,595 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:45,595 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=4369)\n", - "2024-09-12 10:50:45,596 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:45,597 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=4370)\n", - "2024-09-12 10:50:45,598 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:45,599 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=4370)\n", - "2024-09-12 10:50:45,599 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:45,600 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=4370)\n", - "2024-09-12 10:50:45,601 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$shape4.1']\n", - "2024-09-12 10:50:45,602 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_DEREF(arg=0, lineno=4370)\n", - "2024-09-12 10:50:45,602 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$shape4.1', '$dtype6.2']\n", - "2024-09-12 10:50:45,603 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=CALL_FUNCTION(arg=3, lineno=4370)\n", - "2024-09-12 10:50:45,604 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$shape4.1', '$dtype6.2', '$8load_deref.3']\n", - "2024-09-12 10:50:45,605 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=RETURN_VALUE(arg=None, lineno=4370)\n", - "2024-09-12 10:50:45,606 - numba.core.byteflow - DEBUG - stack ['$10call_function.4']\n", - "2024-09-12 10:50:45,606 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:45,607 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:45,608 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:45,609 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:45,610 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:45,611 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:45,611 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:45,612 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:45,613 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:45,614 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$shape4.1'}), (6, {'res': '$dtype6.2'}), (8, {'res': '$8load_deref.3'}), (10, {'func': '$2load_global.0', 'args': ['$shape4.1', '$dtype6.2', '$8load_deref.3'], 'res': '$10call_function.4'}), (12, {'retval': '$10call_function.4', 'castval': '$12return_value.5'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:45,615 - numba.core.interpreter - DEBUG - label 0:\n", - " shape = arg(0, name=shape) ['shape']\n", - " dtype = arg(1, name=dtype) ['dtype']\n", - " $2load_global.0 = global(numpy_empty_nd: ) ['$2load_global.0']\n", - " $8load_deref.3 = freevar(retty: array(int64, 1d, C)) ['$8load_deref.3']\n", - " $10call_function.4 = call $2load_global.0(shape, dtype, $8load_deref.3, func=$2load_global.0, args=[Var(shape, arrayobj.py:4369), Var(dtype, arrayobj.py:4369), Var($8load_deref.3, arrayobj.py:4370)], kws=(), vararg=None, varkwarg=None, target=None) ['$10call_function.4', '$2load_global.0', '$8load_deref.3', 'dtype', 'shape']\n", - " $12return_value.5 = cast(value=$10call_function.4) ['$10call_function.4', '$12return_value.5']\n", - " return $12return_value.5 ['$12return_value.5']\n", - "\n", - "2024-09-12 10:50:45,633 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:45,634 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,635 - numba.core.ssa - DEBUG - on stmt: shape = arg(0, name=shape)\n", - "2024-09-12 10:50:45,636 - numba.core.ssa - DEBUG - on stmt: dtype = arg(1, name=dtype)\n", - "2024-09-12 10:50:45,637 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numpy_empty_nd: )\n", - "2024-09-12 10:50:45,637 - numba.core.ssa - DEBUG - on stmt: $8load_deref.3 = freevar(retty: array(int64, 1d, C))\n", - "2024-09-12 10:50:45,638 - numba.core.ssa - DEBUG - on stmt: $10call_function.4 = call $2load_global.0(shape, dtype, $8load_deref.3, func=$2load_global.0, args=[Var(shape, arrayobj.py:4369), Var(dtype, arrayobj.py:4369), Var($8load_deref.3, arrayobj.py:4370)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,639 - numba.core.ssa - DEBUG - on stmt: $12return_value.5 = cast(value=$10call_function.4)\n", - "2024-09-12 10:50:45,640 - numba.core.ssa - DEBUG - on stmt: return $12return_value.5\n", - "2024-09-12 10:50:45,641 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10call_function.4': [],\n", - " '$12return_value.5': [],\n", - " '$2load_global.0': [],\n", - " '$8load_deref.3': [],\n", - " 'dtype': [],\n", - " 'shape': []})\n", - "2024-09-12 10:50:45,642 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:45,902 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=4369)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=4370)\n", - " 4\tLOAD_FAST(arg=0, lineno=4370)\n", - " 6\tLOAD_FAST(arg=1, lineno=4370)\n", - " 8\tLOAD_DEREF(arg=0, lineno=4370)\n", - " 10\tCALL_FUNCTION(arg=3, lineno=4370)\n", - " 12\tRETURN_VALUE(arg=None, lineno=4370)\n", - "2024-09-12 10:50:45,904 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:45,905 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:45,905 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:45,906 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=4369)\n", - "2024-09-12 10:50:45,907 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:45,907 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=4370)\n", - "2024-09-12 10:50:45,908 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:45,909 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=4370)\n", - "2024-09-12 10:50:45,909 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:45,910 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=4370)\n", - "2024-09-12 10:50:45,911 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$shape4.1']\n", - "2024-09-12 10:50:45,911 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_DEREF(arg=0, lineno=4370)\n", - "2024-09-12 10:50:45,912 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$shape4.1', '$dtype6.2']\n", - "2024-09-12 10:50:45,913 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=CALL_FUNCTION(arg=3, lineno=4370)\n", - "2024-09-12 10:50:45,913 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$shape4.1', '$dtype6.2', '$8load_deref.3']\n", - "2024-09-12 10:50:45,914 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=RETURN_VALUE(arg=None, lineno=4370)\n", - "2024-09-12 10:50:45,915 - numba.core.byteflow - DEBUG - stack ['$10call_function.4']\n", - "2024-09-12 10:50:45,915 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:45,916 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:45,916 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:45,917 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:45,918 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:45,919 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:45,919 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:45,920 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:45,921 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:45,921 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$shape4.1'}), (6, {'res': '$dtype6.2'}), (8, {'res': '$8load_deref.3'}), (10, {'func': '$2load_global.0', 'args': ['$shape4.1', '$dtype6.2', '$8load_deref.3'], 'res': '$10call_function.4'}), (12, {'retval': '$10call_function.4', 'castval': '$12return_value.5'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:45,922 - numba.core.interpreter - DEBUG - label 0:\n", - " shape = arg(0, name=shape) ['shape']\n", - " dtype = arg(1, name=dtype) ['dtype']\n", - " $2load_global.0 = global(numpy_empty_nd: ) ['$2load_global.0']\n", - " $8load_deref.3 = freevar(retty: array(int64, 1d, C)) ['$8load_deref.3']\n", - " $10call_function.4 = call $2load_global.0(shape, dtype, $8load_deref.3, func=$2load_global.0, args=[Var(shape, arrayobj.py:4369), Var(dtype, arrayobj.py:4369), Var($8load_deref.3, arrayobj.py:4370)], kws=(), vararg=None, varkwarg=None, target=None) ['$10call_function.4', '$2load_global.0', '$8load_deref.3', 'dtype', 'shape']\n", - " $12return_value.5 = cast(value=$10call_function.4) ['$10call_function.4', '$12return_value.5']\n", - " return $12return_value.5 ['$12return_value.5']\n", - "\n", - "2024-09-12 10:50:45,928 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:45,929 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:45,929 - numba.core.ssa - DEBUG - on stmt: shape = arg(0, name=shape)\n", - "2024-09-12 10:50:45,930 - numba.core.ssa - DEBUG - on stmt: dtype = arg(1, name=dtype)\n", - "2024-09-12 10:50:45,931 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numpy_empty_nd: )\n", - "2024-09-12 10:50:45,932 - numba.core.ssa - DEBUG - on stmt: $8load_deref.3 = freevar(retty: array(int64, 1d, C))\n", - "2024-09-12 10:50:45,932 - numba.core.ssa - DEBUG - on stmt: $10call_function.4 = call $2load_global.0(shape, dtype, $8load_deref.3, func=$2load_global.0, args=[Var(shape, arrayobj.py:4369), Var(dtype, arrayobj.py:4369), Var($8load_deref.3, arrayobj.py:4370)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:45,933 - numba.core.ssa - DEBUG - on stmt: $12return_value.5 = cast(value=$10call_function.4)\n", - "2024-09-12 10:50:45,934 - numba.core.ssa - DEBUG - on stmt: return $12return_value.5\n", - "2024-09-12 10:50:45,934 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10call_function.4': [],\n", - " '$12return_value.5': [],\n", - " '$2load_global.0': [],\n", - " '$8load_deref.3': [],\n", - " 'dtype': [],\n", - " 'shape': []})\n", - "2024-09-12 10:50:45,935 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:47,601 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=398)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=455)\n", - " 4\tLOAD_ATTR(arg=1, lineno=455)\n", - " 6\tLOAD_ATTR(arg=2, lineno=455)\n", - " 8\tLOAD_METHOD(arg=3, lineno=455)\n", - " 10\tLOAD_GLOBAL(arg=0, lineno=455)\n", - " 12\tLOAD_ATTR(arg=4, lineno=455)\n", - " 14\tLOAD_ATTR(arg=5, lineno=455)\n", - " 16\tCALL_METHOD(arg=1, lineno=455)\n", - " 18\tSTORE_FAST(arg=2, lineno=455)\n", - " 20\tLOAD_FAST(arg=2, lineno=456)\n", - " 22\tLOAD_METHOD(arg=6, lineno=456)\n", - " 24\tLOAD_CONST(arg=1, lineno=456)\n", - " 26\tCALL_METHOD(arg=1, lineno=456)\n", - " 28\tPOP_TOP(arg=None, lineno=456)\n", - " 30\tLOAD_GLOBAL(arg=0, lineno=457)\n", - " 32\tLOAD_ATTR(arg=1, lineno=457)\n", - " 34\tLOAD_ATTR(arg=2, lineno=457)\n", - " 36\tLOAD_METHOD(arg=3, lineno=457)\n", - " 38\tLOAD_GLOBAL(arg=0, lineno=457)\n", - " 40\tLOAD_ATTR(arg=4, lineno=457)\n", - " 42\tLOAD_ATTR(arg=5, lineno=457)\n", - " 44\tCALL_METHOD(arg=1, lineno=457)\n", - " 46\tSTORE_FAST(arg=3, lineno=457)\n", - " 48\tLOAD_FAST(arg=3, lineno=458)\n", - " 50\tLOAD_METHOD(arg=6, lineno=458)\n", - " 52\tLOAD_FAST(arg=0, lineno=458)\n", - " 54\tLOAD_ATTR(arg=7, lineno=458)\n", - " 56\tLOAD_CONST(arg=2, lineno=458)\n", - " 58\tBINARY_SUBSCR(arg=None, lineno=458)\n", - " 60\tCALL_METHOD(arg=1, lineno=458)\n", - " 62\tPOP_TOP(arg=None, lineno=458)\n", - " 64\tLOAD_GLOBAL(arg=8, lineno=459)\n", - " 66\tLOAD_METHOD(arg=5, lineno=459)\n", - " 68\tLOAD_FAST(arg=0, lineno=459)\n", - " 70\tLOAD_ATTR(arg=7, lineno=459)\n", - " 72\tLOAD_CONST(arg=2, lineno=459)\n", - " 74\tBINARY_SUBSCR(arg=None, lineno=459)\n", - " 76\tCALL_METHOD(arg=1, lineno=459)\n", - " 78\tSTORE_FAST(arg=4, lineno=459)\n", - " 80\tLOAD_CONST(arg=1, lineno=461)\n", - " 82\tSTORE_FAST(arg=5, lineno=461)\n", - " 84\tLOAD_FAST(arg=5, lineno=462)\n", - " 86\tLOAD_GLOBAL(arg=9, lineno=462)\n", - " 88\tLOAD_FAST(arg=1, lineno=462)\n", - " 90\tCALL_FUNCTION(arg=1, lineno=462)\n", - " 92\tCOMPARE_OP(arg=0, lineno=462)\n", - " 94\tPOP_JUMP_IF_FALSE(arg=118, lineno=462)\n", - "> 96\tLOAD_GLOBAL(arg=9, lineno=468)\n", - " 98\tLOAD_FAST(arg=2, lineno=468)\n", - " 100\tCALL_FUNCTION(arg=1, lineno=468)\n", - " 102\tSTORE_FAST(arg=6, lineno=468)\n", - " 104\tLOAD_GLOBAL(arg=9, lineno=469)\n", - " 106\tLOAD_GLOBAL(arg=10, lineno=469)\n", - " 108\tLOAD_FAST(arg=1, lineno=469)\n", - " 110\tLOAD_FAST(arg=5, lineno=469)\n", - " 112\tLOAD_CONST(arg=1, lineno=469)\n", - " 114\tBUILD_TUPLE(arg=2, lineno=469)\n", - " 116\tBINARY_SUBSCR(arg=None, lineno=469)\n", - " 118\tLOAD_FAST(arg=1, lineno=469)\n", - " 120\tLOAD_FAST(arg=5, lineno=469)\n", - " 122\tLOAD_CONST(arg=2, lineno=469)\n", - " 124\tBUILD_TUPLE(arg=2, lineno=469)\n", - " 126\tBINARY_SUBSCR(arg=None, lineno=469)\n", - " 128\tLOAD_FAST(arg=1, lineno=469)\n", - " 130\tLOAD_FAST(arg=5, lineno=469)\n", - " 132\tLOAD_CONST(arg=3, lineno=469)\n", - " 134\tBUILD_TUPLE(arg=2, lineno=469)\n", - " 136\tBINARY_SUBSCR(arg=None, lineno=469)\n", - " 138\tCALL_FUNCTION(arg=3, lineno=469)\n", - " 140\tCALL_FUNCTION(arg=1, lineno=469)\n", - " 142\tLOAD_FAST(arg=6, lineno=469)\n", - " 144\tBINARY_MULTIPLY(arg=None, lineno=469)\n", - " 146\tLOAD_CONST(arg=3, lineno=469)\n", - " 148\tBINARY_ADD(arg=None, lineno=469)\n", - " 150\tSTORE_FAST(arg=7, lineno=469)\n", - " 152\tLOAD_FAST(arg=7, lineno=470)\n", - " 154\tLOAD_GLOBAL(arg=8, lineno=470)\n", - " 156\tLOAD_METHOD(arg=11, lineno=470)\n", - " 158\tLOAD_FAST(arg=7, lineno=470)\n", - " 160\tLOAD_GLOBAL(arg=12, lineno=470)\n", - " 162\tLOAD_FAST(arg=6, lineno=470)\n", - " 164\tLOAD_CONST(arg=2, lineno=470)\n", - " 166\tCALL_FUNCTION(arg=2, lineno=470)\n", - " 168\tBINARY_TRUE_DIVIDE(arg=None, lineno=470)\n", - " 170\tCALL_METHOD(arg=1, lineno=470)\n", - " 172\tBINARY_MULTIPLY(arg=None, lineno=470)\n", - " 174\tLOAD_FAST(arg=4, lineno=470)\n", - " 176\tLOAD_FAST(arg=6, lineno=470)\n", - " 178\tBINARY_ADD(arg=None, lineno=470)\n", - " 180\tCOMPARE_OP(arg=4, lineno=470)\n", - " 182\tPOP_JUMP_IF_FALSE(arg=94, lineno=470)\n", - " 184\tJUMP_FORWARD(arg=24, lineno=471)\n", - "> 186\tLOAD_GLOBAL(arg=13, lineno=477)\n", - " 188\tLOAD_FAST(arg=2, lineno=477)\n", - " 190\tLOAD_FAST(arg=3, lineno=477)\n", - " 192\tLOAD_FAST(arg=0, lineno=477)\n", - " 194\tLOAD_FAST(arg=5, lineno=477)\n", - " 196\tBINARY_SUBSCR(arg=None, lineno=477)\n", - " 198\tLOAD_FAST(arg=1, lineno=477)\n", - " 200\tLOAD_FAST(arg=5, lineno=477)\n", - " 202\tBINARY_SUBSCR(arg=None, lineno=477)\n", - " 204\tCALL_FUNCTION(arg=4, lineno=477)\n", - " 206\tUNPACK_SEQUENCE(arg=3, lineno=477)\n", - " 208\tSTORE_FAST(arg=2, lineno=477)\n", - " 210\tSTORE_FAST(arg=3, lineno=477)\n", - " 212\tSTORE_FAST(arg=4, lineno=477)\n", - " 214\tLOAD_FAST(arg=5, lineno=479)\n", - " 216\tLOAD_CONST(arg=2, lineno=479)\n", - " 218\tINPLACE_ADD(arg=None, lineno=479)\n", - " 220\tSTORE_FAST(arg=5, lineno=479)\n", - " 222\tLOAD_FAST(arg=5, lineno=462)\n", - " 224\tLOAD_GLOBAL(arg=9, lineno=462)\n", - " 226\tLOAD_FAST(arg=1, lineno=462)\n", - " 228\tCALL_FUNCTION(arg=1, lineno=462)\n", - " 230\tCOMPARE_OP(arg=0, lineno=462)\n", - " 232\tPOP_JUMP_IF_TRUE(arg=49, lineno=462)\n", - "> 234\tLOAD_GLOBAL(arg=14, lineno=482)\n", - " 236\tLOAD_FAST(arg=2, lineno=482)\n", - " 238\tLOAD_FAST(arg=3, lineno=482)\n", - " 240\tCALL_FUNCTION(arg=2, lineno=482)\n", - " 242\tUNPACK_SEQUENCE(arg=2, lineno=482)\n", - " 244\tSTORE_FAST(arg=2, lineno=482)\n", - " 246\tSTORE_FAST(arg=3, lineno=482)\n", - " 248\tLOAD_FAST(arg=5, lineno=485)\n", - " 250\tLOAD_GLOBAL(arg=9, lineno=485)\n", - " 252\tLOAD_FAST(arg=1, lineno=485)\n", - " 254\tCALL_FUNCTION(arg=1, lineno=485)\n", - " 256\tCOMPARE_OP(arg=2, lineno=485)\n", - " 258\tPOP_JUMP_IF_FALSE(arg=150, lineno=485)\n", - " 260\tLOAD_GLOBAL(arg=9, lineno=485)\n", - " 262\tLOAD_FAST(arg=2, lineno=485)\n", - " 264\tCALL_FUNCTION(arg=1, lineno=485)\n", - " 266\tLOAD_CONST(arg=2, lineno=485)\n", - " 268\tCOMPARE_OP(arg=2, lineno=485)\n", - " 270\tPOP_JUMP_IF_FALSE(arg=150, lineno=485)\n", - " 272\tLOAD_GLOBAL(arg=8, lineno=486)\n", - " 274\tLOAD_METHOD(arg=15, lineno=486)\n", - " 276\tLOAD_FAST(arg=2, lineno=486)\n", - " 278\tLOAD_CONST(arg=1, lineno=486)\n", - " 280\tBINARY_SUBSCR(arg=None, lineno=486)\n", - " 282\tLOAD_FAST(arg=3, lineno=486)\n", - " 284\tLOAD_CONST(arg=1, lineno=486)\n", - " 286\tBINARY_SUBSCR(arg=None, lineno=486)\n", - " 288\tBUILD_LIST(arg=2, lineno=486)\n", - " 290\tCALL_METHOD(arg=1, lineno=486)\n", - " 292\tLOAD_CONST(arg=4, lineno=486)\n", - " 294\tBUILD_TUPLE(arg=2, lineno=486)\n", - " 296\tRETURN_VALUE(arg=None, lineno=486)\n", - "> 298\tLOAD_GLOBAL(arg=16, lineno=490)\n", - " 300\tLOAD_FAST(arg=2, lineno=490)\n", - " 302\tLOAD_FAST(arg=3, lineno=490)\n", - " 304\tLOAD_FAST(arg=0, lineno=490)\n", - " 306\tLOAD_FAST(arg=5, lineno=490)\n", - " 308\tLOAD_CONST(arg=5, lineno=490)\n", - " 310\tBUILD_SLICE(arg=2, lineno=490)\n", - " 312\tBINARY_SUBSCR(arg=None, lineno=490)\n", - " 314\tLOAD_FAST(arg=1, lineno=490)\n", - " 316\tLOAD_FAST(arg=5, lineno=490)\n", - " 318\tLOAD_CONST(arg=5, lineno=490)\n", - " 320\tBUILD_SLICE(arg=2, lineno=490)\n", - " 322\tBINARY_SUBSCR(arg=None, lineno=490)\n", - " 324\tCALL_FUNCTION(arg=4, lineno=490)\n", - " 326\tSTORE_FAST(arg=8, lineno=490)\n", - " 328\tLOAD_GLOBAL(arg=17, lineno=491)\n", - " 330\tLOAD_FAST(arg=8, lineno=491)\n", - " 332\tCALL_FUNCTION(arg=1, lineno=491)\n", - " 334\tLOAD_CONST(arg=6, lineno=491)\n", - " 336\tBUILD_TUPLE(arg=2, lineno=491)\n", - " 338\tRETURN_VALUE(arg=None, lineno=491)\n", - "2024-09-12 10:50:47,604 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:47,605 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:47,606 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:47,606 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=398)\n", - "2024-09-12 10:50:47,607 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,608 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=455)\n", - "2024-09-12 10:50:47,608 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,609 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=455)\n", - "2024-09-12 10:50:47,610 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:47,610 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_ATTR(arg=2, lineno=455)\n", - "2024-09-12 10:50:47,611 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-09-12 10:50:47,612 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=3, lineno=455)\n", - "2024-09-12 10:50:47,612 - numba.core.byteflow - DEBUG - stack ['$6load_attr.2']\n", - "2024-09-12 10:50:47,613 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=0, lineno=455)\n", - "2024-09-12 10:50:47,614 - numba.core.byteflow - DEBUG - stack ['$8load_method.3']\n", - "2024-09-12 10:50:47,614 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=4, lineno=455)\n", - "2024-09-12 10:50:47,615 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$10load_global.4']\n", - "2024-09-12 10:50:47,616 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_ATTR(arg=5, lineno=455)\n", - "2024-09-12 10:50:47,616 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$12load_attr.5']\n", - "2024-09-12 10:50:47,617 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=CALL_METHOD(arg=1, lineno=455)\n", - "2024-09-12 10:50:47,617 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$14load_attr.6']\n", - "2024-09-12 10:50:47,618 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=STORE_FAST(arg=2, lineno=455)\n", - "2024-09-12 10:50:47,619 - numba.core.byteflow - DEBUG - stack ['$16call_method.7']\n", - "2024-09-12 10:50:47,619 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=2, lineno=456)\n", - "2024-09-12 10:50:47,620 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,621 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_METHOD(arg=6, lineno=456)\n", - "2024-09-12 10:50:47,621 - numba.core.byteflow - DEBUG - stack ['$starts20.8']\n", - "2024-09-12 10:50:47,622 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_CONST(arg=1, lineno=456)\n", - "2024-09-12 10:50:47,623 - numba.core.byteflow - DEBUG - stack ['$22load_method.9']\n", - "2024-09-12 10:50:47,623 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=CALL_METHOD(arg=1, lineno=456)\n", - "2024-09-12 10:50:47,624 - numba.core.byteflow - DEBUG - stack ['$22load_method.9', '$const24.10']\n", - "2024-09-12 10:50:47,625 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=POP_TOP(arg=None, lineno=456)\n", - "2024-09-12 10:50:47,625 - numba.core.byteflow - DEBUG - stack ['$26call_method.11']\n", - "2024-09-12 10:50:47,626 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_GLOBAL(arg=0, lineno=457)\n", - "2024-09-12 10:50:47,626 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,627 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_ATTR(arg=1, lineno=457)\n", - "2024-09-12 10:50:47,628 - numba.core.byteflow - DEBUG - stack ['$30load_global.12']\n", - "2024-09-12 10:50:47,628 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_ATTR(arg=2, lineno=457)\n", - "2024-09-12 10:50:47,629 - numba.core.byteflow - DEBUG - stack ['$32load_attr.13']\n", - "2024-09-12 10:50:47,629 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_METHOD(arg=3, lineno=457)\n", - "2024-09-12 10:50:47,630 - numba.core.byteflow - DEBUG - stack ['$34load_attr.14']\n", - "2024-09-12 10:50:47,631 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_GLOBAL(arg=0, lineno=457)\n", - "2024-09-12 10:50:47,631 - numba.core.byteflow - DEBUG - stack ['$36load_method.15']\n", - "2024-09-12 10:50:47,632 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_ATTR(arg=4, lineno=457)\n", - "2024-09-12 10:50:47,633 - numba.core.byteflow - DEBUG - stack ['$36load_method.15', '$38load_global.16']\n", - "2024-09-12 10:50:47,633 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_ATTR(arg=5, lineno=457)\n", - "2024-09-12 10:50:47,634 - numba.core.byteflow - DEBUG - stack ['$36load_method.15', '$40load_attr.17']\n", - "2024-09-12 10:50:47,635 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=CALL_METHOD(arg=1, lineno=457)\n", - "2024-09-12 10:50:47,635 - numba.core.byteflow - DEBUG - stack ['$36load_method.15', '$42load_attr.18']\n", - "2024-09-12 10:50:47,636 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=STORE_FAST(arg=3, lineno=457)\n", - "2024-09-12 10:50:47,636 - numba.core.byteflow - DEBUG - stack ['$44call_method.19']\n", - "2024-09-12 10:50:47,638 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_FAST(arg=3, lineno=458)\n", - "2024-09-12 10:50:47,639 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,640 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_METHOD(arg=6, lineno=458)\n", - "2024-09-12 10:50:47,640 - numba.core.byteflow - DEBUG - stack ['$stops48.20']\n", - "2024-09-12 10:50:47,641 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=LOAD_FAST(arg=0, lineno=458)\n", - "2024-09-12 10:50:47,642 - numba.core.byteflow - DEBUG - stack ['$50load_method.21']\n", - "2024-09-12 10:50:47,642 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=LOAD_ATTR(arg=7, lineno=458)\n", - "2024-09-12 10:50:47,643 - numba.core.byteflow - DEBUG - stack ['$50load_method.21', '$coords52.22']\n", - "2024-09-12 10:50:47,644 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_CONST(arg=2, lineno=458)\n", - "2024-09-12 10:50:47,645 - numba.core.byteflow - DEBUG - stack ['$50load_method.21', '$54load_attr.23']\n", - "2024-09-12 10:50:47,645 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=BINARY_SUBSCR(arg=None, lineno=458)\n", - "2024-09-12 10:50:47,646 - numba.core.byteflow - DEBUG - stack ['$50load_method.21', '$54load_attr.23', '$const56.24']\n", - "2024-09-12 10:50:47,647 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=CALL_METHOD(arg=1, lineno=458)\n", - "2024-09-12 10:50:47,648 - numba.core.byteflow - DEBUG - stack ['$50load_method.21', '$58binary_subscr.25']\n", - "2024-09-12 10:50:47,648 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=POP_TOP(arg=None, lineno=458)\n", - "2024-09-12 10:50:47,649 - numba.core.byteflow - DEBUG - stack ['$60call_method.26']\n", - "2024-09-12 10:50:47,650 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_GLOBAL(arg=8, lineno=459)\n", - "2024-09-12 10:50:47,651 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,651 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_METHOD(arg=5, lineno=459)\n", - "2024-09-12 10:50:47,652 - numba.core.byteflow - DEBUG - stack ['$64load_global.27']\n", - "2024-09-12 10:50:47,653 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_FAST(arg=0, lineno=459)\n", - "2024-09-12 10:50:47,654 - numba.core.byteflow - DEBUG - stack ['$66load_method.28']\n", - "2024-09-12 10:50:47,654 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=LOAD_ATTR(arg=7, lineno=459)\n", - "2024-09-12 10:50:47,655 - numba.core.byteflow - DEBUG - stack ['$66load_method.28', '$coords68.29']\n", - "2024-09-12 10:50:47,656 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=LOAD_CONST(arg=2, lineno=459)\n", - "2024-09-12 10:50:47,657 - numba.core.byteflow - DEBUG - stack ['$66load_method.28', '$70load_attr.30']\n", - "2024-09-12 10:50:47,660 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=BINARY_SUBSCR(arg=None, lineno=459)\n", - "2024-09-12 10:50:47,661 - numba.core.byteflow - DEBUG - stack ['$66load_method.28', '$70load_attr.30', '$const72.31']\n", - "2024-09-12 10:50:47,662 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=CALL_METHOD(arg=1, lineno=459)\n", - "2024-09-12 10:50:47,671 - numba.core.byteflow - DEBUG - stack ['$66load_method.28', '$74binary_subscr.32']\n", - "2024-09-12 10:50:47,672 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=STORE_FAST(arg=4, lineno=459)\n", - "2024-09-12 10:50:47,673 - numba.core.byteflow - DEBUG - stack ['$76call_method.33']\n", - "2024-09-12 10:50:47,673 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_CONST(arg=1, lineno=461)\n", - "2024-09-12 10:50:47,674 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,675 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=STORE_FAST(arg=5, lineno=461)\n", - "2024-09-12 10:50:47,676 - numba.core.byteflow - DEBUG - stack ['$const80.34']\n", - "2024-09-12 10:50:47,676 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=LOAD_FAST(arg=5, lineno=462)\n", - "2024-09-12 10:50:47,677 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,678 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_GLOBAL(arg=9, lineno=462)\n", - "2024-09-12 10:50:47,679 - numba.core.byteflow - DEBUG - stack ['$i84.35']\n", - "2024-09-12 10:50:47,679 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_FAST(arg=1, lineno=462)\n", - "2024-09-12 10:50:47,680 - numba.core.byteflow - DEBUG - stack ['$i84.35', '$86load_global.36']\n", - "2024-09-12 10:50:47,681 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=CALL_FUNCTION(arg=1, lineno=462)\n", - "2024-09-12 10:50:47,682 - numba.core.byteflow - DEBUG - stack ['$i84.35', '$86load_global.36', '$indices88.37']\n", - "2024-09-12 10:50:47,683 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=COMPARE_OP(arg=0, lineno=462)\n", - "2024-09-12 10:50:47,683 - numba.core.byteflow - DEBUG - stack ['$i84.35', '$90call_function.38']\n", - "2024-09-12 10:50:47,684 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=POP_JUMP_IF_FALSE(arg=118, lineno=462)\n", - "2024-09-12 10:50:47,685 - numba.core.byteflow - DEBUG - stack ['$92compare_op.39']\n", - "2024-09-12 10:50:47,686 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=(), blockstack=(), npush=0), Edge(pc=234, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:47,687 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=0), State(pc_initial=234 nstack_initial=0)])\n", - "2024-09-12 10:50:47,687 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:47,688 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=96 nstack_initial=0)\n", - "2024-09-12 10:50:47,689 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=LOAD_GLOBAL(arg=9, lineno=468)\n", - "2024-09-12 10:50:47,690 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,690 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=2, lineno=468)\n", - "2024-09-12 10:50:47,691 - numba.core.byteflow - DEBUG - stack ['$96load_global.0']\n", - "2024-09-12 10:50:47,692 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=CALL_FUNCTION(arg=1, lineno=468)\n", - "2024-09-12 10:50:47,693 - numba.core.byteflow - DEBUG - stack ['$96load_global.0', '$starts98.1']\n", - "2024-09-12 10:50:47,693 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=STORE_FAST(arg=6, lineno=468)\n", - "2024-09-12 10:50:47,694 - numba.core.byteflow - DEBUG - stack ['$100call_function.2']\n", - "2024-09-12 10:50:47,695 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=LOAD_GLOBAL(arg=9, lineno=469)\n", - "2024-09-12 10:50:47,696 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,696 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_GLOBAL(arg=10, lineno=469)\n", - "2024-09-12 10:50:47,697 - numba.core.byteflow - DEBUG - stack ['$104load_global.3']\n", - "2024-09-12 10:50:47,698 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_FAST(arg=1, lineno=469)\n", - "2024-09-12 10:50:47,699 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4']\n", - "2024-09-12 10:50:47,700 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=LOAD_FAST(arg=5, lineno=469)\n", - "2024-09-12 10:50:47,700 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$indices108.5']\n", - "2024-09-12 10:50:47,701 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=1, lineno=469)\n", - "2024-09-12 10:50:47,702 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$indices108.5', '$i110.6']\n", - "2024-09-12 10:50:47,703 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BUILD_TUPLE(arg=2, lineno=469)\n", - "2024-09-12 10:50:47,704 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$indices108.5', '$i110.6', '$const112.7']\n", - "2024-09-12 10:50:47,704 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=BINARY_SUBSCR(arg=None, lineno=469)\n", - "2024-09-12 10:50:47,705 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$indices108.5', '$114build_tuple.8']\n", - "2024-09-12 10:50:47,706 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_FAST(arg=1, lineno=469)\n", - "2024-09-12 10:50:47,707 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9']\n", - "2024-09-12 10:50:47,707 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=5, lineno=469)\n", - "2024-09-12 10:50:47,708 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$indices118.10']\n", - "2024-09-12 10:50:47,709 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_CONST(arg=2, lineno=469)\n", - "2024-09-12 10:50:47,710 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$indices118.10', '$i120.11']\n", - "2024-09-12 10:50:47,710 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=BUILD_TUPLE(arg=2, lineno=469)\n", - "2024-09-12 10:50:47,711 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$indices118.10', '$i120.11', '$const122.12']\n", - "2024-09-12 10:50:47,712 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=BINARY_SUBSCR(arg=None, lineno=469)\n", - "2024-09-12 10:50:47,713 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$indices118.10', '$124build_tuple.13']\n", - "2024-09-12 10:50:47,713 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=LOAD_FAST(arg=1, lineno=469)\n", - "2024-09-12 10:50:47,714 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14']\n", - "2024-09-12 10:50:47,715 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=LOAD_FAST(arg=5, lineno=469)\n", - "2024-09-12 10:50:47,716 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$indices128.15']\n", - "2024-09-12 10:50:47,716 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_CONST(arg=3, lineno=469)\n", - "2024-09-12 10:50:47,717 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$indices128.15', '$i130.16']\n", - "2024-09-12 10:50:47,718 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=BUILD_TUPLE(arg=2, lineno=469)\n", - "2024-09-12 10:50:47,719 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$indices128.15', '$i130.16', '$const132.17']\n", - "2024-09-12 10:50:47,719 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BINARY_SUBSCR(arg=None, lineno=469)\n", - "2024-09-12 10:50:47,720 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$indices128.15', '$134build_tuple.18']\n", - "2024-09-12 10:50:47,721 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=CALL_FUNCTION(arg=3, lineno=469)\n", - "2024-09-12 10:50:47,722 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$136binary_subscr.19']\n", - "2024-09-12 10:50:47,722 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=CALL_FUNCTION(arg=1, lineno=469)\n", - "2024-09-12 10:50:47,723 - numba.core.byteflow - DEBUG - stack ['$104load_global.3', '$138call_function.20']\n", - "2024-09-12 10:50:47,724 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=6, lineno=469)\n", - "2024-09-12 10:50:47,725 - numba.core.byteflow - DEBUG - stack ['$140call_function.21']\n", - "2024-09-12 10:50:47,725 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=BINARY_MULTIPLY(arg=None, lineno=469)\n", - "2024-09-12 10:50:47,726 - numba.core.byteflow - DEBUG - stack ['$140call_function.21', '$n_pairs142.22']\n", - "2024-09-12 10:50:47,727 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_CONST(arg=3, lineno=469)\n", - "2024-09-12 10:50:47,728 - numba.core.byteflow - DEBUG - stack ['$144binary_multiply.23']\n", - "2024-09-12 10:50:47,745 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=BINARY_ADD(arg=None, lineno=469)\n", - "2024-09-12 10:50:47,746 - numba.core.byteflow - DEBUG - stack ['$144binary_multiply.23', '$const146.24']\n", - "2024-09-12 10:50:47,746 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=STORE_FAST(arg=7, lineno=469)\n", - "2024-09-12 10:50:47,747 - numba.core.byteflow - DEBUG - stack ['$148binary_add.25']\n", - "2024-09-12 10:50:47,748 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=LOAD_FAST(arg=7, lineno=470)\n", - "2024-09-12 10:50:47,748 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,749 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_GLOBAL(arg=8, lineno=470)\n", - "2024-09-12 10:50:47,750 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26']\n", - "2024-09-12 10:50:47,750 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=LOAD_METHOD(arg=11, lineno=470)\n", - "2024-09-12 10:50:47,751 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$154load_global.27']\n", - "2024-09-12 10:50:47,751 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=LOAD_FAST(arg=7, lineno=470)\n", - "2024-09-12 10:50:47,752 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28']\n", - "2024-09-12 10:50:47,753 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=LOAD_GLOBAL(arg=12, lineno=470)\n", - "2024-09-12 10:50:47,753 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29']\n", - "2024-09-12 10:50:47,754 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=LOAD_FAST(arg=6, lineno=470)\n", - "2024-09-12 10:50:47,754 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29', '$160load_global.30']\n", - "2024-09-12 10:50:47,755 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=LOAD_CONST(arg=2, lineno=470)\n", - "2024-09-12 10:50:47,756 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29', '$160load_global.30', '$n_pairs162.31']\n", - "2024-09-12 10:50:47,756 - numba.core.byteflow - DEBUG - dispatch pc=166, inst=CALL_FUNCTION(arg=2, lineno=470)\n", - "2024-09-12 10:50:47,757 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29', '$160load_global.30', '$n_pairs162.31', '$const164.32']\n", - "2024-09-12 10:50:47,758 - numba.core.byteflow - DEBUG - dispatch pc=168, inst=BINARY_TRUE_DIVIDE(arg=None, lineno=470)\n", - "2024-09-12 10:50:47,758 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$n_current_slices158.29', '$166call_function.33']\n", - "2024-09-12 10:50:47,759 - numba.core.byteflow - DEBUG - dispatch pc=170, inst=CALL_METHOD(arg=1, lineno=470)\n", - "2024-09-12 10:50:47,760 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$156load_method.28', '$168binary_true_divide.34']\n", - "2024-09-12 10:50:47,760 - numba.core.byteflow - DEBUG - dispatch pc=172, inst=BINARY_MULTIPLY(arg=None, lineno=470)\n", - "2024-09-12 10:50:47,761 - numba.core.byteflow - DEBUG - stack ['$n_current_slices152.26', '$170call_method.35']\n", - "2024-09-12 10:50:47,761 - numba.core.byteflow - DEBUG - dispatch pc=174, inst=LOAD_FAST(arg=4, lineno=470)\n", - "2024-09-12 10:50:47,762 - numba.core.byteflow - DEBUG - stack ['$172binary_multiply.36']\n", - "2024-09-12 10:50:47,763 - numba.core.byteflow - DEBUG - dispatch pc=176, inst=LOAD_FAST(arg=6, lineno=470)\n", - "2024-09-12 10:50:47,763 - numba.core.byteflow - DEBUG - stack ['$172binary_multiply.36', '$n_matches174.37']\n", - "2024-09-12 10:50:47,764 - numba.core.byteflow - DEBUG - dispatch pc=178, inst=BINARY_ADD(arg=None, lineno=470)\n", - "2024-09-12 10:50:47,764 - numba.core.byteflow - DEBUG - stack ['$172binary_multiply.36', '$n_matches174.37', '$n_pairs176.38']\n", - "2024-09-12 10:50:47,765 - numba.core.byteflow - DEBUG - dispatch pc=180, inst=COMPARE_OP(arg=4, lineno=470)\n", - "2024-09-12 10:50:47,766 - numba.core.byteflow - DEBUG - stack ['$172binary_multiply.36', '$178binary_add.39']\n", - "2024-09-12 10:50:47,766 - numba.core.byteflow - DEBUG - dispatch pc=182, inst=POP_JUMP_IF_FALSE(arg=94, lineno=470)\n", - "2024-09-12 10:50:47,767 - numba.core.byteflow - DEBUG - stack ['$180compare_op.40']\n", - "2024-09-12 10:50:47,767 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=184, stack=(), blockstack=(), npush=0), Edge(pc=186, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:47,768 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=234 nstack_initial=0), State(pc_initial=184 nstack_initial=0), State(pc_initial=186 nstack_initial=0)])\n", - "2024-09-12 10:50:47,769 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:47,769 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=234 nstack_initial=0)\n", - "2024-09-12 10:50:47,770 - numba.core.byteflow - DEBUG - dispatch pc=234, inst=LOAD_GLOBAL(arg=14, lineno=482)\n", - "2024-09-12 10:50:47,775 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,776 - numba.core.byteflow - DEBUG - dispatch pc=236, inst=LOAD_FAST(arg=2, lineno=482)\n", - "2024-09-12 10:50:47,777 - numba.core.byteflow - DEBUG - stack ['$234load_global.0']\n", - "2024-09-12 10:50:47,777 - numba.core.byteflow - DEBUG - dispatch pc=238, inst=LOAD_FAST(arg=3, lineno=482)\n", - "2024-09-12 10:50:47,778 - numba.core.byteflow - DEBUG - stack ['$234load_global.0', '$starts236.1']\n", - "2024-09-12 10:50:47,778 - numba.core.byteflow - DEBUG - dispatch pc=240, inst=CALL_FUNCTION(arg=2, lineno=482)\n", - "2024-09-12 10:50:47,780 - numba.core.byteflow - DEBUG - stack ['$234load_global.0', '$starts236.1', '$stops238.2']\n", - "2024-09-12 10:50:47,781 - numba.core.byteflow - DEBUG - dispatch pc=242, inst=UNPACK_SEQUENCE(arg=2, lineno=482)\n", - "2024-09-12 10:50:47,781 - numba.core.byteflow - DEBUG - stack ['$240call_function.3']\n", - "2024-09-12 10:50:47,782 - numba.core.byteflow - DEBUG - dispatch pc=244, inst=STORE_FAST(arg=2, lineno=482)\n", - "2024-09-12 10:50:47,783 - numba.core.byteflow - DEBUG - stack ['$242unpack_sequence.5', '$242unpack_sequence.4']\n", - "2024-09-12 10:50:47,783 - numba.core.byteflow - DEBUG - dispatch pc=246, inst=STORE_FAST(arg=3, lineno=482)\n", - "2024-09-12 10:50:47,784 - numba.core.byteflow - DEBUG - stack ['$242unpack_sequence.5']\n", - "2024-09-12 10:50:47,784 - numba.core.byteflow - DEBUG - dispatch pc=248, inst=LOAD_FAST(arg=5, lineno=485)\n", - "2024-09-12 10:50:47,785 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,786 - numba.core.byteflow - DEBUG - dispatch pc=250, inst=LOAD_GLOBAL(arg=9, lineno=485)\n", - "2024-09-12 10:50:47,786 - numba.core.byteflow - DEBUG - stack ['$i248.7']\n", - "2024-09-12 10:50:47,787 - numba.core.byteflow - DEBUG - dispatch pc=252, inst=LOAD_FAST(arg=1, lineno=485)\n", - "2024-09-12 10:50:47,788 - numba.core.byteflow - DEBUG - stack ['$i248.7', '$250load_global.8']\n", - "2024-09-12 10:50:47,788 - numba.core.byteflow - DEBUG - dispatch pc=254, inst=CALL_FUNCTION(arg=1, lineno=485)\n", - "2024-09-12 10:50:47,789 - numba.core.byteflow - DEBUG - stack ['$i248.7', '$250load_global.8', '$indices252.9']\n", - "2024-09-12 10:50:47,789 - numba.core.byteflow - DEBUG - dispatch pc=256, inst=COMPARE_OP(arg=2, lineno=485)\n", - "2024-09-12 10:50:47,790 - numba.core.byteflow - DEBUG - stack ['$i248.7', '$254call_function.10']\n", - "2024-09-12 10:50:47,791 - numba.core.byteflow - DEBUG - dispatch pc=258, inst=POP_JUMP_IF_FALSE(arg=150, lineno=485)\n", - "2024-09-12 10:50:47,791 - numba.core.byteflow - DEBUG - stack ['$256compare_op.11']\n", - "2024-09-12 10:50:47,792 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=260, stack=(), blockstack=(), npush=0), Edge(pc=298, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:47,793 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=184 nstack_initial=0), State(pc_initial=186 nstack_initial=0), State(pc_initial=260 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:47,796 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:47,796 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=184 nstack_initial=0)\n", - "2024-09-12 10:50:47,797 - numba.core.byteflow - DEBUG - dispatch pc=184, inst=JUMP_FORWARD(arg=24, lineno=471)\n", - "2024-09-12 10:50:47,797 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,798 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=234, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:47,799 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=186 nstack_initial=0), State(pc_initial=260 nstack_initial=0), State(pc_initial=298 nstack_initial=0), State(pc_initial=234 nstack_initial=0)])\n", - "2024-09-12 10:50:47,799 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:47,800 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=186 nstack_initial=0)\n", - "2024-09-12 10:50:47,800 - numba.core.byteflow - DEBUG - dispatch pc=186, inst=LOAD_GLOBAL(arg=13, lineno=477)\n", - "2024-09-12 10:50:47,801 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,802 - numba.core.byteflow - DEBUG - dispatch pc=188, inst=LOAD_FAST(arg=2, lineno=477)\n", - "2024-09-12 10:50:47,802 - numba.core.byteflow - DEBUG - stack ['$186load_global.0']\n", - "2024-09-12 10:50:47,803 - numba.core.byteflow - DEBUG - dispatch pc=190, inst=LOAD_FAST(arg=3, lineno=477)\n", - "2024-09-12 10:50:47,803 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1']\n", - "2024-09-12 10:50:47,804 - numba.core.byteflow - DEBUG - dispatch pc=192, inst=LOAD_FAST(arg=0, lineno=477)\n", - "2024-09-12 10:50:47,804 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2']\n", - "2024-09-12 10:50:47,805 - numba.core.byteflow - DEBUG - dispatch pc=194, inst=LOAD_FAST(arg=5, lineno=477)\n", - "2024-09-12 10:50:47,806 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$coords192.3']\n", - "2024-09-12 10:50:47,806 - numba.core.byteflow - DEBUG - dispatch pc=196, inst=BINARY_SUBSCR(arg=None, lineno=477)\n", - "2024-09-12 10:50:47,807 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$coords192.3', '$i194.4']\n", - "2024-09-12 10:50:47,807 - numba.core.byteflow - DEBUG - dispatch pc=198, inst=LOAD_FAST(arg=1, lineno=477)\n", - "2024-09-12 10:50:47,808 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$196binary_subscr.5']\n", - "2024-09-12 10:50:47,809 - numba.core.byteflow - DEBUG - dispatch pc=200, inst=LOAD_FAST(arg=5, lineno=477)\n", - "2024-09-12 10:50:47,809 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$196binary_subscr.5', '$indices198.6']\n", - "2024-09-12 10:50:47,810 - numba.core.byteflow - DEBUG - dispatch pc=202, inst=BINARY_SUBSCR(arg=None, lineno=477)\n", - "2024-09-12 10:50:47,810 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$196binary_subscr.5', '$indices198.6', '$i200.7']\n", - "2024-09-12 10:50:47,811 - numba.core.byteflow - DEBUG - dispatch pc=204, inst=CALL_FUNCTION(arg=4, lineno=477)\n", - "2024-09-12 10:50:47,812 - numba.core.byteflow - DEBUG - stack ['$186load_global.0', '$starts188.1', '$stops190.2', '$196binary_subscr.5', '$202binary_subscr.8']\n", - "2024-09-12 10:50:47,812 - numba.core.byteflow - DEBUG - dispatch pc=206, inst=UNPACK_SEQUENCE(arg=3, lineno=477)\n", - "2024-09-12 10:50:47,813 - numba.core.byteflow - DEBUG - stack ['$204call_function.9']\n", - "2024-09-12 10:50:47,813 - numba.core.byteflow - DEBUG - dispatch pc=208, inst=STORE_FAST(arg=2, lineno=477)\n", - "2024-09-12 10:50:47,814 - numba.core.byteflow - DEBUG - stack ['$206unpack_sequence.12', '$206unpack_sequence.11', '$206unpack_sequence.10']\n", - "2024-09-12 10:50:47,815 - numba.core.byteflow - DEBUG - dispatch pc=210, inst=STORE_FAST(arg=3, lineno=477)\n", - "2024-09-12 10:50:47,815 - numba.core.byteflow - DEBUG - stack ['$206unpack_sequence.12', '$206unpack_sequence.11']\n", - "2024-09-12 10:50:47,816 - numba.core.byteflow - DEBUG - dispatch pc=212, inst=STORE_FAST(arg=4, lineno=477)\n", - "2024-09-12 10:50:47,816 - numba.core.byteflow - DEBUG - stack ['$206unpack_sequence.12']\n", - "2024-09-12 10:50:47,817 - numba.core.byteflow - DEBUG - dispatch pc=214, inst=LOAD_FAST(arg=5, lineno=479)\n", - "2024-09-12 10:50:47,818 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,818 - numba.core.byteflow - DEBUG - dispatch pc=216, inst=LOAD_CONST(arg=2, lineno=479)\n", - "2024-09-12 10:50:47,819 - numba.core.byteflow - DEBUG - stack ['$i214.14']\n", - "2024-09-12 10:50:47,819 - numba.core.byteflow - DEBUG - dispatch pc=218, inst=INPLACE_ADD(arg=None, lineno=479)\n", - "2024-09-12 10:50:47,820 - numba.core.byteflow - DEBUG - stack ['$i214.14', '$const216.15']\n", - "2024-09-12 10:50:47,820 - numba.core.byteflow - DEBUG - dispatch pc=220, inst=STORE_FAST(arg=5, lineno=479)\n", - "2024-09-12 10:50:47,821 - numba.core.byteflow - DEBUG - stack ['$218inplace_add.16']\n", - "2024-09-12 10:50:47,822 - numba.core.byteflow - DEBUG - dispatch pc=222, inst=LOAD_FAST(arg=5, lineno=462)\n", - "2024-09-12 10:50:47,822 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,823 - numba.core.byteflow - DEBUG - dispatch pc=224, inst=LOAD_GLOBAL(arg=9, lineno=462)\n", - "2024-09-12 10:50:47,823 - numba.core.byteflow - DEBUG - stack ['$i222.17']\n", - "2024-09-12 10:50:47,824 - numba.core.byteflow - DEBUG - dispatch pc=226, inst=LOAD_FAST(arg=1, lineno=462)\n", - "2024-09-12 10:50:47,824 - numba.core.byteflow - DEBUG - stack ['$i222.17', '$224load_global.18']\n", - "2024-09-12 10:50:47,825 - numba.core.byteflow - DEBUG - dispatch pc=228, inst=CALL_FUNCTION(arg=1, lineno=462)\n", - "2024-09-12 10:50:47,826 - numba.core.byteflow - DEBUG - stack ['$i222.17', '$224load_global.18', '$indices226.19']\n", - "2024-09-12 10:50:47,826 - numba.core.byteflow - DEBUG - dispatch pc=230, inst=COMPARE_OP(arg=0, lineno=462)\n", - "2024-09-12 10:50:47,827 - numba.core.byteflow - DEBUG - stack ['$i222.17', '$228call_function.20']\n", - "2024-09-12 10:50:47,827 - numba.core.byteflow - DEBUG - dispatch pc=232, inst=POP_JUMP_IF_TRUE(arg=49, lineno=462)\n", - "2024-09-12 10:50:47,828 - numba.core.byteflow - DEBUG - stack ['$230compare_op.21']\n", - "2024-09-12 10:50:47,829 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=234, stack=(), blockstack=(), npush=0), Edge(pc=96, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:47,829 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=260 nstack_initial=0), State(pc_initial=298 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=96 nstack_initial=0)])\n", - "2024-09-12 10:50:47,830 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:47,830 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=260 nstack_initial=0)\n", - "2024-09-12 10:50:47,831 - numba.core.byteflow - DEBUG - dispatch pc=260, inst=LOAD_GLOBAL(arg=9, lineno=485)\n", - "2024-09-12 10:50:47,832 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,832 - numba.core.byteflow - DEBUG - dispatch pc=262, inst=LOAD_FAST(arg=2, lineno=485)\n", - "2024-09-12 10:50:47,833 - numba.core.byteflow - DEBUG - stack ['$260load_global.0']\n", - "2024-09-12 10:50:47,833 - numba.core.byteflow - DEBUG - dispatch pc=264, inst=CALL_FUNCTION(arg=1, lineno=485)\n", - "2024-09-12 10:50:47,834 - numba.core.byteflow - DEBUG - stack ['$260load_global.0', '$starts262.1']\n", - "2024-09-12 10:50:47,835 - numba.core.byteflow - DEBUG - dispatch pc=266, inst=LOAD_CONST(arg=2, lineno=485)\n", - "2024-09-12 10:50:47,835 - numba.core.byteflow - DEBUG - stack ['$264call_function.2']\n", - "2024-09-12 10:50:47,836 - numba.core.byteflow - DEBUG - dispatch pc=268, inst=COMPARE_OP(arg=2, lineno=485)\n", - "2024-09-12 10:50:47,836 - numba.core.byteflow - DEBUG - stack ['$264call_function.2', '$const266.3']\n", - "2024-09-12 10:50:47,837 - numba.core.byteflow - DEBUG - dispatch pc=270, inst=POP_JUMP_IF_FALSE(arg=150, lineno=485)\n", - "2024-09-12 10:50:47,847 - numba.core.byteflow - DEBUG - stack ['$268compare_op.4']\n", - "2024-09-12 10:50:47,847 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=272, stack=(), blockstack=(), npush=0), Edge(pc=298, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:47,848 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=298 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=96 nstack_initial=0), State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:47,849 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:47,850 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=298 nstack_initial=0)\n", - "2024-09-12 10:50:47,850 - numba.core.byteflow - DEBUG - dispatch pc=298, inst=LOAD_GLOBAL(arg=16, lineno=490)\n", - "2024-09-12 10:50:47,851 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,851 - numba.core.byteflow - DEBUG - dispatch pc=300, inst=LOAD_FAST(arg=2, lineno=490)\n", - "2024-09-12 10:50:47,852 - numba.core.byteflow - DEBUG - stack ['$298load_global.0']\n", - "2024-09-12 10:50:47,852 - numba.core.byteflow - DEBUG - dispatch pc=302, inst=LOAD_FAST(arg=3, lineno=490)\n", - "2024-09-12 10:50:47,853 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1']\n", - "2024-09-12 10:50:47,854 - numba.core.byteflow - DEBUG - dispatch pc=304, inst=LOAD_FAST(arg=0, lineno=490)\n", - "2024-09-12 10:50:47,855 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2']\n", - "2024-09-12 10:50:47,855 - numba.core.byteflow - DEBUG - dispatch pc=306, inst=LOAD_FAST(arg=5, lineno=490)\n", - "2024-09-12 10:50:47,856 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$coords304.3']\n", - "2024-09-12 10:50:47,856 - numba.core.byteflow - DEBUG - dispatch pc=308, inst=LOAD_CONST(arg=5, lineno=490)\n", - "2024-09-12 10:50:47,857 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$coords304.3', '$i306.4']\n", - "2024-09-12 10:50:47,858 - numba.core.byteflow - DEBUG - dispatch pc=310, inst=BUILD_SLICE(arg=2, lineno=490)\n", - "2024-09-12 10:50:47,858 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$coords304.3', '$i306.4', '$const308.5']\n", - "2024-09-12 10:50:47,859 - numba.core.byteflow - DEBUG - dispatch pc=312, inst=BINARY_SUBSCR(arg=None, lineno=490)\n", - "2024-09-12 10:50:47,859 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$coords304.3', '$310build_slice.7']\n", - "2024-09-12 10:50:47,860 - numba.core.byteflow - DEBUG - dispatch pc=314, inst=LOAD_FAST(arg=1, lineno=490)\n", - "2024-09-12 10:50:47,860 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8']\n", - "2024-09-12 10:50:47,861 - numba.core.byteflow - DEBUG - dispatch pc=316, inst=LOAD_FAST(arg=5, lineno=490)\n", - "2024-09-12 10:50:47,861 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$indices314.9']\n", - "2024-09-12 10:50:47,862 - numba.core.byteflow - DEBUG - dispatch pc=318, inst=LOAD_CONST(arg=5, lineno=490)\n", - "2024-09-12 10:50:47,862 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$indices314.9', '$i316.10']\n", - "2024-09-12 10:50:47,865 - numba.core.byteflow - DEBUG - dispatch pc=320, inst=BUILD_SLICE(arg=2, lineno=490)\n", - "2024-09-12 10:50:47,865 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$indices314.9', '$i316.10', '$const318.11']\n", - "2024-09-12 10:50:47,866 - numba.core.byteflow - DEBUG - dispatch pc=322, inst=BINARY_SUBSCR(arg=None, lineno=490)\n", - "2024-09-12 10:50:47,866 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$indices314.9', '$320build_slice.13']\n", - "2024-09-12 10:50:47,867 - numba.core.byteflow - DEBUG - dispatch pc=324, inst=CALL_FUNCTION(arg=4, lineno=490)\n", - "2024-09-12 10:50:47,868 - numba.core.byteflow - DEBUG - stack ['$298load_global.0', '$starts300.1', '$stops302.2', '$312binary_subscr.8', '$322binary_subscr.14']\n", - "2024-09-12 10:50:47,869 - numba.core.byteflow - DEBUG - dispatch pc=326, inst=STORE_FAST(arg=8, lineno=490)\n", - "2024-09-12 10:50:47,869 - numba.core.byteflow - DEBUG - stack ['$324call_function.15']\n", - "2024-09-12 10:50:47,870 - numba.core.byteflow - DEBUG - dispatch pc=328, inst=LOAD_GLOBAL(arg=17, lineno=491)\n", - "2024-09-12 10:50:47,870 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,871 - numba.core.byteflow - DEBUG - dispatch pc=330, inst=LOAD_FAST(arg=8, lineno=491)\n", - "2024-09-12 10:50:47,871 - numba.core.byteflow - DEBUG - stack ['$328load_global.16']\n", - "2024-09-12 10:50:47,872 - numba.core.byteflow - DEBUG - dispatch pc=332, inst=CALL_FUNCTION(arg=1, lineno=491)\n", - "2024-09-12 10:50:47,872 - numba.core.byteflow - DEBUG - stack ['$328load_global.16', '$mask330.17']\n", - "2024-09-12 10:50:47,873 - numba.core.byteflow - DEBUG - dispatch pc=334, inst=LOAD_CONST(arg=6, lineno=491)\n", - "2024-09-12 10:50:47,874 - numba.core.byteflow - DEBUG - stack ['$332call_function.18']\n", - "2024-09-12 10:50:47,874 - numba.core.byteflow - DEBUG - dispatch pc=336, inst=BUILD_TUPLE(arg=2, lineno=491)\n", - "2024-09-12 10:50:47,875 - numba.core.byteflow - DEBUG - stack ['$332call_function.18', '$const334.19']\n", - "2024-09-12 10:50:47,875 - numba.core.byteflow - DEBUG - dispatch pc=338, inst=RETURN_VALUE(arg=None, lineno=491)\n", - "2024-09-12 10:50:47,876 - numba.core.byteflow - DEBUG - stack ['$336build_tuple.20']\n", - "2024-09-12 10:50:47,878 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:47,879 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=234 nstack_initial=0), State(pc_initial=234 nstack_initial=0), State(pc_initial=96 nstack_initial=0), State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:47,879 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=234 nstack_initial=0), State(pc_initial=96 nstack_initial=0), State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:47,880 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=0), State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:47,880 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=272 nstack_initial=0), State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:47,881 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:47,881 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=272 nstack_initial=0)\n", - "2024-09-12 10:50:47,882 - numba.core.byteflow - DEBUG - dispatch pc=272, inst=LOAD_GLOBAL(arg=8, lineno=486)\n", - "2024-09-12 10:50:47,882 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:47,883 - numba.core.byteflow - DEBUG - dispatch pc=274, inst=LOAD_METHOD(arg=15, lineno=486)\n", - "2024-09-12 10:50:47,883 - numba.core.byteflow - DEBUG - stack ['$272load_global.0']\n", - "2024-09-12 10:50:47,884 - numba.core.byteflow - DEBUG - dispatch pc=276, inst=LOAD_FAST(arg=2, lineno=486)\n", - "2024-09-12 10:50:47,884 - numba.core.byteflow - DEBUG - stack ['$274load_method.1']\n", - "2024-09-12 10:50:47,885 - numba.core.byteflow - DEBUG - dispatch pc=278, inst=LOAD_CONST(arg=1, lineno=486)\n", - "2024-09-12 10:50:47,885 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$starts276.2']\n", - "2024-09-12 10:50:47,888 - numba.core.byteflow - DEBUG - dispatch pc=280, inst=BINARY_SUBSCR(arg=None, lineno=486)\n", - "2024-09-12 10:50:47,888 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$starts276.2', '$const278.3']\n", - "2024-09-12 10:50:47,889 - numba.core.byteflow - DEBUG - dispatch pc=282, inst=LOAD_FAST(arg=3, lineno=486)\n", - "2024-09-12 10:50:47,889 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$280binary_subscr.4']\n", - "2024-09-12 10:50:47,891 - numba.core.byteflow - DEBUG - dispatch pc=284, inst=LOAD_CONST(arg=1, lineno=486)\n", - "2024-09-12 10:50:47,891 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$280binary_subscr.4', '$stops282.5']\n", - "2024-09-12 10:50:47,892 - numba.core.byteflow - DEBUG - dispatch pc=286, inst=BINARY_SUBSCR(arg=None, lineno=486)\n", - "2024-09-12 10:50:47,892 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$280binary_subscr.4', '$stops282.5', '$const284.6']\n", - "2024-09-12 10:50:47,893 - numba.core.byteflow - DEBUG - dispatch pc=288, inst=BUILD_LIST(arg=2, lineno=486)\n", - "2024-09-12 10:50:47,893 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$280binary_subscr.4', '$286binary_subscr.7']\n", - "2024-09-12 10:50:47,894 - numba.core.byteflow - DEBUG - dispatch pc=290, inst=CALL_METHOD(arg=1, lineno=486)\n", - "2024-09-12 10:50:47,895 - numba.core.byteflow - DEBUG - stack ['$274load_method.1', '$288build_list.8']\n", - "2024-09-12 10:50:47,896 - numba.core.byteflow - DEBUG - dispatch pc=292, inst=LOAD_CONST(arg=4, lineno=486)\n", - "2024-09-12 10:50:47,896 - numba.core.byteflow - DEBUG - stack ['$290call_method.9']\n", - "2024-09-12 10:50:47,897 - numba.core.byteflow - DEBUG - dispatch pc=294, inst=BUILD_TUPLE(arg=2, lineno=486)\n", - "2024-09-12 10:50:47,898 - numba.core.byteflow - DEBUG - stack ['$290call_method.9', '$const292.10']\n", - "2024-09-12 10:50:47,898 - numba.core.byteflow - DEBUG - dispatch pc=296, inst=RETURN_VALUE(arg=None, lineno=486)\n", - "2024-09-12 10:50:47,899 - numba.core.byteflow - DEBUG - stack ['$294build_tuple.11']\n", - "2024-09-12 10:50:47,900 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:47,901 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=298 nstack_initial=0)])\n", - "2024-09-12 10:50:47,901 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:47,902 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=96 nstack_initial=0): set(),\n", - " State(pc_initial=184 nstack_initial=0): set(),\n", - " State(pc_initial=186 nstack_initial=0): set(),\n", - " State(pc_initial=234 nstack_initial=0): set(),\n", - " State(pc_initial=260 nstack_initial=0): set(),\n", - " State(pc_initial=272 nstack_initial=0): set(),\n", - " State(pc_initial=298 nstack_initial=0): set()})\n", - "2024-09-12 10:50:47,903 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:47,904 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:47,905 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:47,905 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:47,906 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:47,907 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:47,907 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'item': '$4load_attr.1', 'res': '$6load_attr.2'}), (8, {'item': '$6load_attr.2', 'res': '$8load_method.3'}), (10, {'res': '$10load_global.4'}), (12, {'item': '$10load_global.4', 'res': '$12load_attr.5'}), (14, {'item': '$12load_attr.5', 'res': '$14load_attr.6'}), (16, {'func': '$8load_method.3', 'args': ['$14load_attr.6'], 'res': '$16call_method.7'}), (18, {'value': '$16call_method.7'}), (20, {'res': '$starts20.8'}), (22, {'item': '$starts20.8', 'res': '$22load_method.9'}), (24, {'res': '$const24.10'}), (26, {'func': '$22load_method.9', 'args': ['$const24.10'], 'res': '$26call_method.11'}), (30, {'res': '$30load_global.12'}), (32, {'item': '$30load_global.12', 'res': '$32load_attr.13'}), (34, {'item': '$32load_attr.13', 'res': '$34load_attr.14'}), (36, {'item': '$34load_attr.14', 'res': '$36load_method.15'}), (38, {'res': '$38load_global.16'}), (40, {'item': '$38load_global.16', 'res': '$40load_attr.17'}), (42, {'item': '$40load_attr.17', 'res': '$42load_attr.18'}), (44, {'func': '$36load_method.15', 'args': ['$42load_attr.18'], 'res': '$44call_method.19'}), (46, {'value': '$44call_method.19'}), (48, {'res': '$stops48.20'}), (50, {'item': '$stops48.20', 'res': '$50load_method.21'}), (52, {'res': '$coords52.22'}), (54, {'item': '$coords52.22', 'res': '$54load_attr.23'}), (56, {'res': '$const56.24'}), (58, {'index': '$const56.24', 'target': '$54load_attr.23', 'res': '$58binary_subscr.25'}), (60, {'func': '$50load_method.21', 'args': ['$58binary_subscr.25'], 'res': '$60call_method.26'}), (64, {'res': '$64load_global.27'}), (66, {'item': '$64load_global.27', 'res': '$66load_method.28'}), (68, {'res': '$coords68.29'}), (70, {'item': '$coords68.29', 'res': '$70load_attr.30'}), (72, {'res': '$const72.31'}), (74, {'index': '$const72.31', 'target': '$70load_attr.30', 'res': '$74binary_subscr.32'}), (76, {'func': '$66load_method.28', 'args': ['$74binary_subscr.32'], 'res': '$76call_method.33'}), (78, {'value': '$76call_method.33'}), (80, {'res': '$const80.34'}), (82, {'value': '$const80.34'}), (84, {'res': '$i84.35'}), (86, {'res': '$86load_global.36'}), (88, {'res': '$indices88.37'}), (90, {'func': '$86load_global.36', 'args': ['$indices88.37'], 'res': '$90call_function.38'}), (92, {'lhs': '$i84.35', 'rhs': '$90call_function.38', 'res': '$92compare_op.39'}), (94, {'pred': '$92compare_op.39'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: (), 234: ()})\n", - "2024-09-12 10:50:47,908 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=96 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((96, {'res': '$96load_global.0'}), (98, {'res': '$starts98.1'}), (100, {'func': '$96load_global.0', 'args': ['$starts98.1'], 'res': '$100call_function.2'}), (102, {'value': '$100call_function.2'}), (104, {'res': '$104load_global.3'}), (106, {'res': '$106load_global.4'}), (108, {'res': '$indices108.5'}), (110, {'res': '$i110.6'}), (112, {'res': '$const112.7'}), (114, {'items': ['$i110.6', '$const112.7'], 'res': '$114build_tuple.8'}), (116, {'index': '$114build_tuple.8', 'target': '$indices108.5', 'res': '$116binary_subscr.9'}), (118, {'res': '$indices118.10'}), (120, {'res': '$i120.11'}), (122, {'res': '$const122.12'}), (124, {'items': ['$i120.11', '$const122.12'], 'res': '$124build_tuple.13'}), (126, {'index': '$124build_tuple.13', 'target': '$indices118.10', 'res': '$126binary_subscr.14'}), (128, {'res': '$indices128.15'}), (130, {'res': '$i130.16'}), (132, {'res': '$const132.17'}), (134, {'items': ['$i130.16', '$const132.17'], 'res': '$134build_tuple.18'}), (136, {'index': '$134build_tuple.18', 'target': '$indices128.15', 'res': '$136binary_subscr.19'}), (138, {'func': '$106load_global.4', 'args': ['$116binary_subscr.9', '$126binary_subscr.14', '$136binary_subscr.19'], 'res': '$138call_function.20'}), (140, {'func': '$104load_global.3', 'args': ['$138call_function.20'], 'res': '$140call_function.21'}), (142, {'res': '$n_pairs142.22'}), (144, {'lhs': '$140call_function.21', 'rhs': '$n_pairs142.22', 'res': '$144binary_multiply.23'}), (146, {'res': '$const146.24'}), (148, {'lhs': '$144binary_multiply.23', 'rhs': '$const146.24', 'res': '$148binary_add.25'}), (150, {'value': '$148binary_add.25'}), (152, {'res': '$n_current_slices152.26'}), (154, {'res': '$154load_global.27'}), (156, {'item': '$154load_global.27', 'res': '$156load_method.28'}), (158, {'res': '$n_current_slices158.29'}), (160, {'res': '$160load_global.30'}), (162, {'res': '$n_pairs162.31'}), (164, {'res': '$const164.32'}), (166, {'func': '$160load_global.30', 'args': ['$n_pairs162.31', '$const164.32'], 'res': '$166call_function.33'}), (168, {'lhs': '$n_current_slices158.29', 'rhs': '$166call_function.33', 'res': '$168binary_true_divide.34'}), (170, {'func': '$156load_method.28', 'args': ['$168binary_true_divide.34'], 'res': '$170call_method.35'}), (172, {'lhs': '$n_current_slices152.26', 'rhs': '$170call_method.35', 'res': '$172binary_multiply.36'}), (174, {'res': '$n_matches174.37'}), (176, {'res': '$n_pairs176.38'}), (178, {'lhs': '$n_matches174.37', 'rhs': '$n_pairs176.38', 'res': '$178binary_add.39'}), (180, {'lhs': '$172binary_multiply.36', 'rhs': '$178binary_add.39', 'res': '$180compare_op.40'}), (182, {'pred': '$180compare_op.40'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={184: (), 186: ()})\n", - "2024-09-12 10:50:47,909 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=184 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((184, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={234: ()})\n", - "2024-09-12 10:50:47,909 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=186 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((186, {'res': '$186load_global.0'}), (188, {'res': '$starts188.1'}), (190, {'res': '$stops190.2'}), (192, {'res': '$coords192.3'}), (194, {'res': '$i194.4'}), (196, {'index': '$i194.4', 'target': '$coords192.3', 'res': '$196binary_subscr.5'}), (198, {'res': '$indices198.6'}), (200, {'res': '$i200.7'}), (202, {'index': '$i200.7', 'target': '$indices198.6', 'res': '$202binary_subscr.8'}), (204, {'func': '$186load_global.0', 'args': ['$starts188.1', '$stops190.2', '$196binary_subscr.5', '$202binary_subscr.8'], 'res': '$204call_function.9'}), (206, {'iterable': '$204call_function.9', 'stores': ['$206unpack_sequence.10', '$206unpack_sequence.11', '$206unpack_sequence.12'], 'tupleobj': '$206unpack_sequence.13'}), (208, {'value': '$206unpack_sequence.10'}), (210, {'value': '$206unpack_sequence.11'}), (212, {'value': '$206unpack_sequence.12'}), (214, {'res': '$i214.14'}), (216, {'res': '$const216.15'}), (218, {'lhs': '$i214.14', 'rhs': '$const216.15', 'res': '$218inplace_add.16'}), (220, {'value': '$218inplace_add.16'}), (222, {'res': '$i222.17'}), (224, {'res': '$224load_global.18'}), (226, {'res': '$indices226.19'}), (228, {'func': '$224load_global.18', 'args': ['$indices226.19'], 'res': '$228call_function.20'}), (230, {'lhs': '$i222.17', 'rhs': '$228call_function.20', 'res': '$230compare_op.21'}), (232, {'pred': '$230compare_op.21'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={234: (), 96: ()})\n", - "2024-09-12 10:50:47,911 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=234 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((234, {'res': '$234load_global.0'}), (236, {'res': '$starts236.1'}), (238, {'res': '$stops238.2'}), (240, {'func': '$234load_global.0', 'args': ['$starts236.1', '$stops238.2'], 'res': '$240call_function.3'}), (242, {'iterable': '$240call_function.3', 'stores': ['$242unpack_sequence.4', '$242unpack_sequence.5'], 'tupleobj': '$242unpack_sequence.6'}), (244, {'value': '$242unpack_sequence.4'}), (246, {'value': '$242unpack_sequence.5'}), (248, {'res': '$i248.7'}), (250, {'res': '$250load_global.8'}), (252, {'res': '$indices252.9'}), (254, {'func': '$250load_global.8', 'args': ['$indices252.9'], 'res': '$254call_function.10'}), (256, {'lhs': '$i248.7', 'rhs': '$254call_function.10', 'res': '$256compare_op.11'}), (258, {'pred': '$256compare_op.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={260: (), 298: ()})\n", - "2024-09-12 10:50:47,911 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=260 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((260, {'res': '$260load_global.0'}), (262, {'res': '$starts262.1'}), (264, {'func': '$260load_global.0', 'args': ['$starts262.1'], 'res': '$264call_function.2'}), (266, {'res': '$const266.3'}), (268, {'lhs': '$264call_function.2', 'rhs': '$const266.3', 'res': '$268compare_op.4'}), (270, {'pred': '$268compare_op.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={272: (), 298: ()})\n", - "2024-09-12 10:50:47,912 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=272 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((272, {'res': '$272load_global.0'}), (274, {'item': '$272load_global.0', 'res': '$274load_method.1'}), (276, {'res': '$starts276.2'}), (278, {'res': '$const278.3'}), (280, {'index': '$const278.3', 'target': '$starts276.2', 'res': '$280binary_subscr.4'}), (282, {'res': '$stops282.5'}), (284, {'res': '$const284.6'}), (286, {'index': '$const284.6', 'target': '$stops282.5', 'res': '$286binary_subscr.7'}), (288, {'items': ['$280binary_subscr.4', '$286binary_subscr.7'], 'res': '$288build_list.8'}), (290, {'func': '$274load_method.1', 'args': ['$288build_list.8'], 'res': '$290call_method.9'}), (292, {'res': '$const292.10'}), (294, {'items': ['$290call_method.9', '$const292.10'], 'res': '$294build_tuple.11'}), (296, {'retval': '$294build_tuple.11', 'castval': '$296return_value.12'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:47,912 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=298 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((298, {'res': '$298load_global.0'}), (300, {'res': '$starts300.1'}), (302, {'res': '$stops302.2'}), (304, {'res': '$coords304.3'}), (306, {'res': '$i306.4'}), (308, {'res': '$const308.5'}), (310, {'start': '$i306.4', 'stop': '$const308.5', 'step': None, 'res': '$310build_slice.7', 'slicevar': '$310build_slice.6'}), (312, {'index': '$310build_slice.7', 'target': '$coords304.3', 'res': '$312binary_subscr.8'}), (314, {'res': '$indices314.9'}), (316, {'res': '$i316.10'}), (318, {'res': '$const318.11'}), (320, {'start': '$i316.10', 'stop': '$const318.11', 'step': None, 'res': '$320build_slice.13', 'slicevar': '$320build_slice.12'}), (322, {'index': '$320build_slice.13', 'target': '$indices314.9', 'res': '$322binary_subscr.14'}), (324, {'func': '$298load_global.0', 'args': ['$starts300.1', '$stops302.2', '$312binary_subscr.8', '$322binary_subscr.14'], 'res': '$324call_function.15'}), (326, {'value': '$324call_function.15'}), (328, {'res': '$328load_global.16'}), (330, {'res': '$mask330.17'}), (332, {'func': '$328load_global.16', 'args': ['$mask330.17'], 'res': '$332call_function.18'}), (334, {'res': '$const334.19'}), (336, {'items': ['$332call_function.18', '$const334.19'], 'res': '$336build_tuple.20'}), (338, {'retval': '$336build_tuple.20', 'castval': '$338return_value.21'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:47,924 - numba.core.interpreter - DEBUG - label 0:\n", - " coords = arg(0, name=coords) ['coords']\n", - " indices = arg(1, name=indices) ['indices']\n", - " $2load_global.0 = global(numba: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=typed) ['$2load_global.0', '$4load_attr.1']\n", - " $6load_attr.2 = getattr(value=$4load_attr.1, attr=List) ['$4load_attr.1', '$6load_attr.2']\n", - " $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list) ['$6load_attr.2', '$8load_method.3']\n", - " $10load_global.4 = global(numba: ) ['$10load_global.4']\n", - " $12load_attr.5 = getattr(value=$10load_global.4, attr=types) ['$10load_global.4', '$12load_attr.5']\n", - " $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp) ['$12load_attr.5', '$14load_attr.6']\n", - " starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None) ['$14load_attr.6', '$8load_method.3', 'starts']\n", - " $22load_method.9 = getattr(value=starts, attr=append) ['$22load_method.9', 'starts']\n", - " $const24.10 = const(int, 0) ['$const24.10']\n", - " $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None) ['$22load_method.9', '$26call_method.11', '$const24.10']\n", - " $30load_global.12 = global(numba: ) ['$30load_global.12']\n", - " $32load_attr.13 = getattr(value=$30load_global.12, attr=typed) ['$30load_global.12', '$32load_attr.13']\n", - " $34load_attr.14 = getattr(value=$32load_attr.13, attr=List) ['$32load_attr.13', '$34load_attr.14']\n", - " $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list) ['$34load_attr.14', '$36load_method.15']\n", - " $38load_global.16 = global(numba: ) ['$38load_global.16']\n", - " $40load_attr.17 = getattr(value=$38load_global.16, attr=types) ['$38load_global.16', '$40load_attr.17']\n", - " $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp) ['$40load_attr.17', '$42load_attr.18']\n", - " stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None) ['$36load_method.15', '$42load_attr.18', 'stops']\n", - " $50load_method.21 = getattr(value=stops, attr=append) ['$50load_method.21', 'stops']\n", - " $54load_attr.23 = getattr(value=coords, attr=shape) ['$54load_attr.23', 'coords']\n", - " $const56.24 = const(int, 1) ['$const56.24']\n", - " $58binary_subscr.25 = getitem(value=$54load_attr.23, index=$const56.24, fn=) ['$54load_attr.23', '$58binary_subscr.25', '$const56.24']\n", - " $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None) ['$50load_method.21', '$58binary_subscr.25', '$60call_method.26']\n", - " $64load_global.27 = global(np: ) ['$64load_global.27']\n", - " $66load_method.28 = getattr(value=$64load_global.27, attr=intp) ['$64load_global.27', '$66load_method.28']\n", - " $70load_attr.30 = getattr(value=coords, attr=shape) ['$70load_attr.30', 'coords']\n", - " $const72.31 = const(int, 1) ['$const72.31']\n", - " $74binary_subscr.32 = getitem(value=$70load_attr.30, index=$const72.31, fn=) ['$70load_attr.30', '$74binary_subscr.32', '$const72.31']\n", - " n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None) ['$66load_method.28', '$74binary_subscr.32', 'n_matches']\n", - " i = const(int, 0) ['i']\n", - " $86load_global.36 = global(len: ) ['$86load_global.36']\n", - " $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None) ['$86load_global.36', '$90call_function.38', 'indices']\n", - " $92compare_op.39 = i < $90call_function.38 ['$90call_function.38', '$92compare_op.39', 'i']\n", - " bool94 = global(bool: ) ['bool94']\n", - " $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None) ['$92compare_op.39', '$94pred', 'bool94']\n", - " branch $94pred, 96, 234 ['$94pred']\n", - "label 96:\n", - " $96load_global.0 = global(len: ) ['$96load_global.0']\n", - " n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None) ['$96load_global.0', 'n_pairs', 'starts']\n", - " $104load_global.3 = global(len: ) ['$104load_global.3']\n", - " $106load_global.4 = global(range: ) ['$106load_global.4']\n", - " $const112.7 = const(int, 0) ['$const112.7']\n", - " $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)]) ['$114build_tuple.8', '$const112.7', 'i']\n", - " $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=) ['$114build_tuple.8', '$116binary_subscr.9', 'indices']\n", - " $const122.12 = const(int, 1) ['$const122.12']\n", - " $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)]) ['$124build_tuple.13', '$const122.12', 'i']\n", - " $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=) ['$124build_tuple.13', '$126binary_subscr.14', 'indices']\n", - " $const132.17 = const(int, 2) ['$const132.17']\n", - " $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)]) ['$134build_tuple.18', '$const132.17', 'i']\n", - " $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=) ['$134build_tuple.18', '$136binary_subscr.19', 'indices']\n", - " $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None) ['$106load_global.4', '$116binary_subscr.9', '$126binary_subscr.14', '$136binary_subscr.19', '$138call_function.20']\n", - " $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None) ['$104load_global.3', '$138call_function.20', '$140call_function.21']\n", - " $144binary_multiply.23 = $140call_function.21 * n_pairs ['$140call_function.21', '$144binary_multiply.23', 'n_pairs']\n", - " $const146.24 = const(int, 2) ['$const146.24']\n", - " n_current_slices = $144binary_multiply.23 + $const146.24 ['$144binary_multiply.23', '$const146.24', 'n_current_slices']\n", - " $154load_global.27 = global(np: ) ['$154load_global.27']\n", - " $156load_method.28 = getattr(value=$154load_global.27, attr=log) ['$154load_global.27', '$156load_method.28']\n", - " $160load_global.30 = global(max: ) ['$160load_global.30']\n", - " $const164.32 = const(int, 1) ['$const164.32']\n", - " $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None) ['$160load_global.30', '$166call_function.33', '$const164.32', 'n_pairs']\n", - " $168binary_true_divide.34 = n_current_slices / $166call_function.33 ['$166call_function.33', '$168binary_true_divide.34', 'n_current_slices']\n", - " $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None) ['$156load_method.28', '$168binary_true_divide.34', '$170call_method.35']\n", - " $172binary_multiply.36 = n_current_slices * $170call_method.35 ['$170call_method.35', '$172binary_multiply.36', 'n_current_slices']\n", - " $178binary_add.39 = n_matches + n_pairs ['$178binary_add.39', 'n_matches', 'n_pairs']\n", - " $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39 ['$172binary_multiply.36', '$178binary_add.39', '$180compare_op.40']\n", - " bool182 = global(bool: ) ['bool182']\n", - " $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None) ['$180compare_op.40', '$182pred', 'bool182']\n", - " branch $182pred, 184, 186 ['$182pred']\n", - "label 184:\n", - " jump 234 []\n", - "label 186:\n", - " $186load_global.0 = global(_get_mask_pairs: CPUDispatcher()) ['$186load_global.0']\n", - " $196binary_subscr.5 = getitem(value=coords, index=i, fn=) ['$196binary_subscr.5', 'coords', 'i']\n", - " $202binary_subscr.8 = getitem(value=indices, index=i, fn=) ['$202binary_subscr.8', 'i', 'indices']\n", - " $204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None) ['$186load_global.0', '$196binary_subscr.5', '$202binary_subscr.8', '$204call_function.9', 'starts', 'stops']\n", - " $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3) ['$204call_function.9', '$206unpack_sequence.13']\n", - " $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=) ['$206unpack_sequence.10', '$206unpack_sequence.13']\n", - " $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=) ['$206unpack_sequence.11', '$206unpack_sequence.13']\n", - " $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=) ['$206unpack_sequence.12', '$206unpack_sequence.13']\n", - " starts = $206unpack_sequence.10 ['$206unpack_sequence.10', 'starts']\n", - " stops = $206unpack_sequence.11 ['$206unpack_sequence.11', 'stops']\n", - " n_matches = $206unpack_sequence.12 ['$206unpack_sequence.12', 'n_matches']\n", - " $const216.15 = const(int, 1) ['$const216.15']\n", - " $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined) ['$218inplace_add.16', '$const216.15', 'i']\n", - " i = $218inplace_add.16 ['$218inplace_add.16', 'i']\n", - " $224load_global.18 = global(len: ) ['$224load_global.18']\n", - " $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None) ['$224load_global.18', '$228call_function.20', 'indices']\n", - " $230compare_op.21 = i < $228call_function.20 ['$228call_function.20', '$230compare_op.21', 'i']\n", - " bool232 = global(bool: ) ['bool232']\n", - " $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None) ['$230compare_op.21', '$232pred', 'bool232']\n", - " branch $232pred, 96, 234 ['$232pred']\n", - "label 234:\n", - " $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher()) ['$234load_global.0']\n", - " $240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None) ['$234load_global.0', '$240call_function.3', 'starts', 'stops']\n", - " $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2) ['$240call_function.3', '$242unpack_sequence.6']\n", - " $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=) ['$242unpack_sequence.4', '$242unpack_sequence.6']\n", - " $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=) ['$242unpack_sequence.5', '$242unpack_sequence.6']\n", - " starts.1 = $242unpack_sequence.4 ['$242unpack_sequence.4', 'starts.1']\n", - " stops.1 = $242unpack_sequence.5 ['$242unpack_sequence.5', 'stops.1']\n", - " $250load_global.8 = global(len: ) ['$250load_global.8']\n", - " $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None) ['$250load_global.8', '$254call_function.10', 'indices']\n", - " $256compare_op.11 = i == $254call_function.10 ['$254call_function.10', '$256compare_op.11', 'i']\n", - " bool258 = global(bool: ) ['bool258']\n", - " $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None) ['$256compare_op.11', '$258pred', 'bool258']\n", - " branch $258pred, 260, 298 ['$258pred']\n", - "label 260:\n", - " $260load_global.0 = global(len: ) ['$260load_global.0']\n", - " $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None) ['$260load_global.0', '$264call_function.2', 'starts.1']\n", - " $const266.3 = const(int, 1) ['$const266.3']\n", - " $268compare_op.4 = $264call_function.2 == $const266.3 ['$264call_function.2', '$268compare_op.4', '$const266.3']\n", - " bool270 = global(bool: ) ['bool270']\n", - " $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None) ['$268compare_op.4', '$270pred', 'bool270']\n", - " branch $270pred, 272, 298 ['$270pred']\n", - "label 272:\n", - " $272load_global.0 = global(np: ) ['$272load_global.0']\n", - " $274load_method.1 = getattr(value=$272load_global.0, attr=array) ['$272load_global.0', '$274load_method.1']\n", - " $const278.3 = const(int, 0) ['$const278.3']\n", - " $280binary_subscr.4 = getitem(value=starts.1, index=$const278.3, fn=) ['$280binary_subscr.4', '$const278.3', 'starts.1']\n", - " $const284.6 = const(int, 0) ['$const284.6']\n", - " $286binary_subscr.7 = getitem(value=stops.1, index=$const284.6, fn=) ['$286binary_subscr.7', '$const284.6', 'stops.1']\n", - " $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)]) ['$280binary_subscr.4', '$286binary_subscr.7', '$288build_list.8']\n", - " $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None) ['$274load_method.1', '$288build_list.8', '$290call_method.9']\n", - " $const292.10 = const(bool, True) ['$const292.10']\n", - " $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)]) ['$290call_method.9', '$294build_tuple.11', '$const292.10']\n", - " $296return_value.12 = cast(value=$294build_tuple.11) ['$294build_tuple.11', '$296return_value.12']\n", - " return $296return_value.12 ['$296return_value.12']\n", - "label 298:\n", - " $298load_global.0 = global(_filter_pairs: CPUDispatcher()) ['$298load_global.0']\n", - " $const308.5 = const(NoneType, None) ['$const308.5']\n", - " $310build_slice.6 = global(slice: ) ['$310build_slice.6']\n", - " $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None) ['$310build_slice.6', '$310build_slice.7', '$const308.5', 'i']\n", - " $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=) ['$310build_slice.7', '$312binary_subscr.8', 'coords']\n", - " $const318.11 = const(NoneType, None) ['$const318.11']\n", - " $320build_slice.12 = global(slice: ) ['$320build_slice.12']\n", - " $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None) ['$320build_slice.12', '$320build_slice.13', '$const318.11', 'i']\n", - " $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=) ['$320build_slice.13', '$322binary_subscr.14', 'indices']\n", - " mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None) ['$298load_global.0', '$312binary_subscr.8', '$322binary_subscr.14', 'mask', 'starts.1', 'stops.1']\n", - " $328load_global.16 = global(array_from_list_intp: CPUDispatcher()) ['$328load_global.16']\n", - " $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None) ['$328load_global.16', '$332call_function.18', 'mask']\n", - " $const334.19 = const(bool, False) ['$const334.19']\n", - " $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)]) ['$332call_function.18', '$336build_tuple.20', '$const334.19']\n", - " $338return_value.21 = cast(value=$336build_tuple.20) ['$336build_tuple.20', '$338return_value.21']\n", - " return $338return_value.21 ['$338return_value.21']\n", - "\n", - "2024-09-12 10:50:47,973 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:47,975 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:47,975 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:47,976 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:47,977 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:47,978 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:47,978 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:47,979 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:47,980 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:47,981 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:47,981 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:47,982 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:47,983 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:47,983 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:47,984 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:47,985 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:47,985 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:47,986 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:47,987 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:47,988 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:47,988 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:47,989 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:47,990 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:47,991 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:47,991 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:47,992 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:47,993 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:47,993 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:47,994 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:47,995 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:47,996 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:47,997 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:47,997 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:47,998 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:47,999 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:47,999 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:48,000 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,001 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,001 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:48,002 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,003 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:48,004 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 96\n", - "2024-09-12 10:50:48,004 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,005 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,006 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,007 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:48,007 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:48,008 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:48,009 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,009 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:48,010 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:48,011 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,011 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:48,012 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:48,013 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,014 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:48,014 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,015 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,016 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:48,016 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:48,017 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:48,018 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,019 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:48,019 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:48,020 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:48,021 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,021 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:48,022 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,023 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:48,024 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:48,024 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:48,025 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:48,026 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,027 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:48,027 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 184\n", - "2024-09-12 10:50:48,028 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,029 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:48,030 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 186\n", - "2024-09-12 10:50:48,030 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,031 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,032 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:48,032 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:48,033 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,034 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:48,035 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,035 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,036 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:48,037 - numba.core.ssa - DEBUG - on stmt: starts = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,037 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,038 - numba.core.ssa - DEBUG - on stmt: n_matches = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,039 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:48,061 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,062 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:48,062 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:48,063 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,063 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:48,064 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:48,064 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,065 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:48,066 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 234\n", - "2024-09-12 10:50:48,066 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,067 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,067 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,068 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:48,069 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,069 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,070 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:48,070 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:48,071 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:48,071 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,072 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:48,073 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:48,073 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,074 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:48,074 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 260\n", - "2024-09-12 10:50:48,075 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,075 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,076 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,076 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:48,077 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:48,078 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:48,078 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,079 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:48,080 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 272\n", - "2024-09-12 10:50:48,080 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,081 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:48,081 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:48,082 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:48,082 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:48,083 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:48,083 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:48,084 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:48,084 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,085 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:48,086 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:48,086 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:48,087 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:48,087 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 298\n", - "2024-09-12 10:50:48,088 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,089 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,089 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:48,090 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:48,090 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,091 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:48,092 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:48,092 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:48,093 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,093 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:48,094 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,105 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:48,105 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,106 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:48,107 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:48,107 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:48,108 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:48,115 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$104load_global.3': [],\n", - " '$106load_global.4': [],\n", - " '$10load_global.4': [],\n", - " '$114build_tuple.8': [],\n", - " '$116binary_subscr.9': [],\n", - " '$124build_tuple.13': [],\n", - " '$126binary_subscr.14': [],\n", - " '$12load_attr.5': [],\n", - " '$134build_tuple.18': [],\n", - " '$136binary_subscr.19': [],\n", - " '$138call_function.20': [],\n", - " '$140call_function.21': [],\n", - " '$144binary_multiply.23': [],\n", - " '$14load_attr.6': [],\n", - " '$154load_global.27': [],\n", - " '$156load_method.28': [],\n", - " '$160load_global.30': [],\n", - " '$166call_function.33': [],\n", - " '$168binary_true_divide.34': [],\n", - " '$170call_method.35': [],\n", - " '$172binary_multiply.36': [],\n", - " '$178binary_add.39': [],\n", - " '$180compare_op.40': [],\n", - " '$182pred': [],\n", - " '$186load_global.0': [],\n", - " '$196binary_subscr.5': [],\n", - " '$202binary_subscr.8': [],\n", - " '$204call_function.9': [],\n", - " '$206unpack_sequence.10': [],\n", - " '$206unpack_sequence.11': [],\n", - " '$206unpack_sequence.12': [],\n", - " '$206unpack_sequence.13': [],\n", - " '$218inplace_add.16': [],\n", - " '$224load_global.18': [],\n", - " '$228call_function.20': [],\n", - " '$22load_method.9': [],\n", - " '$230compare_op.21': [],\n", - " '$232pred': [],\n", - " '$234load_global.0': [],\n", - " '$240call_function.3': [],\n", - " '$242unpack_sequence.4': [],\n", - " '$242unpack_sequence.5': [],\n", - " '$242unpack_sequence.6': [],\n", - " '$250load_global.8': [],\n", - " '$254call_function.10': [],\n", - " '$256compare_op.11': [],\n", - " '$258pred': [],\n", - " '$260load_global.0': [],\n", - " '$264call_function.2': [],\n", - " '$268compare_op.4': [],\n", - " '$26call_method.11': [],\n", - " '$270pred': [],\n", - " '$272load_global.0': [],\n", - " '$274load_method.1': [],\n", - " '$280binary_subscr.4': [],\n", - " '$286binary_subscr.7': [],\n", - " '$288build_list.8': [],\n", - " '$290call_method.9': [],\n", - " '$294build_tuple.11': [],\n", - " '$296return_value.12': [],\n", - " '$298load_global.0': [],\n", - " '$2load_global.0': [],\n", - " '$30load_global.12': [],\n", - " '$310build_slice.6': [],\n", - " '$310build_slice.7': [],\n", - " '$312binary_subscr.8': [],\n", - " '$320build_slice.12': [],\n", - " '$320build_slice.13': [],\n", - " '$322binary_subscr.14': [],\n", - " '$328load_global.16': [],\n", - " '$32load_attr.13': [],\n", - " '$332call_function.18': [],\n", - " '$336build_tuple.20': [],\n", - " '$338return_value.21': [],\n", - " '$34load_attr.14': [],\n", - " '$36load_method.15': [],\n", - " '$38load_global.16': [],\n", - " '$40load_attr.17': [],\n", - " '$42load_attr.18': [],\n", - " '$4load_attr.1': [],\n", - " '$50load_method.21': [],\n", - " '$54load_attr.23': [],\n", - " '$58binary_subscr.25': [],\n", - " '$60call_method.26': [],\n", - " '$64load_global.27': [],\n", - " '$66load_method.28': [],\n", - " '$6load_attr.2': [],\n", - " '$70load_attr.30': [],\n", - " '$74binary_subscr.32': [],\n", - " '$86load_global.36': [],\n", - " '$8load_method.3': [],\n", - " '$90call_function.38': [],\n", - " '$92compare_op.39': [],\n", - " '$94pred': [],\n", - " '$96load_global.0': [],\n", - " '$const112.7': [],\n", - " '$const122.12': [],\n", - " '$const132.17': [],\n", - " '$const146.24': [],\n", - " '$const164.32': [],\n", - " '$const216.15': [],\n", - " '$const24.10': [],\n", - " '$const266.3': [],\n", - " '$const278.3': [],\n", - " '$const284.6': [],\n", - " '$const292.10': [],\n", - " '$const308.5': [],\n", - " '$const318.11': [],\n", - " '$const334.19': [],\n", - " '$const56.24': [],\n", - " '$const72.31': [],\n", - " 'bool182': [],\n", - " 'bool232': [],\n", - " 'bool258': [],\n", - " 'bool270': [],\n", - " 'bool94': [],\n", - " 'coords': [],\n", - " 'i': [,\n", - " ],\n", - " 'indices': [],\n", - " 'mask': [],\n", - " 'n_current_slices': [],\n", - " 'n_matches': [,\n", - " ],\n", - " 'n_pairs': [],\n", - " 'starts': [,\n", - " ],\n", - " 'starts.1': [],\n", - " 'stops': [,\n", - " ],\n", - " 'stops.1': []})\n", - "2024-09-12 10:50:48,116 - numba.core.ssa - DEBUG - SSA violators {'starts', 'n_matches', 'i', 'stops'}\n", - "2024-09-12 10:50:48,117 - numba.core.ssa - DEBUG - Fix SSA violator on var starts\n", - "2024-09-12 10:50:48,118 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:48,118 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,119 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:48,120 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:48,120 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:48,121 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:48,121 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:48,122 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:48,123 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:48,123 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:48,124 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:48,125 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,125 - numba.core.ssa - DEBUG - first assign: starts\n", - "2024-09-12 10:50:48,126 - numba.core.ssa - DEBUG - replaced with: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,127 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:48,127 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:48,128 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,128 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:48,129 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:48,130 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:48,130 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:48,131 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:48,132 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:48,132 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:48,133 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,133 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:48,134 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,135 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:48,135 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:48,136 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,137 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,137 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:48,138 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,138 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:48,139 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:48,140 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,146 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:48,147 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:48,148 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,148 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,149 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:48,150 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,150 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:48,151 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:48,152 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,153 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,153 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,154 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:48,155 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:48,155 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:48,156 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,156 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:48,157 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:48,159 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,159 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:48,160 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:48,161 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,161 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:48,162 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,162 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,163 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:48,164 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:48,164 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:48,165 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,165 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:48,166 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:48,167 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:48,167 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,168 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:48,169 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,169 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:48,170 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:48,170 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:48,171 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:48,172 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,172 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:48,173 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:48,173 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,174 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:48,175 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:48,175 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,179 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,180 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:48,181 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:48,182 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,182 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:48,183 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,184 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,184 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:48,185 - numba.core.ssa - DEBUG - on stmt: starts = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,185 - numba.core.ssa - DEBUG - replaced with: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,186 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,186 - numba.core.ssa - DEBUG - on stmt: n_matches = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,187 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:48,187 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,188 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:48,189 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:48,189 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,190 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:48,190 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:48,191 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,192 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:48,192 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:48,193 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,193 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,194 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,194 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:48,195 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,196 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,196 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:48,200 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:48,201 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:48,202 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,202 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:48,203 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:48,203 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,204 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:48,204 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:48,205 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,206 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,206 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,207 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:48,207 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:48,208 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:48,208 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,209 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:48,210 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:48,210 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,211 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:48,211 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:48,212 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:48,212 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:48,213 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:48,213 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:48,214 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:48,215 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,215 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:48,216 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:48,216 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:48,217 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:48,217 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:48,218 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,218 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,219 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:48,220 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:48,220 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,221 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:48,221 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:48,222 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:48,222 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,223 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:48,223 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,224 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:48,225 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,225 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:48,226 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:48,226 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:48,227 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:48,227 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 186: []})\n", - "2024-09-12 10:50:48,228 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:48,229 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,229 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:48,230 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:48,237 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:48,238 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:48,238 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:48,239 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:48,239 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:48,240 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:48,240 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:48,241 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,242 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:48,242 - numba.core.ssa - DEBUG - find_def var='starts' stmt=$22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:48,243 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:48,243 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,244 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:48,244 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:48,245 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:48,245 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:48,248 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:48,248 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:48,249 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:48,250 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,250 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:48,251 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,251 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:48,252 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:48,252 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,253 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,253 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:48,254 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,255 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:48,256 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:48,257 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,258 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:48,258 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:48,259 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,259 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,260 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:48,260 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,261 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:48,262 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:48,262 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,263 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,263 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,264 - numba.core.ssa - DEBUG - find_def var='starts' stmt=n_pairs = call $96load_global.0(starts, func=$96load_global.0, args=[Var(starts, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,264 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:48,265 - numba.core.ssa - DEBUG - insert phi node starts.3 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:48,267 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:48,268 - numba.core.ssa - DEBUG - incoming_def starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,268 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:48,269 - numba.core.ssa - DEBUG - incoming_def starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,270 - numba.core.ssa - DEBUG - replaced with: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,271 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:48,271 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:48,272 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:48,272 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,273 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:48,274 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:48,274 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,275 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:48,276 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:48,277 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,277 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:48,278 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,279 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,279 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:48,280 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:48,280 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:48,281 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,281 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:48,282 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:48,282 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:48,283 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,283 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:48,284 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,284 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:48,285 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:48,286 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:48,286 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:48,287 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,287 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:48,288 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:48,288 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,289 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:48,289 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:48,290 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,290 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,291 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:48,291 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:48,292 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,296 - numba.core.ssa - DEBUG - find_def var='starts' stmt=$204call_function.9 = call $186load_global.0(starts, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,297 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:48,297 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:48,298 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:48,299 - numba.core.ssa - DEBUG - replaced with: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,300 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:48,300 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,301 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,301 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:48,302 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,302 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,303 - numba.core.ssa - DEBUG - on stmt: n_matches = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,303 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:48,304 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,304 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:48,305 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:48,305 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,306 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:48,306 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:48,307 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,307 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:48,308 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:48,308 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,309 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,309 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,310 - numba.core.ssa - DEBUG - find_def var='starts' stmt=$240call_function.3 = call $234load_global.0(starts, stops, func=$234load_global.0, args=[Var(starts, indexing.py:455), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,311 - numba.core.ssa - DEBUG - find_def_from_top label 234\n", - "2024-09-12 10:50:48,311 - numba.core.ssa - DEBUG - insert phi node starts.4 = phi(incoming_values=[], incoming_blocks=[]) at 234\n", - "2024-09-12 10:50:48,312 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:48,315 - numba.core.ssa - DEBUG - incoming_def starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,316 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:48,316 - numba.core.ssa - DEBUG - incoming_def starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,317 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-09-12 10:50:48,317 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-09-12 10:50:48,318 - numba.core.ssa - DEBUG - idom 96 from label 184\n", - "2024-09-12 10:50:48,318 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:48,319 - numba.core.ssa - DEBUG - incoming_def starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,320 - numba.core.ssa - DEBUG - replaced with: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,320 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:48,322 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,323 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,323 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:48,324 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:48,324 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:48,325 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,325 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:48,326 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:48,326 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,327 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:48,329 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:48,329 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,330 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,330 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,331 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:48,332 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:48,333 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:48,333 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,334 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:48,334 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:48,335 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,335 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:48,336 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:48,336 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:48,338 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:48,338 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:48,339 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:48,339 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:48,340 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,340 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:48,341 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:48,341 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:48,342 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:48,343 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:48,343 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,344 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,344 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:48,345 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:48,345 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,347 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:48,348 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:48,349 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:48,349 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,350 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:48,351 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,352 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:48,352 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,353 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:48,353 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:48,354 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:48,355 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:48,355 - numba.core.ssa - DEBUG - Fix SSA violator on var n_matches\n", - "2024-09-12 10:50:48,356 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:48,356 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,357 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:48,358 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:48,359 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:48,359 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:48,360 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:48,360 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:48,361 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:48,361 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:48,362 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:48,362 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,363 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:48,363 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:48,364 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,366 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:48,366 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:48,367 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:48,367 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:48,368 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:48,369 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:48,369 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:48,370 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,370 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:48,371 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,371 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:48,372 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:48,373 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,374 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,374 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:48,375 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,376 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:48,376 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:48,377 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,378 - numba.core.ssa - DEBUG - first assign: n_matches\n", - "2024-09-12 10:50:48,378 - numba.core.ssa - DEBUG - replaced with: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,379 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:48,380 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:48,380 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,381 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,382 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:48,382 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,383 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:48,384 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:48,384 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,385 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,385 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,386 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,387 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:48,387 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:48,388 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:48,388 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,389 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:48,389 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:48,390 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,391 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:48,392 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:48,392 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,393 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:48,394 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,394 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,395 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:48,396 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:48,397 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:48,397 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,398 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:48,398 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:48,399 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:48,400 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,400 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:48,401 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,401 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:48,402 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:48,402 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:48,404 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:48,404 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,405 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:48,406 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:48,406 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,407 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:48,407 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:48,408 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,408 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,409 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:48,410 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:48,411 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,411 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:48,412 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,412 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,413 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:48,414 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,415 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,415 - numba.core.ssa - DEBUG - on stmt: n_matches = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,416 - numba.core.ssa - DEBUG - replaced with: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,416 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:48,417 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,417 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:48,418 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:48,419 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,419 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:48,420 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:48,420 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,421 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:48,422 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:48,422 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,423 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:48,423 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,424 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,425 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:48,425 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,426 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,426 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:48,427 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:48,427 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:48,429 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,429 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:48,430 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:48,430 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,431 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:48,432 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:48,432 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,433 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,434 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,434 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:48,435 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:48,435 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:48,436 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,436 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:48,437 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:48,437 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,438 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:48,439 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:48,439 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:48,440 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:48,440 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:48,441 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:48,441 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:48,442 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,442 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:48,443 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:48,445 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:48,445 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:48,445 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:48,446 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,447 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,447 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:48,448 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:48,448 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,449 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:48,449 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:48,450 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:48,450 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,451 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:48,451 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,452 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:48,452 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,453 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:48,455 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:48,455 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:48,456 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:48,456 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 186: []})\n", - "2024-09-12 10:50:48,457 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:48,457 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,458 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:48,459 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:48,459 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:48,460 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:48,460 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:48,461 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:48,462 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:48,462 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:48,463 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:48,464 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,464 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:48,465 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:48,465 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,466 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:48,466 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:48,467 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:48,467 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:48,468 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:48,469 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:48,469 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:48,470 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,471 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:48,471 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,472 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:48,473 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:48,473 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,474 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,474 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:48,475 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,475 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:48,476 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:48,477 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,478 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:48,478 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:48,479 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,479 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,480 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:48,481 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,481 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:48,482 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:48,483 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,483 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,484 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,484 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,485 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:48,485 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:48,486 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:48,486 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,487 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:48,487 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:48,489 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,489 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:48,490 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:48,490 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,491 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:48,492 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,492 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,493 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:48,494 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:48,494 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:48,495 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,495 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:48,496 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:48,496 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:48,497 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,497 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:48,498 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,499 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:48,499 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:48,500 - numba.core.ssa - DEBUG - find_def var='n_matches' stmt=$178binary_add.39 = n_matches + n_pairs\n", - "2024-09-12 10:50:48,500 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:48,501 - numba.core.ssa - DEBUG - insert phi node n_matches.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:48,502 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:48,503 - numba.core.ssa - DEBUG - incoming_def n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,503 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:48,504 - numba.core.ssa - DEBUG - incoming_def n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,504 - numba.core.ssa - DEBUG - replaced with: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:48,505 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:48,506 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:48,506 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,507 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:48,508 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:48,508 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,509 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:48,509 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:48,510 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,511 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,511 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:48,512 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:48,512 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,513 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:48,513 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,514 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,515 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:48,516 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,516 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,517 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,517 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:48,518 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,518 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:48,519 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:48,520 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,520 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:48,521 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:48,521 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,522 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:48,522 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:48,523 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,524 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:48,525 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,525 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,526 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:48,526 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,527 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,528 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:48,528 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:48,529 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:48,529 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,530 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:48,530 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:48,531 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,531 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:48,532 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:48,532 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,534 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,534 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,535 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:48,535 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:48,535 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:48,536 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,536 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:48,538 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:48,538 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,539 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:48,539 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:48,540 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:48,540 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:48,541 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:48,542 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:48,542 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:48,543 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,544 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:48,544 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:48,545 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:48,545 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:48,546 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:48,547 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,547 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,548 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:48,548 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:48,549 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,549 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:48,550 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:48,550 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:48,551 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,551 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:48,551 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,552 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:48,554 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,554 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:48,555 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:48,555 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:48,556 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:48,556 - numba.core.ssa - DEBUG - Fix SSA violator on var i\n", - "2024-09-12 10:50:48,557 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:48,557 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,558 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:48,558 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:48,560 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:48,560 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:48,561 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:48,561 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:48,561 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:48,562 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:48,562 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:48,564 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,564 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:48,565 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:48,565 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,566 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:48,566 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:48,567 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:48,568 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:48,568 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:48,569 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:48,569 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:48,570 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,570 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:48,571 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,572 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:48,572 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:48,573 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,573 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,574 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:48,575 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,576 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:48,576 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:48,577 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,577 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:48,578 - numba.core.ssa - DEBUG - first assign: i\n", - "2024-09-12 10:50:48,579 - numba.core.ssa - DEBUG - replaced with: i = const(int, 0)\n", - "2024-09-12 10:50:48,579 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:48,580 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,581 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,581 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:48,582 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,582 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:48,582 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:48,584 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,584 - numba.core.ssa - DEBUG - on stmt: n_matches.2 = phi(incoming_values=[Var(n_matches, indexing.py:459), Var(n_matches.1, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,584 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,585 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,585 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,586 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:48,586 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:48,588 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:48,588 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,589 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:48,589 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:48,590 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,590 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:48,591 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:48,591 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,591 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:48,592 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,593 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,594 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:48,594 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:48,595 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:48,595 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,596 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:48,596 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:48,598 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:48,598 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,599 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:48,599 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,600 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:48,600 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:48,600 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:48,602 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:48,602 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,603 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:48,603 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:48,604 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,605 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:48,605 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:48,605 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,606 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,607 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:48,608 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:48,608 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,609 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:48,610 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,610 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,611 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:48,611 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,612 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,612 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,613 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:48,614 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,614 - numba.core.ssa - DEBUG - on stmt: i = $218inplace_add.16\n", - "2024-09-12 10:50:48,615 - numba.core.ssa - DEBUG - replaced with: i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:48,616 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:48,616 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,617 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:48,617 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:48,618 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,619 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:48,619 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:48,620 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,620 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:48,621 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,622 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,622 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:48,623 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,624 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,624 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:48,625 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:48,625 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:48,626 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,627 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:48,627 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:48,628 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,628 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:48,629 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:48,629 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,630 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,630 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,631 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:48,632 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:48,632 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:48,633 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,634 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:48,634 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:48,635 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,636 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:48,636 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:48,637 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:48,637 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:48,638 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:48,639 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:48,639 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:48,640 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,641 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:48,641 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:48,642 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:48,642 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:48,643 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:48,643 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,644 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,645 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:48,645 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:48,645 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,646 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:48,646 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:48,647 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:48,647 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,648 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:48,649 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,650 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:48,650 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,651 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:48,652 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:48,652 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:48,653 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:48,654 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 186: []})\n", - "2024-09-12 10:50:48,654 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:48,655 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,655 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:48,656 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:48,657 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:48,657 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:48,658 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:48,659 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:48,659 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:48,660 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:48,660 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:48,660 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,661 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:48,661 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:48,662 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,663 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:48,664 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:48,664 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:48,665 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:48,665 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:48,666 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:48,666 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:48,667 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,667 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:48,667 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,668 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:48,668 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:48,669 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,669 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,670 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:48,670 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,673 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:48,673 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:48,674 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,674 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:48,675 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:48,675 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,676 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,677 - numba.core.ssa - DEBUG - find_def var='i' stmt=$92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,677 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:48,678 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,678 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:48,679 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:48,679 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,680 - numba.core.ssa - DEBUG - on stmt: n_matches.2 = phi(incoming_values=[Var(n_matches, indexing.py:459), Var(n_matches.1, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,681 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,681 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,682 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,682 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:48,683 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:48,684 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:48,684 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,685 - numba.core.ssa - DEBUG - find_def var='i' stmt=$114build_tuple.8 = build_tuple(items=[Var(i, indexing.py:461), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,685 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:48,686 - numba.core.ssa - DEBUG - insert phi node i.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:48,687 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:48,687 - numba.core.ssa - DEBUG - incoming_def i = const(int, 0)\n", - "2024-09-12 10:50:48,688 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:48,688 - numba.core.ssa - DEBUG - incoming_def i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:48,689 - numba.core.ssa - DEBUG - replaced with: $114build_tuple.8 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,689 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:48,691 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:48,691 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,692 - numba.core.ssa - DEBUG - find_def var='i' stmt=$124build_tuple.13 = build_tuple(items=[Var(i, indexing.py:461), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,692 - numba.core.ssa - DEBUG - replaced with: $124build_tuple.13 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,693 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:48,694 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:48,694 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,695 - numba.core.ssa - DEBUG - find_def var='i' stmt=$134build_tuple.18 = build_tuple(items=[Var(i, indexing.py:461), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,695 - numba.core.ssa - DEBUG - replaced with: $134build_tuple.18 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,696 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:48,697 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,697 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,698 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:48,699 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:48,699 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:48,700 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,700 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:48,701 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:48,702 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:48,702 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,703 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:48,704 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,704 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:48,705 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:48,705 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:48,706 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:48,707 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,707 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:48,708 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:48,709 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,709 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:48,710 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:48,710 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,711 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,712 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:48,712 - numba.core.ssa - DEBUG - find_def var='i' stmt=$196binary_subscr.5 = getitem(value=coords, index=i, fn=)\n", - "2024-09-12 10:50:48,713 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:48,713 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:48,714 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:48,715 - numba.core.ssa - DEBUG - replaced with: $196binary_subscr.5 = getitem(value=coords, index=i.2, fn=)\n", - "2024-09-12 10:50:48,715 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:48,716 - numba.core.ssa - DEBUG - find_def var='i' stmt=$202binary_subscr.8 = getitem(value=indices, index=i, fn=)\n", - "2024-09-12 10:50:48,716 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:48,717 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:48,718 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:48,718 - numba.core.ssa - DEBUG - replaced with: $202binary_subscr.8 = getitem(value=indices, index=i.2, fn=)\n", - "2024-09-12 10:50:48,719 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,720 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:48,720 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,721 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,721 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:48,722 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,723 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,723 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,724 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:48,724 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,725 - numba.core.ssa - DEBUG - find_def var='i' stmt=$218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,726 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:48,726 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:48,727 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:48,727 - numba.core.ssa - DEBUG - replaced with: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i.2, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,728 - numba.core.ssa - DEBUG - on stmt: i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:48,728 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:48,729 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,730 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:48,730 - numba.core.ssa - DEBUG - find_def var='i' stmt=$230compare_op.21 = i < $228call_function.20\n", - "2024-09-12 10:50:48,731 - numba.core.ssa - DEBUG - replaced with: $230compare_op.21 = i.1 < $228call_function.20\n", - "2024-09-12 10:50:48,731 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:48,732 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,732 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:48,733 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:48,733 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,734 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:48,734 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,736 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,736 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:48,737 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,737 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,738 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:48,739 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:48,739 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:48,740 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,740 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:48,741 - numba.core.ssa - DEBUG - find_def var='i' stmt=$256compare_op.11 = i == $254call_function.10\n", - "2024-09-12 10:50:48,742 - numba.core.ssa - DEBUG - find_def_from_top label 234\n", - "2024-09-12 10:50:48,742 - numba.core.ssa - DEBUG - insert phi node i.3 = phi(incoming_values=[], incoming_blocks=[]) at 234\n", - "2024-09-12 10:50:48,743 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:48,743 - numba.core.ssa - DEBUG - incoming_def i = const(int, 0)\n", - "2024-09-12 10:50:48,744 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:48,745 - numba.core.ssa - DEBUG - incoming_def i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:48,745 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-09-12 10:50:48,746 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-09-12 10:50:48,747 - numba.core.ssa - DEBUG - idom 96 from label 184\n", - "2024-09-12 10:50:48,747 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:48,748 - numba.core.ssa - DEBUG - incoming_def i.2 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,748 - numba.core.ssa - DEBUG - replaced with: $256compare_op.11 = i.3 == $254call_function.10\n", - "2024-09-12 10:50:48,749 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:48,750 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,750 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:48,751 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:48,752 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,752 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,753 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,753 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:48,754 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:48,754 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:48,755 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,756 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:48,756 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:48,757 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,758 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:48,758 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:48,759 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:48,759 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:48,760 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:48,760 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:48,761 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:48,762 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,762 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:48,763 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:48,764 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:48,764 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:48,765 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:48,765 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,766 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,767 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:48,767 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:48,768 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,768 - numba.core.ssa - DEBUG - find_def var='i' stmt=$310build_slice.7 = call $310build_slice.6(i, $const308.5, func=$310build_slice.6, args=(Var(i, indexing.py:461), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,769 - numba.core.ssa - DEBUG - find_def_from_top label 298\n", - "2024-09-12 10:50:48,770 - numba.core.ssa - DEBUG - idom 234 from label 298\n", - "2024-09-12 10:50:48,770 - numba.core.ssa - DEBUG - find_def_from_bottom label 234\n", - "2024-09-12 10:50:48,771 - numba.core.ssa - DEBUG - replaced with: $310build_slice.7 = call $310build_slice.6(i.3, $const308.5, func=$310build_slice.6, args=(Var(i.3, indexing.py:482), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,772 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:48,772 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:48,773 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:48,773 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,774 - numba.core.ssa - DEBUG - find_def var='i' stmt=$320build_slice.13 = call $320build_slice.12(i, $const318.11, func=$320build_slice.12, args=(Var(i, indexing.py:461), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,775 - numba.core.ssa - DEBUG - find_def_from_top label 298\n", - "2024-09-12 10:50:48,775 - numba.core.ssa - DEBUG - idom 234 from label 298\n", - "2024-09-12 10:50:48,776 - numba.core.ssa - DEBUG - find_def_from_bottom label 234\n", - "2024-09-12 10:50:48,776 - numba.core.ssa - DEBUG - replaced with: $320build_slice.13 = call $320build_slice.12(i.3, $const318.11, func=$320build_slice.12, args=(Var(i.3, indexing.py:482), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,777 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:48,778 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,778 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:48,779 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,779 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:48,780 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:48,781 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:48,782 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:48,782 - numba.core.ssa - DEBUG - Fix SSA violator on var stops\n", - "2024-09-12 10:50:48,783 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:48,783 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,784 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:48,784 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:48,785 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:48,786 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:48,786 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:48,787 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:48,787 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:48,788 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:48,789 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:48,789 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,790 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:48,791 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:48,791 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,792 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:48,792 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:48,793 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:48,794 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:48,794 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:48,795 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:48,795 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:48,796 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,796 - numba.core.ssa - DEBUG - first assign: stops\n", - "2024-09-12 10:50:48,797 - numba.core.ssa - DEBUG - replaced with: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,798 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:48,799 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,799 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:48,799 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:48,800 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,800 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,802 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:48,802 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,803 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:48,803 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:48,804 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,804 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:48,804 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:48,805 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,805 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,806 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:48,807 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,808 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:48,808 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:48,809 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,810 - numba.core.ssa - DEBUG - on stmt: i.2 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,810 - numba.core.ssa - DEBUG - on stmt: n_matches.2 = phi(incoming_values=[Var(n_matches, indexing.py:459), Var(n_matches.1, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,811 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,811 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,812 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,812 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:48,813 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:48,813 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:48,815 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,815 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:48,816 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:48,816 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,817 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:48,817 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:48,818 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,818 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:48,819 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,820 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,820 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:48,821 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:48,822 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:48,822 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,823 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:48,824 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:48,824 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:48,825 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,825 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:48,826 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,827 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:48,827 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:48,828 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:48,829 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:48,829 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,830 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:48,830 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:48,831 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,832 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:48,832 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:48,833 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,833 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,834 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i.2, fn=)\n", - "2024-09-12 10:50:48,835 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i.2, fn=)\n", - "2024-09-12 10:50:48,835 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,836 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:48,836 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,837 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,837 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:48,837 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,839 - numba.core.ssa - DEBUG - on stmt: stops = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,839 - numba.core.ssa - DEBUG - replaced with: stops.2 = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,840 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,840 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:48,841 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i.2, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,841 - numba.core.ssa - DEBUG - on stmt: i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:48,842 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:48,842 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,843 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i.1 < $228call_function.20\n", - "2024-09-12 10:50:48,843 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:48,844 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,844 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:48,845 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:48,846 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,847 - numba.core.ssa - DEBUG - on stmt: i.3 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479), Var(i.2, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:48,847 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:48,848 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,849 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,849 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:48,850 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,850 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,851 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:48,852 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:48,852 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:48,853 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,853 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i.3 == $254call_function.10\n", - "2024-09-12 10:50:48,854 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:48,855 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,855 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:48,856 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:48,857 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,857 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,857 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,858 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:48,859 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:48,860 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:48,860 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,860 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:48,861 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:48,861 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,862 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:48,863 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:48,863 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:48,864 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:48,865 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:48,865 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:48,866 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:48,866 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,867 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:48,867 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:48,867 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:48,868 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:48,869 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:48,870 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,870 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,871 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:48,871 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:48,872 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i.3, $const308.5, func=$310build_slice.6, args=(Var(i.3, indexing.py:482), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,872 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:48,873 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:48,873 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:48,874 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i.3, $const318.11, func=$320build_slice.12, args=(Var(i.3, indexing.py:482), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,875 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:48,876 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,876 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:48,877 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,877 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:48,878 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:48,878 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:48,879 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:48,880 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 186: []})\n", - "2024-09-12 10:50:48,880 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:48,881 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,882 - numba.core.ssa - DEBUG - on stmt: coords = arg(0, name=coords)\n", - "2024-09-12 10:50:48,882 - numba.core.ssa - DEBUG - on stmt: indices = arg(1, name=indices)\n", - "2024-09-12 10:50:48,883 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:48,883 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:48,884 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:48,884 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:48,885 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:48,885 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:48,886 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:48,886 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:455)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,887 - numba.core.ssa - DEBUG - on stmt: $22load_method.9 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:48,887 - numba.core.ssa - DEBUG - on stmt: $const24.10 = const(int, 0)\n", - "2024-09-12 10:50:48,888 - numba.core.ssa - DEBUG - on stmt: $26call_method.11 = call $22load_method.9($const24.10, func=$22load_method.9, args=[Var($const24.10, indexing.py:456)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,888 - numba.core.ssa - DEBUG - on stmt: $30load_global.12 = global(numba: )\n", - "2024-09-12 10:50:48,890 - numba.core.ssa - DEBUG - on stmt: $32load_attr.13 = getattr(value=$30load_global.12, attr=typed)\n", - "2024-09-12 10:50:48,891 - numba.core.ssa - DEBUG - on stmt: $34load_attr.14 = getattr(value=$32load_attr.13, attr=List)\n", - "2024-09-12 10:50:48,891 - numba.core.ssa - DEBUG - on stmt: $36load_method.15 = getattr(value=$34load_attr.14, attr=empty_list)\n", - "2024-09-12 10:50:48,892 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(numba: )\n", - "2024-09-12 10:50:48,893 - numba.core.ssa - DEBUG - on stmt: $40load_attr.17 = getattr(value=$38load_global.16, attr=types)\n", - "2024-09-12 10:50:48,893 - numba.core.ssa - DEBUG - on stmt: $42load_attr.18 = getattr(value=$40load_attr.17, attr=intp)\n", - "2024-09-12 10:50:48,894 - numba.core.ssa - DEBUG - on stmt: stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,894 - numba.core.ssa - DEBUG - on stmt: $50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:48,894 - numba.core.ssa - DEBUG - find_def var='stops' stmt=$50load_method.21 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:48,896 - numba.core.ssa - DEBUG - on stmt: $54load_attr.23 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,896 - numba.core.ssa - DEBUG - on stmt: $const56.24 = const(int, 1)\n", - "2024-09-12 10:50:48,897 - numba.core.ssa - DEBUG - on stmt: $58binary_subscr.25 = static_getitem(value=$54load_attr.23, index=1, index_var=$const56.24, fn=)\n", - "2024-09-12 10:50:48,897 - numba.core.ssa - DEBUG - on stmt: $60call_method.26 = call $50load_method.21($58binary_subscr.25, func=$50load_method.21, args=[Var($58binary_subscr.25, indexing.py:458)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,898 - numba.core.ssa - DEBUG - on stmt: $64load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,898 - numba.core.ssa - DEBUG - on stmt: $66load_method.28 = getattr(value=$64load_global.27, attr=intp)\n", - "2024-09-12 10:50:48,899 - numba.core.ssa - DEBUG - on stmt: $70load_attr.30 = getattr(value=coords, attr=shape)\n", - "2024-09-12 10:50:48,900 - numba.core.ssa - DEBUG - on stmt: $const72.31 = const(int, 1)\n", - "2024-09-12 10:50:48,900 - numba.core.ssa - DEBUG - on stmt: $74binary_subscr.32 = static_getitem(value=$70load_attr.30, index=1, index_var=$const72.31, fn=)\n", - "2024-09-12 10:50:48,901 - numba.core.ssa - DEBUG - on stmt: n_matches = call $66load_method.28($74binary_subscr.32, func=$66load_method.28, args=[Var($74binary_subscr.32, indexing.py:459)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,901 - numba.core.ssa - DEBUG - on stmt: i = const(int, 0)\n", - "2024-09-12 10:50:48,902 - numba.core.ssa - DEBUG - on stmt: $86load_global.36 = global(len: )\n", - "2024-09-12 10:50:48,903 - numba.core.ssa - DEBUG - on stmt: $90call_function.38 = call $86load_global.36(indices, func=$86load_global.36, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,903 - numba.core.ssa - DEBUG - on stmt: $92compare_op.39 = i < $90call_function.38\n", - "2024-09-12 10:50:48,904 - numba.core.ssa - DEBUG - on stmt: bool94 = global(bool: )\n", - "2024-09-12 10:50:48,904 - numba.core.ssa - DEBUG - on stmt: $94pred = call bool94($92compare_op.39, func=bool94, args=(Var($92compare_op.39, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,905 - numba.core.ssa - DEBUG - on stmt: branch $94pred, 96, 234\n", - "2024-09-12 10:50:48,906 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:48,906 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,907 - numba.core.ssa - DEBUG - on stmt: i.2 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,908 - numba.core.ssa - DEBUG - on stmt: n_matches.2 = phi(incoming_values=[Var(n_matches, indexing.py:459), Var(n_matches.1, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,908 - numba.core.ssa - DEBUG - on stmt: starts.3 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,909 - numba.core.ssa - DEBUG - on stmt: $96load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,909 - numba.core.ssa - DEBUG - on stmt: n_pairs = call $96load_global.0(starts.3, func=$96load_global.0, args=[Var(starts.3, indexing.py:468)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,910 - numba.core.ssa - DEBUG - on stmt: $104load_global.3 = global(len: )\n", - "2024-09-12 10:50:48,911 - numba.core.ssa - DEBUG - on stmt: $106load_global.4 = global(range: )\n", - "2024-09-12 10:50:48,911 - numba.core.ssa - DEBUG - on stmt: $const112.7 = const(int, 0)\n", - "2024-09-12 10:50:48,912 - numba.core.ssa - DEBUG - on stmt: $114build_tuple.8 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const112.7, indexing.py:469)])\n", - "2024-09-12 10:50:48,912 - numba.core.ssa - DEBUG - on stmt: $116binary_subscr.9 = getitem(value=indices, index=$114build_tuple.8, fn=)\n", - "2024-09-12 10:50:48,913 - numba.core.ssa - DEBUG - on stmt: $const122.12 = const(int, 1)\n", - "2024-09-12 10:50:48,913 - numba.core.ssa - DEBUG - on stmt: $124build_tuple.13 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const122.12, indexing.py:469)])\n", - "2024-09-12 10:50:48,914 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.14 = getitem(value=indices, index=$124build_tuple.13, fn=)\n", - "2024-09-12 10:50:48,915 - numba.core.ssa - DEBUG - on stmt: $const132.17 = const(int, 2)\n", - "2024-09-12 10:50:48,916 - numba.core.ssa - DEBUG - on stmt: $134build_tuple.18 = build_tuple(items=[Var(i.2, indexing.py:468), Var($const132.17, indexing.py:469)])\n", - "2024-09-12 10:50:48,916 - numba.core.ssa - DEBUG - on stmt: $136binary_subscr.19 = getitem(value=indices, index=$134build_tuple.18, fn=)\n", - "2024-09-12 10:50:48,917 - numba.core.ssa - DEBUG - on stmt: $138call_function.20 = call $106load_global.4($116binary_subscr.9, $126binary_subscr.14, $136binary_subscr.19, func=$106load_global.4, args=[Var($116binary_subscr.9, indexing.py:469), Var($126binary_subscr.14, indexing.py:469), Var($136binary_subscr.19, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,917 - numba.core.ssa - DEBUG - on stmt: $140call_function.21 = call $104load_global.3($138call_function.20, func=$104load_global.3, args=[Var($138call_function.20, indexing.py:469)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,918 - numba.core.ssa - DEBUG - on stmt: $144binary_multiply.23 = $140call_function.21 * n_pairs\n", - "2024-09-12 10:50:48,919 - numba.core.ssa - DEBUG - on stmt: $const146.24 = const(int, 2)\n", - "2024-09-12 10:50:48,919 - numba.core.ssa - DEBUG - on stmt: n_current_slices = $144binary_multiply.23 + $const146.24\n", - "2024-09-12 10:50:48,920 - numba.core.ssa - DEBUG - on stmt: $154load_global.27 = global(np: )\n", - "2024-09-12 10:50:48,921 - numba.core.ssa - DEBUG - on stmt: $156load_method.28 = getattr(value=$154load_global.27, attr=log)\n", - "2024-09-12 10:50:48,921 - numba.core.ssa - DEBUG - on stmt: $160load_global.30 = global(max: )\n", - "2024-09-12 10:50:48,922 - numba.core.ssa - DEBUG - on stmt: $const164.32 = const(int, 1)\n", - "2024-09-12 10:50:48,922 - numba.core.ssa - DEBUG - on stmt: $166call_function.33 = call $160load_global.30(n_pairs, $const164.32, func=$160load_global.30, args=[Var(n_pairs, indexing.py:468), Var($const164.32, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,923 - numba.core.ssa - DEBUG - on stmt: $168binary_true_divide.34 = n_current_slices / $166call_function.33\n", - "2024-09-12 10:50:48,923 - numba.core.ssa - DEBUG - on stmt: $170call_method.35 = call $156load_method.28($168binary_true_divide.34, func=$156load_method.28, args=[Var($168binary_true_divide.34, indexing.py:470)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,924 - numba.core.ssa - DEBUG - on stmt: $172binary_multiply.36 = n_current_slices * $170call_method.35\n", - "2024-09-12 10:50:48,925 - numba.core.ssa - DEBUG - on stmt: $178binary_add.39 = n_matches.2 + n_pairs\n", - "2024-09-12 10:50:48,926 - numba.core.ssa - DEBUG - on stmt: $180compare_op.40 = $172binary_multiply.36 > $178binary_add.39\n", - "2024-09-12 10:50:48,926 - numba.core.ssa - DEBUG - on stmt: bool182 = global(bool: )\n", - "2024-09-12 10:50:48,927 - numba.core.ssa - DEBUG - on stmt: $182pred = call bool182($180compare_op.40, func=bool182, args=(Var($180compare_op.40, indexing.py:470),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,927 - numba.core.ssa - DEBUG - on stmt: branch $182pred, 184, 186\n", - "2024-09-12 10:50:48,928 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 184\n", - "2024-09-12 10:50:48,928 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,929 - numba.core.ssa - DEBUG - on stmt: jump 234\n", - "2024-09-12 10:50:48,930 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 186\n", - "2024-09-12 10:50:48,930 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,931 - numba.core.ssa - DEBUG - on stmt: $186load_global.0 = global(_get_mask_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,931 - numba.core.ssa - DEBUG - on stmt: $196binary_subscr.5 = getitem(value=coords, index=i.2, fn=)\n", - "2024-09-12 10:50:48,932 - numba.core.ssa - DEBUG - on stmt: $202binary_subscr.8 = getitem(value=indices, index=i.2, fn=)\n", - "2024-09-12 10:50:48,933 - numba.core.ssa - DEBUG - on stmt: $204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,933 - numba.core.ssa - DEBUG - find_def var='stops' stmt=$204call_function.9 = call $186load_global.0(starts.3, stops, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops, indexing.py:457), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,934 - numba.core.ssa - DEBUG - find_def_from_top label 186\n", - "2024-09-12 10:50:48,935 - numba.core.ssa - DEBUG - idom 96 from label 186\n", - "2024-09-12 10:50:48,935 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:48,936 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:48,936 - numba.core.ssa - DEBUG - insert phi node stops.3 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:48,937 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:48,938 - numba.core.ssa - DEBUG - incoming_def stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,938 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:48,939 - numba.core.ssa - DEBUG - incoming_def stops.2 = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,940 - numba.core.ssa - DEBUG - replaced with: $204call_function.9 = call $186load_global.0(starts.3, stops.3, $196binary_subscr.5, $202binary_subscr.8, func=$186load_global.0, args=[Var(starts.3, indexing.py:468), Var(stops.3, indexing.py:477), Var($196binary_subscr.5, indexing.py:477), Var($202binary_subscr.8, indexing.py:477)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,940 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.13 = exhaust_iter(value=$204call_function.9, count=3)\n", - "2024-09-12 10:50:48,941 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.10 = static_getitem(value=$206unpack_sequence.13, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,941 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.11 = static_getitem(value=$206unpack_sequence.13, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,941 - numba.core.ssa - DEBUG - on stmt: $206unpack_sequence.12 = static_getitem(value=$206unpack_sequence.13, index=2, index_var=None, fn=)\n", - "2024-09-12 10:50:48,942 - numba.core.ssa - DEBUG - on stmt: starts.2 = $206unpack_sequence.10\n", - "2024-09-12 10:50:48,942 - numba.core.ssa - DEBUG - on stmt: stops.2 = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,943 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $206unpack_sequence.12\n", - "2024-09-12 10:50:48,943 - numba.core.ssa - DEBUG - on stmt: $const216.15 = const(int, 1)\n", - "2024-09-12 10:50:48,944 - numba.core.ssa - DEBUG - on stmt: $218inplace_add.16 = inplace_binop(fn=, immutable_fn=, lhs=i.2, rhs=$const216.15, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:48,944 - numba.core.ssa - DEBUG - on stmt: i.1 = $218inplace_add.16\n", - "2024-09-12 10:50:48,946 - numba.core.ssa - DEBUG - on stmt: $224load_global.18 = global(len: )\n", - "2024-09-12 10:50:48,947 - numba.core.ssa - DEBUG - on stmt: $228call_function.20 = call $224load_global.18(indices, func=$224load_global.18, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,947 - numba.core.ssa - DEBUG - on stmt: $230compare_op.21 = i.1 < $228call_function.20\n", - "2024-09-12 10:50:48,947 - numba.core.ssa - DEBUG - on stmt: bool232 = global(bool: )\n", - "2024-09-12 10:50:48,948 - numba.core.ssa - DEBUG - on stmt: $232pred = call bool232($230compare_op.21, func=bool232, args=(Var($230compare_op.21, indexing.py:462),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,949 - numba.core.ssa - DEBUG - on stmt: branch $232pred, 96, 234\n", - "2024-09-12 10:50:48,950 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:48,950 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,951 - numba.core.ssa - DEBUG - on stmt: i.3 = phi(incoming_values=[Var(i, indexing.py:461), Var(i.1, indexing.py:479), Var(i.2, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:48,951 - numba.core.ssa - DEBUG - on stmt: starts.4 = phi(incoming_values=[Var(starts, indexing.py:455), Var(starts.2, indexing.py:477), Var(starts.3, indexing.py:468)], incoming_blocks=[0, 186, 184])\n", - "2024-09-12 10:50:48,952 - numba.core.ssa - DEBUG - on stmt: $234load_global.0 = global(_join_adjacent_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,953 - numba.core.ssa - DEBUG - on stmt: $240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,954 - numba.core.ssa - DEBUG - find_def var='stops' stmt=$240call_function.3 = call $234load_global.0(starts.4, stops, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,954 - numba.core.ssa - DEBUG - find_def_from_top label 234\n", - "2024-09-12 10:50:48,955 - numba.core.ssa - DEBUG - insert phi node stops.4 = phi(incoming_values=[], incoming_blocks=[]) at 234\n", - "2024-09-12 10:50:48,955 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:48,956 - numba.core.ssa - DEBUG - incoming_def stops = call $36load_method.15($42load_attr.18, func=$36load_method.15, args=[Var($42load_attr.18, indexing.py:457)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,957 - numba.core.ssa - DEBUG - find_def_from_bottom label 186\n", - "2024-09-12 10:50:48,957 - numba.core.ssa - DEBUG - incoming_def stops.2 = $206unpack_sequence.11\n", - "2024-09-12 10:50:48,958 - numba.core.ssa - DEBUG - find_def_from_bottom label 184\n", - "2024-09-12 10:50:48,958 - numba.core.ssa - DEBUG - find_def_from_top label 184\n", - "2024-09-12 10:50:48,959 - numba.core.ssa - DEBUG - idom 96 from label 184\n", - "2024-09-12 10:50:48,959 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:48,960 - numba.core.ssa - DEBUG - incoming_def stops.3 = phi(incoming_values=[Var(stops, indexing.py:457), Var(stops.2, indexing.py:477)], incoming_blocks=[0, 186])\n", - "2024-09-12 10:50:48,960 - numba.core.ssa - DEBUG - replaced with: $240call_function.3 = call $234load_global.0(starts.4, stops.4, func=$234load_global.0, args=[Var(starts.4, indexing.py:482), Var(stops.4, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,961 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.6 = exhaust_iter(value=$240call_function.3, count=2)\n", - "2024-09-12 10:50:48,962 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.4 = static_getitem(value=$242unpack_sequence.6, index=0, index_var=None, fn=)\n", - "2024-09-12 10:50:48,962 - numba.core.ssa - DEBUG - on stmt: $242unpack_sequence.5 = static_getitem(value=$242unpack_sequence.6, index=1, index_var=None, fn=)\n", - "2024-09-12 10:50:48,963 - numba.core.ssa - DEBUG - on stmt: starts.1 = $242unpack_sequence.4\n", - "2024-09-12 10:50:48,963 - numba.core.ssa - DEBUG - on stmt: stops.1 = $242unpack_sequence.5\n", - "2024-09-12 10:50:48,964 - numba.core.ssa - DEBUG - on stmt: $250load_global.8 = global(len: )\n", - "2024-09-12 10:50:48,964 - numba.core.ssa - DEBUG - on stmt: $254call_function.10 = call $250load_global.8(indices, func=$250load_global.8, args=[Var(indices, indexing.py:398)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,965 - numba.core.ssa - DEBUG - on stmt: $256compare_op.11 = i.3 == $254call_function.10\n", - "2024-09-12 10:50:48,965 - numba.core.ssa - DEBUG - on stmt: bool258 = global(bool: )\n", - "2024-09-12 10:50:48,966 - numba.core.ssa - DEBUG - on stmt: $258pred = call bool258($256compare_op.11, func=bool258, args=(Var($256compare_op.11, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,966 - numba.core.ssa - DEBUG - on stmt: branch $258pred, 260, 298\n", - "2024-09-12 10:50:48,967 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 260\n", - "2024-09-12 10:50:48,967 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,969 - numba.core.ssa - DEBUG - on stmt: $260load_global.0 = global(len: )\n", - "2024-09-12 10:50:48,969 - numba.core.ssa - DEBUG - on stmt: $264call_function.2 = call $260load_global.0(starts.1, func=$260load_global.0, args=[Var(starts.1, indexing.py:482)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,970 - numba.core.ssa - DEBUG - on stmt: $const266.3 = const(int, 1)\n", - "2024-09-12 10:50:48,970 - numba.core.ssa - DEBUG - on stmt: $268compare_op.4 = $264call_function.2 == $const266.3\n", - "2024-09-12 10:50:48,971 - numba.core.ssa - DEBUG - on stmt: bool270 = global(bool: )\n", - "2024-09-12 10:50:48,971 - numba.core.ssa - DEBUG - on stmt: $270pred = call bool270($268compare_op.4, func=bool270, args=(Var($268compare_op.4, indexing.py:485),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,972 - numba.core.ssa - DEBUG - on stmt: branch $270pred, 272, 298\n", - "2024-09-12 10:50:48,973 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 272\n", - "2024-09-12 10:50:48,974 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,974 - numba.core.ssa - DEBUG - on stmt: $272load_global.0 = global(np: )\n", - "2024-09-12 10:50:48,975 - numba.core.ssa - DEBUG - on stmt: $274load_method.1 = getattr(value=$272load_global.0, attr=array)\n", - "2024-09-12 10:50:48,975 - numba.core.ssa - DEBUG - on stmt: $const278.3 = const(int, 0)\n", - "2024-09-12 10:50:48,976 - numba.core.ssa - DEBUG - on stmt: $280binary_subscr.4 = static_getitem(value=starts.1, index=0, index_var=$const278.3, fn=)\n", - "2024-09-12 10:50:48,977 - numba.core.ssa - DEBUG - on stmt: $const284.6 = const(int, 0)\n", - "2024-09-12 10:50:48,977 - numba.core.ssa - DEBUG - on stmt: $286binary_subscr.7 = static_getitem(value=stops.1, index=0, index_var=$const284.6, fn=)\n", - "2024-09-12 10:50:48,978 - numba.core.ssa - DEBUG - on stmt: $288build_list.8 = build_list(items=[Var($280binary_subscr.4, indexing.py:486), Var($286binary_subscr.7, indexing.py:486)])\n", - "2024-09-12 10:50:48,978 - numba.core.ssa - DEBUG - on stmt: $290call_method.9 = call $274load_method.1($288build_list.8, func=$274load_method.1, args=[Var($288build_list.8, indexing.py:486)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,979 - numba.core.ssa - DEBUG - on stmt: $const292.10 = const(bool, True)\n", - "2024-09-12 10:50:48,979 - numba.core.ssa - DEBUG - on stmt: $294build_tuple.11 = build_tuple(items=[Var($290call_method.9, indexing.py:486), Var($const292.10, indexing.py:486)])\n", - "2024-09-12 10:50:48,979 - numba.core.ssa - DEBUG - on stmt: $296return_value.12 = cast(value=$294build_tuple.11)\n", - "2024-09-12 10:50:48,980 - numba.core.ssa - DEBUG - on stmt: return $296return_value.12\n", - "2024-09-12 10:50:48,980 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 298\n", - "2024-09-12 10:50:48,981 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:48,981 - numba.core.ssa - DEBUG - on stmt: $298load_global.0 = global(_filter_pairs: CPUDispatcher())\n", - "2024-09-12 10:50:48,983 - numba.core.ssa - DEBUG - on stmt: $const308.5 = const(NoneType, None)\n", - "2024-09-12 10:50:48,984 - numba.core.ssa - DEBUG - on stmt: $310build_slice.6 = global(slice: )\n", - "2024-09-12 10:50:48,984 - numba.core.ssa - DEBUG - on stmt: $310build_slice.7 = call $310build_slice.6(i.3, $const308.5, func=$310build_slice.6, args=(Var(i.3, indexing.py:482), Var($const308.5, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,985 - numba.core.ssa - DEBUG - on stmt: $312binary_subscr.8 = getitem(value=coords, index=$310build_slice.7, fn=)\n", - "2024-09-12 10:50:48,985 - numba.core.ssa - DEBUG - on stmt: $const318.11 = const(NoneType, None)\n", - "2024-09-12 10:50:48,985 - numba.core.ssa - DEBUG - on stmt: $320build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:48,986 - numba.core.ssa - DEBUG - on stmt: $320build_slice.13 = call $320build_slice.12(i.3, $const318.11, func=$320build_slice.12, args=(Var(i.3, indexing.py:482), Var($const318.11, indexing.py:490)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,986 - numba.core.ssa - DEBUG - on stmt: $322binary_subscr.14 = getitem(value=indices, index=$320build_slice.13, fn=)\n", - "2024-09-12 10:50:48,987 - numba.core.ssa - DEBUG - on stmt: mask = call $298load_global.0(starts.1, stops.1, $312binary_subscr.8, $322binary_subscr.14, func=$298load_global.0, args=[Var(starts.1, indexing.py:482), Var(stops.1, indexing.py:482), Var($312binary_subscr.8, indexing.py:490), Var($322binary_subscr.14, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,987 - numba.core.ssa - DEBUG - on stmt: $328load_global.16 = global(array_from_list_intp: CPUDispatcher())\n", - "2024-09-12 10:50:48,989 - numba.core.ssa - DEBUG - on stmt: $332call_function.18 = call $328load_global.16(mask, func=$328load_global.16, args=[Var(mask, indexing.py:490)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:48,989 - numba.core.ssa - DEBUG - on stmt: $const334.19 = const(bool, False)\n", - "2024-09-12 10:50:48,990 - numba.core.ssa - DEBUG - on stmt: $336build_tuple.20 = build_tuple(items=[Var($332call_function.18, indexing.py:491), Var($const334.19, indexing.py:491)])\n", - "2024-09-12 10:50:48,990 - numba.core.ssa - DEBUG - on stmt: $338return_value.21 = cast(value=$336build_tuple.20)\n", - "2024-09-12 10:50:48,991 - numba.core.ssa - DEBUG - on stmt: return $338return_value.21\n", - "2024-09-12 10:50:49,041 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=494)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=534)\n", - " 4\tLOAD_ATTR(arg=1, lineno=534)\n", - " 6\tLOAD_ATTR(arg=2, lineno=534)\n", - " 8\tLOAD_METHOD(arg=3, lineno=534)\n", - " 10\tLOAD_GLOBAL(arg=0, lineno=534)\n", - " 12\tLOAD_ATTR(arg=4, lineno=534)\n", - " 14\tLOAD_ATTR(arg=5, lineno=534)\n", - " 16\tCALL_METHOD(arg=1, lineno=534)\n", - " 18\tSTORE_FAST(arg=4, lineno=534)\n", - " 20\tLOAD_GLOBAL(arg=0, lineno=535)\n", - " 22\tLOAD_ATTR(arg=1, lineno=535)\n", - " 24\tLOAD_ATTR(arg=2, lineno=535)\n", - " 26\tLOAD_METHOD(arg=3, lineno=535)\n", - " 28\tLOAD_GLOBAL(arg=0, lineno=535)\n", - " 30\tLOAD_ATTR(arg=4, lineno=535)\n", - " 32\tLOAD_ATTR(arg=5, lineno=535)\n", - " 34\tCALL_METHOD(arg=1, lineno=535)\n", - " 36\tSTORE_FAST(arg=5, lineno=535)\n", - " 38\tLOAD_GLOBAL(arg=6, lineno=536)\n", - " 40\tLOAD_METHOD(arg=5, lineno=536)\n", - " 42\tLOAD_CONST(arg=1, lineno=536)\n", - " 44\tCALL_METHOD(arg=1, lineno=536)\n", - " 46\tSTORE_FAST(arg=6, lineno=536)\n", - " 48\tLOAD_GLOBAL(arg=7, lineno=538)\n", - " 50\tLOAD_GLOBAL(arg=8, lineno=538)\n", - " 52\tLOAD_FAST(arg=0, lineno=538)\n", - " 54\tCALL_FUNCTION(arg=1, lineno=538)\n", - " 56\tCALL_FUNCTION(arg=1, lineno=538)\n", - " 58\tGET_ITER(arg=None, lineno=538)\n", - "> 60\tFOR_ITER(arg=77, lineno=538)\n", - " 62\tSTORE_FAST(arg=7, lineno=538)\n", - " 64\tLOAD_GLOBAL(arg=7, lineno=541)\n", - " 66\tLOAD_FAST(arg=3, lineno=541)\n", - " 68\tLOAD_CONST(arg=1, lineno=541)\n", - " 70\tBINARY_SUBSCR(arg=None, lineno=541)\n", - " 72\tLOAD_FAST(arg=3, lineno=541)\n", - " 74\tLOAD_CONST(arg=2, lineno=541)\n", - " 76\tBINARY_SUBSCR(arg=None, lineno=541)\n", - " 78\tLOAD_FAST(arg=3, lineno=541)\n", - " 80\tLOAD_CONST(arg=3, lineno=541)\n", - " 82\tBINARY_SUBSCR(arg=None, lineno=541)\n", - " 84\tCALL_FUNCTION(arg=3, lineno=541)\n", - " 86\tGET_ITER(arg=None, lineno=541)\n", - "> 88\tFOR_ITER(arg=62, lineno=541)\n", - " 90\tSTORE_FAST(arg=8, lineno=541)\n", - " 92\tLOAD_GLOBAL(arg=6, lineno=542)\n", - " 94\tLOAD_ATTR(arg=9, lineno=542)\n", - " 96\tLOAD_FAST(arg=2, lineno=542)\n", - " 98\tLOAD_FAST(arg=0, lineno=542)\n", - " 100\tLOAD_FAST(arg=7, lineno=542)\n", - " 102\tBINARY_SUBSCR(arg=None, lineno=542)\n", - " 104\tLOAD_FAST(arg=1, lineno=542)\n", - " 106\tLOAD_FAST(arg=7, lineno=542)\n", - " 108\tBINARY_SUBSCR(arg=None, lineno=542)\n", - " 110\tBUILD_SLICE(arg=2, lineno=542)\n", - " 112\tBINARY_SUBSCR(arg=None, lineno=542)\n", - " 114\tLOAD_FAST(arg=8, lineno=542)\n", - " 116\tLOAD_CONST(arg=4, lineno=542)\n", - " 118\tLOAD_CONST(arg=5, lineno=542)\n", - " 120\tCALL_FUNCTION_KW(arg=3, lineno=542)\n", - " 122\tLOAD_FAST(arg=0, lineno=542)\n", - " 124\tLOAD_FAST(arg=7, lineno=542)\n", - " 126\tBINARY_SUBSCR(arg=None, lineno=542)\n", - " 128\tBINARY_ADD(arg=None, lineno=542)\n", - " 130\tSTORE_FAST(arg=9, lineno=542)\n", - " 132\tLOAD_GLOBAL(arg=6, lineno=543)\n", - " 134\tLOAD_ATTR(arg=9, lineno=543)\n", - " 136\tLOAD_FAST(arg=2, lineno=543)\n", - " 138\tLOAD_FAST(arg=0, lineno=543)\n", - " 140\tLOAD_FAST(arg=7, lineno=543)\n", - " 142\tBINARY_SUBSCR(arg=None, lineno=543)\n", - " 144\tLOAD_FAST(arg=1, lineno=543)\n", - " 146\tLOAD_FAST(arg=7, lineno=543)\n", - " 148\tBINARY_SUBSCR(arg=None, lineno=543)\n", - " 150\tBUILD_SLICE(arg=2, lineno=543)\n", - " 152\tBINARY_SUBSCR(arg=None, lineno=543)\n", - " 154\tLOAD_FAST(arg=8, lineno=543)\n", - " 156\tLOAD_CONST(arg=6, lineno=543)\n", - " 158\tLOAD_CONST(arg=5, lineno=543)\n", - " 160\tCALL_FUNCTION_KW(arg=3, lineno=543)\n", - " 162\tLOAD_FAST(arg=0, lineno=543)\n", - " 164\tLOAD_FAST(arg=7, lineno=543)\n", - " 166\tBINARY_SUBSCR(arg=None, lineno=543)\n", - " 168\tBINARY_ADD(arg=None, lineno=543)\n", - " 170\tSTORE_FAST(arg=10, lineno=543)\n", - " 172\tLOAD_FAST(arg=9, lineno=545)\n", - " 174\tLOAD_FAST(arg=10, lineno=545)\n", - " 176\tCOMPARE_OP(arg=3, lineno=545)\n", - " 178\tPOP_JUMP_IF_FALSE(arg=107, lineno=545)\n", - " 180\tLOAD_FAST(arg=4, lineno=546)\n", - " 182\tLOAD_METHOD(arg=10, lineno=546)\n", - " 184\tLOAD_FAST(arg=9, lineno=546)\n", - " 186\tCALL_METHOD(arg=1, lineno=546)\n", - " 188\tPOP_TOP(arg=None, lineno=546)\n", - " 190\tLOAD_FAST(arg=5, lineno=547)\n", - " 192\tLOAD_METHOD(arg=10, lineno=547)\n", - " 194\tLOAD_FAST(arg=10, lineno=547)\n", - " 196\tCALL_METHOD(arg=1, lineno=547)\n", - " 198\tPOP_TOP(arg=None, lineno=547)\n", - " 200\tLOAD_FAST(arg=6, lineno=548)\n", - " 202\tLOAD_FAST(arg=10, lineno=548)\n", - " 204\tLOAD_FAST(arg=9, lineno=548)\n", - " 206\tBINARY_SUBTRACT(arg=None, lineno=548)\n", - " 208\tINPLACE_ADD(arg=None, lineno=548)\n", - " 210\tSTORE_FAST(arg=6, lineno=548)\n", - "> 212\tJUMP_ABSOLUTE(arg=45, lineno=548)\n", - "> 214\tJUMP_ABSOLUTE(arg=31, lineno=541)\n", - "> 216\tLOAD_FAST(arg=4, lineno=550)\n", - " 218\tLOAD_FAST(arg=5, lineno=550)\n", - " 220\tLOAD_FAST(arg=6, lineno=550)\n", - " 222\tBUILD_TUPLE(arg=3, lineno=550)\n", - " 224\tRETURN_VALUE(arg=None, lineno=550)\n", - "2024-09-12 10:50:49,042 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:49,042 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,043 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:49,044 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=494)\n", - "2024-09-12 10:50:49,044 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,045 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=534)\n", - "2024-09-12 10:50:49,046 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,047 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=534)\n", - "2024-09-12 10:50:49,047 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:49,048 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_ATTR(arg=2, lineno=534)\n", - "2024-09-12 10:50:49,049 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-09-12 10:50:49,049 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=3, lineno=534)\n", - "2024-09-12 10:50:49,050 - numba.core.byteflow - DEBUG - stack ['$6load_attr.2']\n", - "2024-09-12 10:50:49,051 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=0, lineno=534)\n", - "2024-09-12 10:50:49,051 - numba.core.byteflow - DEBUG - stack ['$8load_method.3']\n", - "2024-09-12 10:50:49,052 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=4, lineno=534)\n", - "2024-09-12 10:50:49,053 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$10load_global.4']\n", - "2024-09-12 10:50:49,054 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_ATTR(arg=5, lineno=534)\n", - "2024-09-12 10:50:49,054 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$12load_attr.5']\n", - "2024-09-12 10:50:49,055 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=CALL_METHOD(arg=1, lineno=534)\n", - "2024-09-12 10:50:49,056 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$14load_attr.6']\n", - "2024-09-12 10:50:49,056 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=STORE_FAST(arg=4, lineno=534)\n", - "2024-09-12 10:50:49,057 - numba.core.byteflow - DEBUG - stack ['$16call_method.7']\n", - "2024-09-12 10:50:49,058 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_GLOBAL(arg=0, lineno=535)\n", - "2024-09-12 10:50:49,059 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,059 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_ATTR(arg=1, lineno=535)\n", - "2024-09-12 10:50:49,060 - numba.core.byteflow - DEBUG - stack ['$20load_global.8']\n", - "2024-09-12 10:50:49,061 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_ATTR(arg=2, lineno=535)\n", - "2024-09-12 10:50:49,061 - numba.core.byteflow - DEBUG - stack ['$22load_attr.9']\n", - "2024-09-12 10:50:49,062 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=LOAD_METHOD(arg=3, lineno=535)\n", - "2024-09-12 10:50:49,063 - numba.core.byteflow - DEBUG - stack ['$24load_attr.10']\n", - "2024-09-12 10:50:49,064 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_GLOBAL(arg=0, lineno=535)\n", - "2024-09-12 10:50:49,064 - numba.core.byteflow - DEBUG - stack ['$26load_method.11']\n", - "2024-09-12 10:50:49,065 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_ATTR(arg=4, lineno=535)\n", - "2024-09-12 10:50:49,066 - numba.core.byteflow - DEBUG - stack ['$26load_method.11', '$28load_global.12']\n", - "2024-09-12 10:50:49,066 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_ATTR(arg=5, lineno=535)\n", - "2024-09-12 10:50:49,067 - numba.core.byteflow - DEBUG - stack ['$26load_method.11', '$30load_attr.13']\n", - "2024-09-12 10:50:49,068 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=CALL_METHOD(arg=1, lineno=535)\n", - "2024-09-12 10:50:49,068 - numba.core.byteflow - DEBUG - stack ['$26load_method.11', '$32load_attr.14']\n", - "2024-09-12 10:50:49,069 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=STORE_FAST(arg=5, lineno=535)\n", - "2024-09-12 10:50:49,070 - numba.core.byteflow - DEBUG - stack ['$34call_method.15']\n", - "2024-09-12 10:50:49,070 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_GLOBAL(arg=6, lineno=536)\n", - "2024-09-12 10:50:49,071 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,072 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_METHOD(arg=5, lineno=536)\n", - "2024-09-12 10:50:49,072 - numba.core.byteflow - DEBUG - stack ['$38load_global.16']\n", - "2024-09-12 10:50:49,073 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=LOAD_CONST(arg=1, lineno=536)\n", - "2024-09-12 10:50:49,074 - numba.core.byteflow - DEBUG - stack ['$40load_method.17']\n", - "2024-09-12 10:50:49,075 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=CALL_METHOD(arg=1, lineno=536)\n", - "2024-09-12 10:50:49,075 - numba.core.byteflow - DEBUG - stack ['$40load_method.17', '$const42.18']\n", - "2024-09-12 10:50:49,076 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=STORE_FAST(arg=6, lineno=536)\n", - "2024-09-12 10:50:49,077 - numba.core.byteflow - DEBUG - stack ['$44call_method.19']\n", - "2024-09-12 10:50:49,077 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=LOAD_GLOBAL(arg=7, lineno=538)\n", - "2024-09-12 10:50:49,078 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,079 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=LOAD_GLOBAL(arg=8, lineno=538)\n", - "2024-09-12 10:50:49,079 - numba.core.byteflow - DEBUG - stack ['$48load_global.20']\n", - "2024-09-12 10:50:49,080 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=LOAD_FAST(arg=0, lineno=538)\n", - "2024-09-12 10:50:49,081 - numba.core.byteflow - DEBUG - stack ['$48load_global.20', '$50load_global.21']\n", - "2024-09-12 10:50:49,081 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=CALL_FUNCTION(arg=1, lineno=538)\n", - "2024-09-12 10:50:49,082 - numba.core.byteflow - DEBUG - stack ['$48load_global.20', '$50load_global.21', '$starts_old52.22']\n", - "2024-09-12 10:50:49,083 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=CALL_FUNCTION(arg=1, lineno=538)\n", - "2024-09-12 10:50:49,083 - numba.core.byteflow - DEBUG - stack ['$48load_global.20', '$54call_function.23']\n", - "2024-09-12 10:50:49,084 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=GET_ITER(arg=None, lineno=538)\n", - "2024-09-12 10:50:49,085 - numba.core.byteflow - DEBUG - stack ['$56call_function.24']\n", - "2024-09-12 10:50:49,085 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=60, stack=('$58get_iter.25',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,086 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=1)])\n", - "2024-09-12 10:50:49,087 - numba.core.byteflow - DEBUG - stack: ['$phi60.0']\n", - "2024-09-12 10:50:49,088 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=60 nstack_initial=1)\n", - "2024-09-12 10:50:49,088 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=FOR_ITER(arg=77, lineno=538)\n", - "2024-09-12 10:50:49,089 - numba.core.byteflow - DEBUG - stack ['$phi60.0']\n", - "2024-09-12 10:50:49,090 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=216, stack=(), blockstack=(), npush=0), Edge(pc=62, stack=('$phi60.0', '$60for_iter.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,090 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=216 nstack_initial=0), State(pc_initial=62 nstack_initial=2)])\n", - "2024-09-12 10:50:49,091 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,092 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=216 nstack_initial=0)\n", - "2024-09-12 10:50:49,093 - numba.core.byteflow - DEBUG - dispatch pc=216, inst=LOAD_FAST(arg=4, lineno=550)\n", - "2024-09-12 10:50:49,093 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,094 - numba.core.byteflow - DEBUG - dispatch pc=218, inst=LOAD_FAST(arg=5, lineno=550)\n", - "2024-09-12 10:50:49,095 - numba.core.byteflow - DEBUG - stack ['$starts216.0']\n", - "2024-09-12 10:50:49,095 - numba.core.byteflow - DEBUG - dispatch pc=220, inst=LOAD_FAST(arg=6, lineno=550)\n", - "2024-09-12 10:50:49,096 - numba.core.byteflow - DEBUG - stack ['$starts216.0', '$stops218.1']\n", - "2024-09-12 10:50:49,097 - numba.core.byteflow - DEBUG - dispatch pc=222, inst=BUILD_TUPLE(arg=3, lineno=550)\n", - "2024-09-12 10:50:49,097 - numba.core.byteflow - DEBUG - stack ['$starts216.0', '$stops218.1', '$n_matches220.2']\n", - "2024-09-12 10:50:49,098 - numba.core.byteflow - DEBUG - dispatch pc=224, inst=RETURN_VALUE(arg=None, lineno=550)\n", - "2024-09-12 10:50:49,099 - numba.core.byteflow - DEBUG - stack ['$222build_tuple.3']\n", - "2024-09-12 10:50:49,099 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:49,100 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=62 nstack_initial=2)])\n", - "2024-09-12 10:50:49,101 - numba.core.byteflow - DEBUG - stack: ['$phi62.0', '$phi62.1']\n", - "2024-09-12 10:50:49,101 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=62 nstack_initial=2)\n", - "2024-09-12 10:50:49,102 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=STORE_FAST(arg=7, lineno=538)\n", - "2024-09-12 10:50:49,102 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$phi62.1']\n", - "2024-09-12 10:50:49,103 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_GLOBAL(arg=7, lineno=541)\n", - "2024-09-12 10:50:49,104 - numba.core.byteflow - DEBUG - stack ['$phi62.0']\n", - "2024-09-12 10:50:49,105 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_FAST(arg=3, lineno=541)\n", - "2024-09-12 10:50:49,105 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2']\n", - "2024-09-12 10:50:49,106 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_CONST(arg=1, lineno=541)\n", - "2024-09-12 10:50:49,107 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$idx66.3']\n", - "2024-09-12 10:50:49,107 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=BINARY_SUBSCR(arg=None, lineno=541)\n", - "2024-09-12 10:50:49,108 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$idx66.3', '$const68.4']\n", - "2024-09-12 10:50:49,109 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=LOAD_FAST(arg=3, lineno=541)\n", - "2024-09-12 10:50:49,109 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5']\n", - "2024-09-12 10:50:49,110 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=2, lineno=541)\n", - "2024-09-12 10:50:49,111 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$idx72.6']\n", - "2024-09-12 10:50:49,111 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=BINARY_SUBSCR(arg=None, lineno=541)\n", - "2024-09-12 10:50:49,112 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$idx72.6', '$const74.7']\n", - "2024-09-12 10:50:49,113 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=3, lineno=541)\n", - "2024-09-12 10:50:49,113 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8']\n", - "2024-09-12 10:50:49,114 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_CONST(arg=3, lineno=541)\n", - "2024-09-12 10:50:49,115 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8', '$idx78.9']\n", - "2024-09-12 10:50:49,115 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=BINARY_SUBSCR(arg=None, lineno=541)\n", - "2024-09-12 10:50:49,116 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8', '$idx78.9', '$const80.10']\n", - "2024-09-12 10:50:49,117 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=CALL_FUNCTION(arg=3, lineno=541)\n", - "2024-09-12 10:50:49,117 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8', '$82binary_subscr.11']\n", - "2024-09-12 10:50:49,118 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=GET_ITER(arg=None, lineno=541)\n", - "2024-09-12 10:50:49,119 - numba.core.byteflow - DEBUG - stack ['$phi62.0', '$84call_function.12']\n", - "2024-09-12 10:50:49,119 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=88, stack=('$phi62.0', '$86get_iter.13'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,120 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=88 nstack_initial=2)])\n", - "2024-09-12 10:50:49,121 - numba.core.byteflow - DEBUG - stack: ['$phi88.0', '$phi88.1']\n", - "2024-09-12 10:50:49,121 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=88 nstack_initial=2)\n", - "2024-09-12 10:50:49,122 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=FOR_ITER(arg=62, lineno=541)\n", - "2024-09-12 10:50:49,122 - numba.core.byteflow - DEBUG - stack ['$phi88.0', '$phi88.1']\n", - "2024-09-12 10:50:49,123 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=214, stack=('$phi88.0',), blockstack=(), npush=0), Edge(pc=90, stack=('$phi88.0', '$phi88.1', '$88for_iter.3'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,124 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=214 nstack_initial=1), State(pc_initial=90 nstack_initial=3)])\n", - "2024-09-12 10:50:49,124 - numba.core.byteflow - DEBUG - stack: ['$phi214.0']\n", - "2024-09-12 10:50:49,125 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=214 nstack_initial=1)\n", - "2024-09-12 10:50:49,126 - numba.core.byteflow - DEBUG - dispatch pc=214, inst=JUMP_ABSOLUTE(arg=31, lineno=541)\n", - "2024-09-12 10:50:49,126 - numba.core.byteflow - DEBUG - stack ['$phi214.0']\n", - "2024-09-12 10:50:49,127 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=60, stack=('$phi214.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,128 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=90 nstack_initial=3), State(pc_initial=60 nstack_initial=1)])\n", - "2024-09-12 10:50:49,128 - numba.core.byteflow - DEBUG - stack: ['$phi90.0', '$phi90.1', '$phi90.2']\n", - "2024-09-12 10:50:49,129 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=90 nstack_initial=3)\n", - "2024-09-12 10:50:49,130 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=STORE_FAST(arg=8, lineno=541)\n", - "2024-09-12 10:50:49,130 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$phi90.2']\n", - "2024-09-12 10:50:49,131 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=LOAD_GLOBAL(arg=6, lineno=542)\n", - "2024-09-12 10:50:49,132 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1']\n", - "2024-09-12 10:50:49,132 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_ATTR(arg=9, lineno=542)\n", - "2024-09-12 10:50:49,133 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$92load_global.3']\n", - "2024-09-12 10:50:49,134 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=LOAD_FAST(arg=2, lineno=542)\n", - "2024-09-12 10:50:49,134 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4']\n", - "2024-09-12 10:50:49,135 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=0, lineno=542)\n", - "2024-09-12 10:50:49,136 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5']\n", - "2024-09-12 10:50:49,136 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=7, lineno=542)\n", - "2024-09-12 10:50:49,137 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$starts_old98.6']\n", - "2024-09-12 10:50:49,138 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=BINARY_SUBSCR(arg=None, lineno=542)\n", - "2024-09-12 10:50:49,138 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$starts_old98.6', '$j100.7']\n", - "2024-09-12 10:50:49,139 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=LOAD_FAST(arg=1, lineno=542)\n", - "2024-09-12 10:50:49,139 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$102binary_subscr.8']\n", - "2024-09-12 10:50:49,140 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_FAST(arg=7, lineno=542)\n", - "2024-09-12 10:50:49,141 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$102binary_subscr.8', '$stops_old104.9']\n", - "2024-09-12 10:50:49,141 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=BINARY_SUBSCR(arg=None, lineno=542)\n", - "2024-09-12 10:50:49,142 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$102binary_subscr.8', '$stops_old104.9', '$j106.10']\n", - "2024-09-12 10:50:49,143 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=BUILD_SLICE(arg=2, lineno=542)\n", - "2024-09-12 10:50:49,143 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$102binary_subscr.8', '$108binary_subscr.11']\n", - "2024-09-12 10:50:49,144 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=BINARY_SUBSCR(arg=None, lineno=542)\n", - "2024-09-12 10:50:49,145 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$c96.5', '$110build_slice.13']\n", - "2024-09-12 10:50:49,145 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=LOAD_FAST(arg=8, lineno=542)\n", - "2024-09-12 10:50:49,146 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$112binary_subscr.14']\n", - "2024-09-12 10:50:49,146 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=LOAD_CONST(arg=4, lineno=542)\n", - "2024-09-12 10:50:49,147 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$112binary_subscr.14', '$p_match114.15']\n", - "2024-09-12 10:50:49,148 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_CONST(arg=5, lineno=542)\n", - "2024-09-12 10:50:49,148 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$112binary_subscr.14', '$p_match114.15', '$const116.16']\n", - "2024-09-12 10:50:49,149 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=CALL_FUNCTION_KW(arg=3, lineno=542)\n", - "2024-09-12 10:50:49,150 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$94load_attr.4', '$112binary_subscr.14', '$p_match114.15', '$const116.16', '$const118.17']\n", - "2024-09-12 10:50:49,150 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_FAST(arg=0, lineno=542)\n", - "2024-09-12 10:50:49,151 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$120call_function_kw.18']\n", - "2024-09-12 10:50:49,151 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=LOAD_FAST(arg=7, lineno=542)\n", - "2024-09-12 10:50:49,152 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$120call_function_kw.18', '$starts_old122.19']\n", - "2024-09-12 10:50:49,153 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=BINARY_SUBSCR(arg=None, lineno=542)\n", - "2024-09-12 10:50:49,153 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$120call_function_kw.18', '$starts_old122.19', '$j124.20']\n", - "2024-09-12 10:50:49,154 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=BINARY_ADD(arg=None, lineno=542)\n", - "2024-09-12 10:50:49,155 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$120call_function_kw.18', '$126binary_subscr.21']\n", - "2024-09-12 10:50:49,155 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=STORE_FAST(arg=9, lineno=542)\n", - "2024-09-12 10:50:49,156 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$128binary_add.22']\n", - "2024-09-12 10:50:49,157 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_GLOBAL(arg=6, lineno=543)\n", - "2024-09-12 10:50:49,157 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1']\n", - "2024-09-12 10:50:49,158 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_ATTR(arg=9, lineno=543)\n", - "2024-09-12 10:50:49,158 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$132load_global.23']\n", - "2024-09-12 10:50:49,159 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=LOAD_FAST(arg=2, lineno=543)\n", - "2024-09-12 10:50:49,160 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24']\n", - "2024-09-12 10:50:49,160 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=LOAD_FAST(arg=0, lineno=543)\n", - "2024-09-12 10:50:49,161 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25']\n", - "2024-09-12 10:50:49,161 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=LOAD_FAST(arg=7, lineno=543)\n", - "2024-09-12 10:50:49,162 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$starts_old138.26']\n", - "2024-09-12 10:50:49,163 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=BINARY_SUBSCR(arg=None, lineno=543)\n", - "2024-09-12 10:50:49,164 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$starts_old138.26', '$j140.27']\n", - "2024-09-12 10:50:49,164 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=LOAD_FAST(arg=1, lineno=543)\n", - "2024-09-12 10:50:49,165 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$142binary_subscr.28']\n", - "2024-09-12 10:50:49,165 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_FAST(arg=7, lineno=543)\n", - "2024-09-12 10:50:49,166 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$142binary_subscr.28', '$stops_old144.29']\n", - "2024-09-12 10:50:49,167 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=BINARY_SUBSCR(arg=None, lineno=543)\n", - "2024-09-12 10:50:49,167 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$142binary_subscr.28', '$stops_old144.29', '$j146.30']\n", - "2024-09-12 10:50:49,168 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=BUILD_SLICE(arg=2, lineno=543)\n", - "2024-09-12 10:50:49,168 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$142binary_subscr.28', '$148binary_subscr.31']\n", - "2024-09-12 10:50:49,169 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=BINARY_SUBSCR(arg=None, lineno=543)\n", - "2024-09-12 10:50:49,170 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$c136.25', '$150build_slice.33']\n", - "2024-09-12 10:50:49,171 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_FAST(arg=8, lineno=543)\n", - "2024-09-12 10:50:49,171 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$152binary_subscr.34']\n", - "2024-09-12 10:50:49,172 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=LOAD_CONST(arg=6, lineno=543)\n", - "2024-09-12 10:50:49,172 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$152binary_subscr.34', '$p_match154.35']\n", - "2024-09-12 10:50:49,173 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=LOAD_CONST(arg=5, lineno=543)\n", - "2024-09-12 10:50:49,174 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$152binary_subscr.34', '$p_match154.35', '$const156.36']\n", - "2024-09-12 10:50:49,174 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=CALL_FUNCTION_KW(arg=3, lineno=543)\n", - "2024-09-12 10:50:49,175 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$134load_attr.24', '$152binary_subscr.34', '$p_match154.35', '$const156.36', '$const158.37']\n", - "2024-09-12 10:50:49,175 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=LOAD_FAST(arg=0, lineno=543)\n", - "2024-09-12 10:50:49,176 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$160call_function_kw.38']\n", - "2024-09-12 10:50:49,177 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=LOAD_FAST(arg=7, lineno=543)\n", - "2024-09-12 10:50:49,177 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$160call_function_kw.38', '$starts_old162.39']\n", - "2024-09-12 10:50:49,178 - numba.core.byteflow - DEBUG - dispatch pc=166, inst=BINARY_SUBSCR(arg=None, lineno=543)\n", - "2024-09-12 10:50:49,178 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$160call_function_kw.38', '$starts_old162.39', '$j164.40']\n", - "2024-09-12 10:50:49,179 - numba.core.byteflow - DEBUG - dispatch pc=168, inst=BINARY_ADD(arg=None, lineno=543)\n", - "2024-09-12 10:50:49,179 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$160call_function_kw.38', '$166binary_subscr.41']\n", - "2024-09-12 10:50:49,180 - numba.core.byteflow - DEBUG - dispatch pc=170, inst=STORE_FAST(arg=10, lineno=543)\n", - "2024-09-12 10:50:49,181 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$168binary_add.42']\n", - "2024-09-12 10:50:49,181 - numba.core.byteflow - DEBUG - dispatch pc=172, inst=LOAD_FAST(arg=9, lineno=545)\n", - "2024-09-12 10:50:49,182 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1']\n", - "2024-09-12 10:50:49,182 - numba.core.byteflow - DEBUG - dispatch pc=174, inst=LOAD_FAST(arg=10, lineno=545)\n", - "2024-09-12 10:50:49,183 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$start172.43']\n", - "2024-09-12 10:50:49,184 - numba.core.byteflow - DEBUG - dispatch pc=176, inst=COMPARE_OP(arg=3, lineno=545)\n", - "2024-09-12 10:50:49,184 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$start172.43', '$stop174.44']\n", - "2024-09-12 10:50:49,185 - numba.core.byteflow - DEBUG - dispatch pc=178, inst=POP_JUMP_IF_FALSE(arg=107, lineno=545)\n", - "2024-09-12 10:50:49,186 - numba.core.byteflow - DEBUG - stack ['$phi90.0', '$phi90.1', '$176compare_op.45']\n", - "2024-09-12 10:50:49,186 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=180, stack=('$phi90.0', '$phi90.1'), blockstack=(), npush=0), Edge(pc=212, stack=('$phi90.0', '$phi90.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,187 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=1), State(pc_initial=180 nstack_initial=2), State(pc_initial=212 nstack_initial=2)])\n", - "2024-09-12 10:50:49,188 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=180 nstack_initial=2), State(pc_initial=212 nstack_initial=2)])\n", - "2024-09-12 10:50:49,188 - numba.core.byteflow - DEBUG - stack: ['$phi180.0', '$phi180.1']\n", - "2024-09-12 10:50:49,189 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=180 nstack_initial=2)\n", - "2024-09-12 10:50:49,189 - numba.core.byteflow - DEBUG - dispatch pc=180, inst=LOAD_FAST(arg=4, lineno=546)\n", - "2024-09-12 10:50:49,190 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1']\n", - "2024-09-12 10:50:49,191 - numba.core.byteflow - DEBUG - dispatch pc=182, inst=LOAD_METHOD(arg=10, lineno=546)\n", - "2024-09-12 10:50:49,191 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$starts180.2']\n", - "2024-09-12 10:50:49,192 - numba.core.byteflow - DEBUG - dispatch pc=184, inst=LOAD_FAST(arg=9, lineno=546)\n", - "2024-09-12 10:50:49,192 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$182load_method.3']\n", - "2024-09-12 10:50:49,193 - numba.core.byteflow - DEBUG - dispatch pc=186, inst=CALL_METHOD(arg=1, lineno=546)\n", - "2024-09-12 10:50:49,194 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$182load_method.3', '$start184.4']\n", - "2024-09-12 10:50:49,194 - numba.core.byteflow - DEBUG - dispatch pc=188, inst=POP_TOP(arg=None, lineno=546)\n", - "2024-09-12 10:50:49,195 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$186call_method.5']\n", - "2024-09-12 10:50:49,196 - numba.core.byteflow - DEBUG - dispatch pc=190, inst=LOAD_FAST(arg=5, lineno=547)\n", - "2024-09-12 10:50:49,196 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1']\n", - "2024-09-12 10:50:49,197 - numba.core.byteflow - DEBUG - dispatch pc=192, inst=LOAD_METHOD(arg=10, lineno=547)\n", - "2024-09-12 10:50:49,198 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$stops190.6']\n", - "2024-09-12 10:50:49,198 - numba.core.byteflow - DEBUG - dispatch pc=194, inst=LOAD_FAST(arg=10, lineno=547)\n", - "2024-09-12 10:50:49,199 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$192load_method.7']\n", - "2024-09-12 10:50:49,200 - numba.core.byteflow - DEBUG - dispatch pc=196, inst=CALL_METHOD(arg=1, lineno=547)\n", - "2024-09-12 10:50:49,200 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$192load_method.7', '$stop194.8']\n", - "2024-09-12 10:50:49,201 - numba.core.byteflow - DEBUG - dispatch pc=198, inst=POP_TOP(arg=None, lineno=547)\n", - "2024-09-12 10:50:49,202 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$196call_method.9']\n", - "2024-09-12 10:50:49,202 - numba.core.byteflow - DEBUG - dispatch pc=200, inst=LOAD_FAST(arg=6, lineno=548)\n", - "2024-09-12 10:50:49,203 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1']\n", - "2024-09-12 10:50:49,204 - numba.core.byteflow - DEBUG - dispatch pc=202, inst=LOAD_FAST(arg=10, lineno=548)\n", - "2024-09-12 10:50:49,204 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$n_matches200.10']\n", - "2024-09-12 10:50:49,205 - numba.core.byteflow - DEBUG - dispatch pc=204, inst=LOAD_FAST(arg=9, lineno=548)\n", - "2024-09-12 10:50:49,206 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$n_matches200.10', '$stop202.11']\n", - "2024-09-12 10:50:49,206 - numba.core.byteflow - DEBUG - dispatch pc=206, inst=BINARY_SUBTRACT(arg=None, lineno=548)\n", - "2024-09-12 10:50:49,207 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$n_matches200.10', '$stop202.11', '$start204.12']\n", - "2024-09-12 10:50:49,207 - numba.core.byteflow - DEBUG - dispatch pc=208, inst=INPLACE_ADD(arg=None, lineno=548)\n", - "2024-09-12 10:50:49,208 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$n_matches200.10', '$206binary_subtract.13']\n", - "2024-09-12 10:50:49,209 - numba.core.byteflow - DEBUG - dispatch pc=210, inst=STORE_FAST(arg=6, lineno=548)\n", - "2024-09-12 10:50:49,209 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$208inplace_add.14']\n", - "2024-09-12 10:50:49,210 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=212, stack=('$phi180.0', '$phi180.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,211 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=212 nstack_initial=2), State(pc_initial=212 nstack_initial=2)])\n", - "2024-09-12 10:50:49,211 - numba.core.byteflow - DEBUG - stack: ['$phi212.0', '$phi212.1']\n", - "2024-09-12 10:50:49,212 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=212 nstack_initial=2)\n", - "2024-09-12 10:50:49,213 - numba.core.byteflow - DEBUG - dispatch pc=212, inst=JUMP_ABSOLUTE(arg=45, lineno=548)\n", - "2024-09-12 10:50:49,213 - numba.core.byteflow - DEBUG - stack ['$phi212.0', '$phi212.1']\n", - "2024-09-12 10:50:49,214 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=88, stack=('$phi212.0', '$phi212.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,215 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=212 nstack_initial=2), State(pc_initial=88 nstack_initial=2)])\n", - "2024-09-12 10:50:49,215 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=88 nstack_initial=2)])\n", - "2024-09-12 10:50:49,216 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:49,217 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=60 nstack_initial=1): {'$phi60.0'},\n", - " State(pc_initial=62 nstack_initial=2): {'$phi62.1'},\n", - " State(pc_initial=88 nstack_initial=2): {'$phi88.1'},\n", - " State(pc_initial=90 nstack_initial=3): {'$phi90.2'},\n", - " State(pc_initial=180 nstack_initial=2): set(),\n", - " State(pc_initial=212 nstack_initial=2): set(),\n", - " State(pc_initial=214 nstack_initial=1): set(),\n", - " State(pc_initial=216 nstack_initial=0): set()})\n", - "2024-09-12 10:50:49,257 - numba.core.byteflow - DEBUG - defmap: {'$phi60.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi62.1': State(pc_initial=60 nstack_initial=1),\n", - " '$phi88.1': State(pc_initial=62 nstack_initial=2),\n", - " '$phi90.2': State(pc_initial=88 nstack_initial=2)}\n", - "2024-09-12 10:50:49,258 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi180.0': {('$phi90.0', State(pc_initial=90 nstack_initial=3))},\n", - " '$phi180.1': {('$phi90.1', State(pc_initial=90 nstack_initial=3))},\n", - " '$phi212.0': {('$phi180.0',\n", - " State(pc_initial=180 nstack_initial=2)),\n", - " ('$phi90.0', State(pc_initial=90 nstack_initial=3))},\n", - " '$phi212.1': {('$phi180.1',\n", - " State(pc_initial=180 nstack_initial=2)),\n", - " ('$phi90.1', State(pc_initial=90 nstack_initial=3))},\n", - " '$phi214.0': {('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi60.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi214.0',\n", - " State(pc_initial=214 nstack_initial=1))},\n", - " '$phi62.0': {('$phi60.0', State(pc_initial=60 nstack_initial=1))},\n", - " '$phi62.1': {('$60for_iter.2',\n", - " State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.0': {('$phi212.0', State(pc_initial=212 nstack_initial=2)),\n", - " ('$phi62.0', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi88.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2)),\n", - " ('$phi212.1',\n", - " State(pc_initial=212 nstack_initial=2))},\n", - " '$phi90.0': {('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi90.1': {('$phi88.1', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3',\n", - " State(pc_initial=88 nstack_initial=2))}})\n", - "2024-09-12 10:50:49,260 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi180.0': {('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi180.1': {('$phi88.1', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi212.0': {('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi212.1': {('$phi88.1', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi214.0': {('$phi212.0',\n", - " State(pc_initial=212 nstack_initial=2)),\n", - " ('$phi62.0', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi60.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi212.0', State(pc_initial=212 nstack_initial=2)),\n", - " ('$phi62.0', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi62.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi212.0', State(pc_initial=212 nstack_initial=2)),\n", - " ('$phi62.0', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi62.1': {('$60for_iter.2',\n", - " State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi88.0', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi88.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2)),\n", - " ('$phi88.1', State(pc_initial=88 nstack_initial=2))},\n", - " '$phi90.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi90.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3',\n", - " State(pc_initial=88 nstack_initial=2))}})\n", - "2024-09-12 10:50:49,261 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi180.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi180.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi212.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi212.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi214.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi60.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.1': {('$60for_iter.2',\n", - " State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi88.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi90.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3',\n", - " State(pc_initial=88 nstack_initial=2))}})\n", - "2024-09-12 10:50:49,263 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi180.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi180.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi212.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi212.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi214.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi60.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.1': {('$60for_iter.2',\n", - " State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi88.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.0': {('$58get_iter.25',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi90.1': {('$86get_iter.13',\n", - " State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3',\n", - " State(pc_initial=88 nstack_initial=2))}})\n", - "2024-09-12 10:50:49,264 - numba.core.byteflow - DEBUG - keep phismap: {'$phi60.0': {('$58get_iter.25', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi62.1': {('$60for_iter.2', State(pc_initial=60 nstack_initial=1))},\n", - " '$phi88.1': {('$86get_iter.13', State(pc_initial=62 nstack_initial=2))},\n", - " '$phi90.2': {('$88for_iter.3', State(pc_initial=88 nstack_initial=2))}}\n", - "2024-09-12 10:50:49,265 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi60.0': '$58get_iter.25'},\n", - " State(pc_initial=60 nstack_initial=1): {'$phi62.1': '$60for_iter.2'},\n", - " State(pc_initial=62 nstack_initial=2): {'$phi88.1': '$86get_iter.13'},\n", - " State(pc_initial=88 nstack_initial=2): {'$phi90.2': '$88for_iter.3'}})\n", - "2024-09-12 10:50:49,266 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:49,266 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'item': '$4load_attr.1', 'res': '$6load_attr.2'}), (8, {'item': '$6load_attr.2', 'res': '$8load_method.3'}), (10, {'res': '$10load_global.4'}), (12, {'item': '$10load_global.4', 'res': '$12load_attr.5'}), (14, {'item': '$12load_attr.5', 'res': '$14load_attr.6'}), (16, {'func': '$8load_method.3', 'args': ['$14load_attr.6'], 'res': '$16call_method.7'}), (18, {'value': '$16call_method.7'}), (20, {'res': '$20load_global.8'}), (22, {'item': '$20load_global.8', 'res': '$22load_attr.9'}), (24, {'item': '$22load_attr.9', 'res': '$24load_attr.10'}), (26, {'item': '$24load_attr.10', 'res': '$26load_method.11'}), (28, {'res': '$28load_global.12'}), (30, {'item': '$28load_global.12', 'res': '$30load_attr.13'}), (32, {'item': '$30load_attr.13', 'res': '$32load_attr.14'}), (34, {'func': '$26load_method.11', 'args': ['$32load_attr.14'], 'res': '$34call_method.15'}), (36, {'value': '$34call_method.15'}), (38, {'res': '$38load_global.16'}), (40, {'item': '$38load_global.16', 'res': '$40load_method.17'}), (42, {'res': '$const42.18'}), (44, {'func': '$40load_method.17', 'args': ['$const42.18'], 'res': '$44call_method.19'}), (46, {'value': '$44call_method.19'}), (48, {'res': '$48load_global.20'}), (50, {'res': '$50load_global.21'}), (52, {'res': '$starts_old52.22'}), (54, {'func': '$50load_global.21', 'args': ['$starts_old52.22'], 'res': '$54call_function.23'}), (56, {'func': '$48load_global.20', 'args': ['$54call_function.23'], 'res': '$56call_function.24'}), (58, {'value': '$56call_function.24', 'res': '$58get_iter.25'})), outgoing_phis={'$phi60.0': '$58get_iter.25'}, blockstack=(), active_try_block=None, outgoing_edgepushed={60: ('$58get_iter.25',)})\n", - "2024-09-12 10:50:49,267 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=60 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((60, {'iterator': '$phi60.0', 'pair': '$60for_iter.1', 'indval': '$60for_iter.2', 'pred': '$60for_iter.3'}),), outgoing_phis={'$phi62.1': '$60for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={216: (), 62: ('$phi60.0', '$60for_iter.2')})\n", - "2024-09-12 10:50:49,268 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=62 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((62, {'value': '$phi62.1'}), (64, {'res': '$64load_global.2'}), (66, {'res': '$idx66.3'}), (68, {'res': '$const68.4'}), (70, {'index': '$const68.4', 'target': '$idx66.3', 'res': '$70binary_subscr.5'}), (72, {'res': '$idx72.6'}), (74, {'res': '$const74.7'}), (76, {'index': '$const74.7', 'target': '$idx72.6', 'res': '$76binary_subscr.8'}), (78, {'res': '$idx78.9'}), (80, {'res': '$const80.10'}), (82, {'index': '$const80.10', 'target': '$idx78.9', 'res': '$82binary_subscr.11'}), (84, {'func': '$64load_global.2', 'args': ['$70binary_subscr.5', '$76binary_subscr.8', '$82binary_subscr.11'], 'res': '$84call_function.12'}), (86, {'value': '$84call_function.12', 'res': '$86get_iter.13'})), outgoing_phis={'$phi88.1': '$86get_iter.13'}, blockstack=(), active_try_block=None, outgoing_edgepushed={88: ('$phi62.0', '$86get_iter.13')})\n", - "2024-09-12 10:50:49,269 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=88 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((88, {'iterator': '$phi88.1', 'pair': '$88for_iter.2', 'indval': '$88for_iter.3', 'pred': '$88for_iter.4'}),), outgoing_phis={'$phi90.2': '$88for_iter.3'}, blockstack=(), active_try_block=None, outgoing_edgepushed={214: ('$phi88.0',), 90: ('$phi88.0', '$phi88.1', '$88for_iter.3')})\n", - "2024-09-12 10:50:49,270 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=90 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((90, {'value': '$phi90.2'}), (92, {'res': '$92load_global.3'}), (94, {'item': '$92load_global.3', 'res': '$94load_attr.4'}), (96, {'res': '$c96.5'}), (98, {'res': '$starts_old98.6'}), (100, {'res': '$j100.7'}), (102, {'index': '$j100.7', 'target': '$starts_old98.6', 'res': '$102binary_subscr.8'}), (104, {'res': '$stops_old104.9'}), (106, {'res': '$j106.10'}), (108, {'index': '$j106.10', 'target': '$stops_old104.9', 'res': '$108binary_subscr.11'}), (110, {'start': '$102binary_subscr.8', 'stop': '$108binary_subscr.11', 'step': None, 'res': '$110build_slice.13', 'slicevar': '$110build_slice.12'}), (112, {'index': '$110build_slice.13', 'target': '$c96.5', 'res': '$112binary_subscr.14'}), (114, {'res': '$p_match114.15'}), (116, {'res': '$const116.16'}), (118, {'res': '$const118.17'}), (120, {'func': '$94load_attr.4', 'args': ['$112binary_subscr.14', '$p_match114.15', '$const116.16'], 'names': '$const118.17', 'res': '$120call_function_kw.18'}), (122, {'res': '$starts_old122.19'}), (124, {'res': '$j124.20'}), (126, {'index': '$j124.20', 'target': '$starts_old122.19', 'res': '$126binary_subscr.21'}), (128, {'lhs': '$120call_function_kw.18', 'rhs': '$126binary_subscr.21', 'res': '$128binary_add.22'}), (130, {'value': '$128binary_add.22'}), (132, {'res': '$132load_global.23'}), (134, {'item': '$132load_global.23', 'res': '$134load_attr.24'}), (136, {'res': '$c136.25'}), (138, {'res': '$starts_old138.26'}), (140, {'res': '$j140.27'}), (142, {'index': '$j140.27', 'target': '$starts_old138.26', 'res': '$142binary_subscr.28'}), (144, {'res': '$stops_old144.29'}), (146, {'res': '$j146.30'}), (148, {'index': '$j146.30', 'target': '$stops_old144.29', 'res': '$148binary_subscr.31'}), (150, {'start': '$142binary_subscr.28', 'stop': '$148binary_subscr.31', 'step': None, 'res': '$150build_slice.33', 'slicevar': '$150build_slice.32'}), (152, {'index': '$150build_slice.33', 'target': '$c136.25', 'res': '$152binary_subscr.34'}), (154, {'res': '$p_match154.35'}), (156, {'res': '$const156.36'}), (158, {'res': '$const158.37'}), (160, {'func': '$134load_attr.24', 'args': ['$152binary_subscr.34', '$p_match154.35', '$const156.36'], 'names': '$const158.37', 'res': '$160call_function_kw.38'}), (162, {'res': '$starts_old162.39'}), (164, {'res': '$j164.40'}), (166, {'index': '$j164.40', 'target': '$starts_old162.39', 'res': '$166binary_subscr.41'}), (168, {'lhs': '$160call_function_kw.38', 'rhs': '$166binary_subscr.41', 'res': '$168binary_add.42'}), (170, {'value': '$168binary_add.42'}), (172, {'res': '$start172.43'}), (174, {'res': '$stop174.44'}), (176, {'lhs': '$start172.43', 'rhs': '$stop174.44', 'res': '$176compare_op.45'}), (178, {'pred': '$176compare_op.45'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={180: ('$phi90.0', '$phi90.1'), 212: ('$phi90.0', '$phi90.1')})\n", - "2024-09-12 10:50:49,270 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=180 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((180, {'res': '$starts180.2'}), (182, {'item': '$starts180.2', 'res': '$182load_method.3'}), (184, {'res': '$start184.4'}), (186, {'func': '$182load_method.3', 'args': ['$start184.4'], 'res': '$186call_method.5'}), (190, {'res': '$stops190.6'}), (192, {'item': '$stops190.6', 'res': '$192load_method.7'}), (194, {'res': '$stop194.8'}), (196, {'func': '$192load_method.7', 'args': ['$stop194.8'], 'res': '$196call_method.9'}), (200, {'res': '$n_matches200.10'}), (202, {'res': '$stop202.11'}), (204, {'res': '$start204.12'}), (206, {'lhs': '$stop202.11', 'rhs': '$start204.12', 'res': '$206binary_subtract.13'}), (208, {'lhs': '$n_matches200.10', 'rhs': '$206binary_subtract.13', 'res': '$208inplace_add.14'}), (210, {'value': '$208inplace_add.14'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={212: ('$phi180.0', '$phi180.1')})\n", - "2024-09-12 10:50:49,271 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=212 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((212, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={88: ('$phi212.0', '$phi212.1')})\n", - "2024-09-12 10:50:49,272 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=214 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((214, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={60: ('$phi214.0',)})\n", - "2024-09-12 10:50:49,272 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=216 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((216, {'res': '$starts216.0'}), (218, {'res': '$stops218.1'}), (220, {'res': '$n_matches220.2'}), (222, {'items': ['$starts216.0', '$stops218.1', '$n_matches220.2'], 'res': '$222build_tuple.3'}), (224, {'retval': '$222build_tuple.3', 'castval': '$224return_value.4'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:49,280 - numba.core.interpreter - DEBUG - label 0:\n", - " starts_old = arg(0, name=starts_old) ['starts_old']\n", - " stops_old = arg(1, name=stops_old) ['stops_old']\n", - " c = arg(2, name=c) ['c']\n", - " idx = arg(3, name=idx) ['idx']\n", - " $2load_global.0 = global(numba: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=typed) ['$2load_global.0', '$4load_attr.1']\n", - " $6load_attr.2 = getattr(value=$4load_attr.1, attr=List) ['$4load_attr.1', '$6load_attr.2']\n", - " $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list) ['$6load_attr.2', '$8load_method.3']\n", - " $10load_global.4 = global(numba: ) ['$10load_global.4']\n", - " $12load_attr.5 = getattr(value=$10load_global.4, attr=types) ['$10load_global.4', '$12load_attr.5']\n", - " $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp) ['$12load_attr.5', '$14load_attr.6']\n", - " starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:534)], kws=(), vararg=None, varkwarg=None, target=None) ['$14load_attr.6', '$8load_method.3', 'starts']\n", - " $20load_global.8 = global(numba: ) ['$20load_global.8']\n", - " $22load_attr.9 = getattr(value=$20load_global.8, attr=typed) ['$20load_global.8', '$22load_attr.9']\n", - " $24load_attr.10 = getattr(value=$22load_attr.9, attr=List) ['$22load_attr.9', '$24load_attr.10']\n", - " $26load_method.11 = getattr(value=$24load_attr.10, attr=empty_list) ['$24load_attr.10', '$26load_method.11']\n", - " $28load_global.12 = global(numba: ) ['$28load_global.12']\n", - " $30load_attr.13 = getattr(value=$28load_global.12, attr=types) ['$28load_global.12', '$30load_attr.13']\n", - " $32load_attr.14 = getattr(value=$30load_attr.13, attr=intp) ['$30load_attr.13', '$32load_attr.14']\n", - " stops = call $26load_method.11($32load_attr.14, func=$26load_method.11, args=[Var($32load_attr.14, indexing.py:535)], kws=(), vararg=None, varkwarg=None, target=None) ['$26load_method.11', '$32load_attr.14', 'stops']\n", - " $38load_global.16 = global(np: ) ['$38load_global.16']\n", - " $40load_method.17 = getattr(value=$38load_global.16, attr=intp) ['$38load_global.16', '$40load_method.17']\n", - " $const42.18 = const(int, 0) ['$const42.18']\n", - " n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None) ['$40load_method.17', '$const42.18', 'n_matches']\n", - " $48load_global.20 = global(range: ) ['$48load_global.20']\n", - " $50load_global.21 = global(len: ) ['$50load_global.21']\n", - " $54call_function.23 = call $50load_global.21(starts_old, func=$50load_global.21, args=[Var(starts_old, indexing.py:494)], kws=(), vararg=None, varkwarg=None, target=None) ['$50load_global.21', '$54call_function.23', 'starts_old']\n", - " $56call_function.24 = call $48load_global.20($54call_function.23, func=$48load_global.20, args=[Var($54call_function.23, indexing.py:538)], kws=(), vararg=None, varkwarg=None, target=None) ['$48load_global.20', '$54call_function.23', '$56call_function.24']\n", - " $58get_iter.25 = getiter(value=$56call_function.24) ['$56call_function.24', '$58get_iter.25']\n", - " $phi60.0 = $58get_iter.25 ['$58get_iter.25', '$phi60.0']\n", - " jump 60 []\n", - "label 60:\n", - " $60for_iter.1 = iternext(value=$phi60.0) ['$60for_iter.1', '$phi60.0']\n", - " $60for_iter.2 = pair_first(value=$60for_iter.1) ['$60for_iter.1', '$60for_iter.2']\n", - " $60for_iter.3 = pair_second(value=$60for_iter.1) ['$60for_iter.1', '$60for_iter.3']\n", - " $phi62.1 = $60for_iter.2 ['$60for_iter.2', '$phi62.1']\n", - " branch $60for_iter.3, 62, 216 ['$60for_iter.3']\n", - "label 62:\n", - " j = $phi62.1 ['$phi62.1', 'j']\n", - " $64load_global.2 = global(range: ) ['$64load_global.2']\n", - " $const68.4 = const(int, 0) ['$const68.4']\n", - " $70binary_subscr.5 = getitem(value=idx, index=$const68.4, fn=) ['$70binary_subscr.5', '$const68.4', 'idx']\n", - " $const74.7 = const(int, 1) ['$const74.7']\n", - " $76binary_subscr.8 = getitem(value=idx, index=$const74.7, fn=) ['$76binary_subscr.8', '$const74.7', 'idx']\n", - " $const80.10 = const(int, 2) ['$const80.10']\n", - " $82binary_subscr.11 = getitem(value=idx, index=$const80.10, fn=) ['$82binary_subscr.11', '$const80.10', 'idx']\n", - " $84call_function.12 = call $64load_global.2($70binary_subscr.5, $76binary_subscr.8, $82binary_subscr.11, func=$64load_global.2, args=[Var($70binary_subscr.5, indexing.py:541), Var($76binary_subscr.8, indexing.py:541), Var($82binary_subscr.11, indexing.py:541)], kws=(), vararg=None, varkwarg=None, target=None) ['$64load_global.2', '$70binary_subscr.5', '$76binary_subscr.8', '$82binary_subscr.11', '$84call_function.12']\n", - " $86get_iter.13 = getiter(value=$84call_function.12) ['$84call_function.12', '$86get_iter.13']\n", - " $phi88.1 = $86get_iter.13 ['$86get_iter.13', '$phi88.1']\n", - " jump 88 []\n", - "label 88:\n", - " $88for_iter.2 = iternext(value=$phi88.1) ['$88for_iter.2', '$phi88.1']\n", - " $88for_iter.3 = pair_first(value=$88for_iter.2) ['$88for_iter.2', '$88for_iter.3']\n", - " $88for_iter.4 = pair_second(value=$88for_iter.2) ['$88for_iter.2', '$88for_iter.4']\n", - " $phi90.2 = $88for_iter.3 ['$88for_iter.3', '$phi90.2']\n", - " branch $88for_iter.4, 90, 214 ['$88for_iter.4']\n", - "label 90:\n", - " p_match = $phi90.2 ['$phi90.2', 'p_match']\n", - " $92load_global.3 = global(np: ) ['$92load_global.3']\n", - " $94load_attr.4 = getattr(value=$92load_global.3, attr=searchsorted) ['$92load_global.3', '$94load_attr.4']\n", - " $102binary_subscr.8 = getitem(value=starts_old, index=j, fn=) ['$102binary_subscr.8', 'j', 'starts_old']\n", - " $108binary_subscr.11 = getitem(value=stops_old, index=j, fn=) ['$108binary_subscr.11', 'j', 'stops_old']\n", - " $110build_slice.12 = global(slice: ) ['$110build_slice.12']\n", - " $110build_slice.13 = call $110build_slice.12($102binary_subscr.8, $108binary_subscr.11, func=$110build_slice.12, args=(Var($102binary_subscr.8, indexing.py:542), Var($108binary_subscr.11, indexing.py:542)), kws=(), vararg=None, varkwarg=None, target=None) ['$102binary_subscr.8', '$108binary_subscr.11', '$110build_slice.12', '$110build_slice.13']\n", - " $112binary_subscr.14 = getitem(value=c, index=$110build_slice.13, fn=) ['$110build_slice.13', '$112binary_subscr.14', 'c']\n", - " $const116.16 = const(str, left) ['$const116.16']\n", - " $120call_function_kw.18 = call $94load_attr.4($112binary_subscr.14, p_match, func=$94load_attr.4, args=[Var($112binary_subscr.14, indexing.py:542), Var(p_match, indexing.py:541)], kws=[('side', Var($const116.16, indexing.py:542))], vararg=None, varkwarg=None, target=None) ['$112binary_subscr.14', '$120call_function_kw.18', '$94load_attr.4', '$const116.16', 'p_match']\n", - " $126binary_subscr.21 = getitem(value=starts_old, index=j, fn=) ['$126binary_subscr.21', 'j', 'starts_old']\n", - " start = $120call_function_kw.18 + $126binary_subscr.21 ['$120call_function_kw.18', '$126binary_subscr.21', 'start']\n", - " $132load_global.23 = global(np: ) ['$132load_global.23']\n", - " $134load_attr.24 = getattr(value=$132load_global.23, attr=searchsorted) ['$132load_global.23', '$134load_attr.24']\n", - " $142binary_subscr.28 = getitem(value=starts_old, index=j, fn=) ['$142binary_subscr.28', 'j', 'starts_old']\n", - " $148binary_subscr.31 = getitem(value=stops_old, index=j, fn=) ['$148binary_subscr.31', 'j', 'stops_old']\n", - " $150build_slice.32 = global(slice: ) ['$150build_slice.32']\n", - " $150build_slice.33 = call $150build_slice.32($142binary_subscr.28, $148binary_subscr.31, func=$150build_slice.32, args=(Var($142binary_subscr.28, indexing.py:543), Var($148binary_subscr.31, indexing.py:543)), kws=(), vararg=None, varkwarg=None, target=None) ['$142binary_subscr.28', '$148binary_subscr.31', '$150build_slice.32', '$150build_slice.33']\n", - " $152binary_subscr.34 = getitem(value=c, index=$150build_slice.33, fn=) ['$150build_slice.33', '$152binary_subscr.34', 'c']\n", - " $const156.36 = const(str, right) ['$const156.36']\n", - " $160call_function_kw.38 = call $134load_attr.24($152binary_subscr.34, p_match, func=$134load_attr.24, args=[Var($152binary_subscr.34, indexing.py:543), Var(p_match, indexing.py:541)], kws=[('side', Var($const156.36, indexing.py:543))], vararg=None, varkwarg=None, target=None) ['$134load_attr.24', '$152binary_subscr.34', '$160call_function_kw.38', '$const156.36', 'p_match']\n", - " $166binary_subscr.41 = getitem(value=starts_old, index=j, fn=) ['$166binary_subscr.41', 'j', 'starts_old']\n", - " stop = $160call_function_kw.38 + $166binary_subscr.41 ['$160call_function_kw.38', '$166binary_subscr.41', 'stop']\n", - " $176compare_op.45 = start != stop ['$176compare_op.45', 'start', 'stop']\n", - " bool178 = global(bool: ) ['bool178']\n", - " $178pred = call bool178($176compare_op.45, func=bool178, args=(Var($176compare_op.45, indexing.py:545),), kws=(), vararg=None, varkwarg=None, target=None) ['$176compare_op.45', '$178pred', 'bool178']\n", - " branch $178pred, 180, 212 ['$178pred']\n", - "label 180:\n", - " $182load_method.3 = getattr(value=starts, attr=append) ['$182load_method.3', 'starts']\n", - " $186call_method.5 = call $182load_method.3(start, func=$182load_method.3, args=[Var(start, indexing.py:542)], kws=(), vararg=None, varkwarg=None, target=None) ['$182load_method.3', '$186call_method.5', 'start']\n", - " $192load_method.7 = getattr(value=stops, attr=append) ['$192load_method.7', 'stops']\n", - " $196call_method.9 = call $192load_method.7(stop, func=$192load_method.7, args=[Var(stop, indexing.py:543)], kws=(), vararg=None, varkwarg=None, target=None) ['$192load_method.7', '$196call_method.9', 'stop']\n", - " $206binary_subtract.13 = stop - start ['$206binary_subtract.13', 'start', 'stop']\n", - " $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined) ['$206binary_subtract.13', '$208inplace_add.14', 'n_matches']\n", - " n_matches = $208inplace_add.14 ['$208inplace_add.14', 'n_matches']\n", - " jump 212 []\n", - "label 212:\n", - " jump 88 []\n", - "label 214:\n", - " jump 60 []\n", - "label 216:\n", - " $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)]) ['$222build_tuple.3', 'n_matches', 'starts', 'stops']\n", - " $224return_value.4 = cast(value=$222build_tuple.3) ['$222build_tuple.3', '$224return_value.4']\n", - " return $224return_value.4 ['$224return_value.4']\n", - "\n", - "2024-09-12 10:50:49,322 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:49,324 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,325 - numba.core.ssa - DEBUG - on stmt: starts_old = arg(0, name=starts_old)\n", - "2024-09-12 10:50:49,325 - numba.core.ssa - DEBUG - on stmt: stops_old = arg(1, name=stops_old)\n", - "2024-09-12 10:50:49,326 - numba.core.ssa - DEBUG - on stmt: c = arg(2, name=c)\n", - "2024-09-12 10:50:49,327 - numba.core.ssa - DEBUG - on stmt: idx = arg(3, name=idx)\n", - "2024-09-12 10:50:49,327 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:49,328 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:49,329 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:49,330 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:49,330 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:49,331 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:49,332 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:49,332 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:534)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,333 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(numba: )\n", - "2024-09-12 10:50:49,334 - numba.core.ssa - DEBUG - on stmt: $22load_attr.9 = getattr(value=$20load_global.8, attr=typed)\n", - "2024-09-12 10:50:49,335 - numba.core.ssa - DEBUG - on stmt: $24load_attr.10 = getattr(value=$22load_attr.9, attr=List)\n", - "2024-09-12 10:50:49,335 - numba.core.ssa - DEBUG - on stmt: $26load_method.11 = getattr(value=$24load_attr.10, attr=empty_list)\n", - "2024-09-12 10:50:49,336 - numba.core.ssa - DEBUG - on stmt: $28load_global.12 = global(numba: )\n", - "2024-09-12 10:50:49,337 - numba.core.ssa - DEBUG - on stmt: $30load_attr.13 = getattr(value=$28load_global.12, attr=types)\n", - "2024-09-12 10:50:49,338 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30load_attr.13, attr=intp)\n", - "2024-09-12 10:50:49,338 - numba.core.ssa - DEBUG - on stmt: stops = call $26load_method.11($32load_attr.14, func=$26load_method.11, args=[Var($32load_attr.14, indexing.py:535)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,339 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(np: )\n", - "2024-09-12 10:50:49,340 - numba.core.ssa - DEBUG - on stmt: $40load_method.17 = getattr(value=$38load_global.16, attr=intp)\n", - "2024-09-12 10:50:49,340 - numba.core.ssa - DEBUG - on stmt: $const42.18 = const(int, 0)\n", - "2024-09-12 10:50:49,341 - numba.core.ssa - DEBUG - on stmt: n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,342 - numba.core.ssa - DEBUG - on stmt: $48load_global.20 = global(range: )\n", - "2024-09-12 10:50:49,343 - numba.core.ssa - DEBUG - on stmt: $50load_global.21 = global(len: )\n", - "2024-09-12 10:50:49,343 - numba.core.ssa - DEBUG - on stmt: $54call_function.23 = call $50load_global.21(starts_old, func=$50load_global.21, args=[Var(starts_old, indexing.py:494)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,344 - numba.core.ssa - DEBUG - on stmt: $56call_function.24 = call $48load_global.20($54call_function.23, func=$48load_global.20, args=[Var($54call_function.23, indexing.py:538)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,345 - numba.core.ssa - DEBUG - on stmt: $58get_iter.25 = getiter(value=$56call_function.24)\n", - "2024-09-12 10:50:49,346 - numba.core.ssa - DEBUG - on stmt: $phi60.0 = $58get_iter.25\n", - "2024-09-12 10:50:49,346 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:49,347 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 60\n", - "2024-09-12 10:50:49,348 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,349 - numba.core.ssa - DEBUG - on stmt: $60for_iter.1 = iternext(value=$phi60.0)\n", - "2024-09-12 10:50:49,349 - numba.core.ssa - DEBUG - on stmt: $60for_iter.2 = pair_first(value=$60for_iter.1)\n", - "2024-09-12 10:50:49,350 - numba.core.ssa - DEBUG - on stmt: $60for_iter.3 = pair_second(value=$60for_iter.1)\n", - "2024-09-12 10:50:49,351 - numba.core.ssa - DEBUG - on stmt: $phi62.1 = $60for_iter.2\n", - "2024-09-12 10:50:49,352 - numba.core.ssa - DEBUG - on stmt: branch $60for_iter.3, 62, 216\n", - "2024-09-12 10:50:49,352 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 62\n", - "2024-09-12 10:50:49,353 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,354 - numba.core.ssa - DEBUG - on stmt: j = $phi62.1\n", - "2024-09-12 10:50:49,354 - numba.core.ssa - DEBUG - on stmt: $64load_global.2 = global(range: )\n", - "2024-09-12 10:50:49,355 - numba.core.ssa - DEBUG - on stmt: $const68.4 = const(int, 0)\n", - "2024-09-12 10:50:49,356 - numba.core.ssa - DEBUG - on stmt: $70binary_subscr.5 = static_getitem(value=idx, index=0, index_var=$const68.4, fn=)\n", - "2024-09-12 10:50:49,356 - numba.core.ssa - DEBUG - on stmt: $const74.7 = const(int, 1)\n", - "2024-09-12 10:50:49,357 - numba.core.ssa - DEBUG - on stmt: $76binary_subscr.8 = static_getitem(value=idx, index=1, index_var=$const74.7, fn=)\n", - "2024-09-12 10:50:49,358 - numba.core.ssa - DEBUG - on stmt: $const80.10 = const(int, 2)\n", - "2024-09-12 10:50:49,359 - numba.core.ssa - DEBUG - on stmt: $82binary_subscr.11 = static_getitem(value=idx, index=2, index_var=$const80.10, fn=)\n", - "2024-09-12 10:50:49,359 - numba.core.ssa - DEBUG - on stmt: $84call_function.12 = call $64load_global.2($70binary_subscr.5, $76binary_subscr.8, $82binary_subscr.11, func=$64load_global.2, args=[Var($70binary_subscr.5, indexing.py:541), Var($76binary_subscr.8, indexing.py:541), Var($82binary_subscr.11, indexing.py:541)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,360 - numba.core.ssa - DEBUG - on stmt: $86get_iter.13 = getiter(value=$84call_function.12)\n", - "2024-09-12 10:50:49,361 - numba.core.ssa - DEBUG - on stmt: $phi88.1 = $86get_iter.13\n", - "2024-09-12 10:50:49,362 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:49,362 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 88\n", - "2024-09-12 10:50:49,363 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,364 - numba.core.ssa - DEBUG - on stmt: $88for_iter.2 = iternext(value=$phi88.1)\n", - "2024-09-12 10:50:49,364 - numba.core.ssa - DEBUG - on stmt: $88for_iter.3 = pair_first(value=$88for_iter.2)\n", - "2024-09-12 10:50:49,365 - numba.core.ssa - DEBUG - on stmt: $88for_iter.4 = pair_second(value=$88for_iter.2)\n", - "2024-09-12 10:50:49,366 - numba.core.ssa - DEBUG - on stmt: $phi90.2 = $88for_iter.3\n", - "2024-09-12 10:50:49,367 - numba.core.ssa - DEBUG - on stmt: branch $88for_iter.4, 90, 214\n", - "2024-09-12 10:50:49,367 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 90\n", - "2024-09-12 10:50:49,368 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,369 - numba.core.ssa - DEBUG - on stmt: p_match = $phi90.2\n", - "2024-09-12 10:50:49,369 - numba.core.ssa - DEBUG - on stmt: $92load_global.3 = global(np: )\n", - "2024-09-12 10:50:49,370 - numba.core.ssa - DEBUG - on stmt: $94load_attr.4 = getattr(value=$92load_global.3, attr=searchsorted)\n", - "2024-09-12 10:50:49,371 - numba.core.ssa - DEBUG - on stmt: $102binary_subscr.8 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,372 - numba.core.ssa - DEBUG - on stmt: $108binary_subscr.11 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:49,372 - numba.core.ssa - DEBUG - on stmt: $110build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:49,373 - numba.core.ssa - DEBUG - on stmt: $110build_slice.13 = call $110build_slice.12($102binary_subscr.8, $108binary_subscr.11, func=$110build_slice.12, args=(Var($102binary_subscr.8, indexing.py:542), Var($108binary_subscr.11, indexing.py:542)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,374 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.14 = getitem(value=c, index=$110build_slice.13, fn=)\n", - "2024-09-12 10:50:49,375 - numba.core.ssa - DEBUG - on stmt: $const116.16 = const(str, left)\n", - "2024-09-12 10:50:49,375 - numba.core.ssa - DEBUG - on stmt: $120call_function_kw.18 = call $94load_attr.4($112binary_subscr.14, p_match, func=$94load_attr.4, args=[Var($112binary_subscr.14, indexing.py:542), Var(p_match, indexing.py:541)], kws=[('side', Var($const116.16, indexing.py:542))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,376 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.21 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,377 - numba.core.ssa - DEBUG - on stmt: start = $120call_function_kw.18 + $126binary_subscr.21\n", - "2024-09-12 10:50:49,377 - numba.core.ssa - DEBUG - on stmt: $132load_global.23 = global(np: )\n", - "2024-09-12 10:50:49,378 - numba.core.ssa - DEBUG - on stmt: $134load_attr.24 = getattr(value=$132load_global.23, attr=searchsorted)\n", - "2024-09-12 10:50:49,379 - numba.core.ssa - DEBUG - on stmt: $142binary_subscr.28 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,380 - numba.core.ssa - DEBUG - on stmt: $148binary_subscr.31 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:49,380 - numba.core.ssa - DEBUG - on stmt: $150build_slice.32 = global(slice: )\n", - "2024-09-12 10:50:49,381 - numba.core.ssa - DEBUG - on stmt: $150build_slice.33 = call $150build_slice.32($142binary_subscr.28, $148binary_subscr.31, func=$150build_slice.32, args=(Var($142binary_subscr.28, indexing.py:543), Var($148binary_subscr.31, indexing.py:543)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,382 - numba.core.ssa - DEBUG - on stmt: $152binary_subscr.34 = getitem(value=c, index=$150build_slice.33, fn=)\n", - "2024-09-12 10:50:49,383 - numba.core.ssa - DEBUG - on stmt: $const156.36 = const(str, right)\n", - "2024-09-12 10:50:49,383 - numba.core.ssa - DEBUG - on stmt: $160call_function_kw.38 = call $134load_attr.24($152binary_subscr.34, p_match, func=$134load_attr.24, args=[Var($152binary_subscr.34, indexing.py:543), Var(p_match, indexing.py:541)], kws=[('side', Var($const156.36, indexing.py:543))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,384 - numba.core.ssa - DEBUG - on stmt: $166binary_subscr.41 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,385 - numba.core.ssa - DEBUG - on stmt: stop = $160call_function_kw.38 + $166binary_subscr.41\n", - "2024-09-12 10:50:49,385 - numba.core.ssa - DEBUG - on stmt: $176compare_op.45 = start != stop\n", - "2024-09-12 10:50:49,386 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:49,387 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.45, func=bool178, args=(Var($176compare_op.45, indexing.py:545),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,387 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 212\n", - "2024-09-12 10:50:49,388 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 180\n", - "2024-09-12 10:50:49,389 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,389 - numba.core.ssa - DEBUG - on stmt: $182load_method.3 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:49,390 - numba.core.ssa - DEBUG - on stmt: $186call_method.5 = call $182load_method.3(start, func=$182load_method.3, args=[Var(start, indexing.py:542)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,391 - numba.core.ssa - DEBUG - on stmt: $192load_method.7 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:49,392 - numba.core.ssa - DEBUG - on stmt: $196call_method.9 = call $192load_method.7(stop, func=$192load_method.7, args=[Var(stop, indexing.py:543)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,392 - numba.core.ssa - DEBUG - on stmt: $206binary_subtract.13 = stop - start\n", - "2024-09-12 10:50:49,393 - numba.core.ssa - DEBUG - on stmt: $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:49,394 - numba.core.ssa - DEBUG - on stmt: n_matches = $208inplace_add.14\n", - "2024-09-12 10:50:49,394 - numba.core.ssa - DEBUG - on stmt: jump 212\n", - "2024-09-12 10:50:49,395 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 212\n", - "2024-09-12 10:50:49,396 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,396 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:49,397 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 214\n", - "2024-09-12 10:50:49,398 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,398 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:49,399 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 216\n", - "2024-09-12 10:50:49,400 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,400 - numba.core.ssa - DEBUG - on stmt: $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)])\n", - "2024-09-12 10:50:49,401 - numba.core.ssa - DEBUG - on stmt: $224return_value.4 = cast(value=$222build_tuple.3)\n", - "2024-09-12 10:50:49,402 - numba.core.ssa - DEBUG - on stmt: return $224return_value.4\n", - "2024-09-12 10:50:49,405 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102binary_subscr.8': [],\n", - " '$108binary_subscr.11': [],\n", - " '$10load_global.4': [],\n", - " '$110build_slice.12': [],\n", - " '$110build_slice.13': [],\n", - " '$112binary_subscr.14': [],\n", - " '$120call_function_kw.18': [],\n", - " '$126binary_subscr.21': [],\n", - " '$12load_attr.5': [],\n", - " '$132load_global.23': [],\n", - " '$134load_attr.24': [],\n", - " '$142binary_subscr.28': [],\n", - " '$148binary_subscr.31': [],\n", - " '$14load_attr.6': [],\n", - " '$150build_slice.32': [],\n", - " '$150build_slice.33': [],\n", - " '$152binary_subscr.34': [],\n", - " '$160call_function_kw.38': [],\n", - " '$166binary_subscr.41': [],\n", - " '$176compare_op.45': [],\n", - " '$178pred': [],\n", - " '$182load_method.3': [],\n", - " '$186call_method.5': [],\n", - " '$192load_method.7': [],\n", - " '$196call_method.9': [],\n", - " '$206binary_subtract.13': [],\n", - " '$208inplace_add.14': [],\n", - " '$20load_global.8': [],\n", - " '$222build_tuple.3': [],\n", - " '$224return_value.4': [],\n", - " '$22load_attr.9': [],\n", - " '$24load_attr.10': [],\n", - " '$26load_method.11': [],\n", - " '$28load_global.12': [],\n", - " '$2load_global.0': [],\n", - " '$30load_attr.13': [],\n", - " '$32load_attr.14': [],\n", - " '$38load_global.16': [],\n", - " '$40load_method.17': [],\n", - " '$48load_global.20': [],\n", - " '$4load_attr.1': [],\n", - " '$50load_global.21': [],\n", - " '$54call_function.23': [],\n", - " '$56call_function.24': [],\n", - " '$58get_iter.25': [],\n", - " '$60for_iter.1': [],\n", - " '$60for_iter.2': [],\n", - " '$60for_iter.3': [],\n", - " '$64load_global.2': [],\n", - " '$6load_attr.2': [],\n", - " '$70binary_subscr.5': [],\n", - " '$76binary_subscr.8': [],\n", - " '$82binary_subscr.11': [],\n", - " '$84call_function.12': [],\n", - " '$86get_iter.13': [],\n", - " '$88for_iter.2': [],\n", - " '$88for_iter.3': [],\n", - " '$88for_iter.4': [],\n", - " '$8load_method.3': [],\n", - " '$92load_global.3': [],\n", - " '$94load_attr.4': [],\n", - " '$const116.16': [],\n", - " '$const156.36': [],\n", - " '$const42.18': [],\n", - " '$const68.4': [],\n", - " '$const74.7': [],\n", - " '$const80.10': [],\n", - " '$phi60.0': [],\n", - " '$phi62.1': [],\n", - " '$phi88.1': [],\n", - " '$phi90.2': [],\n", - " 'bool178': [],\n", - " 'c': [],\n", - " 'idx': [],\n", - " 'j': [],\n", - " 'n_matches': [,\n", - " ],\n", - " 'p_match': [],\n", - " 'start': [],\n", - " 'starts': [],\n", - " 'starts_old': [],\n", - " 'stop': [],\n", - " 'stops': [],\n", - " 'stops_old': []})\n", - "2024-09-12 10:50:49,406 - numba.core.ssa - DEBUG - SSA violators {'n_matches'}\n", - "2024-09-12 10:50:49,407 - numba.core.ssa - DEBUG - Fix SSA violator on var n_matches\n", - "2024-09-12 10:50:49,407 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:49,408 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,409 - numba.core.ssa - DEBUG - on stmt: starts_old = arg(0, name=starts_old)\n", - "2024-09-12 10:50:49,409 - numba.core.ssa - DEBUG - on stmt: stops_old = arg(1, name=stops_old)\n", - "2024-09-12 10:50:49,410 - numba.core.ssa - DEBUG - on stmt: c = arg(2, name=c)\n", - "2024-09-12 10:50:49,411 - numba.core.ssa - DEBUG - on stmt: idx = arg(3, name=idx)\n", - "2024-09-12 10:50:49,411 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:49,412 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:49,413 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:49,413 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:49,414 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:49,415 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:49,415 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:49,416 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:534)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,417 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(numba: )\n", - "2024-09-12 10:50:49,417 - numba.core.ssa - DEBUG - on stmt: $22load_attr.9 = getattr(value=$20load_global.8, attr=typed)\n", - "2024-09-12 10:50:49,418 - numba.core.ssa - DEBUG - on stmt: $24load_attr.10 = getattr(value=$22load_attr.9, attr=List)\n", - "2024-09-12 10:50:49,419 - numba.core.ssa - DEBUG - on stmt: $26load_method.11 = getattr(value=$24load_attr.10, attr=empty_list)\n", - "2024-09-12 10:50:49,420 - numba.core.ssa - DEBUG - on stmt: $28load_global.12 = global(numba: )\n", - "2024-09-12 10:50:49,420 - numba.core.ssa - DEBUG - on stmt: $30load_attr.13 = getattr(value=$28load_global.12, attr=types)\n", - "2024-09-12 10:50:49,421 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30load_attr.13, attr=intp)\n", - "2024-09-12 10:50:49,422 - numba.core.ssa - DEBUG - on stmt: stops = call $26load_method.11($32load_attr.14, func=$26load_method.11, args=[Var($32load_attr.14, indexing.py:535)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,423 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(np: )\n", - "2024-09-12 10:50:49,423 - numba.core.ssa - DEBUG - on stmt: $40load_method.17 = getattr(value=$38load_global.16, attr=intp)\n", - "2024-09-12 10:50:49,424 - numba.core.ssa - DEBUG - on stmt: $const42.18 = const(int, 0)\n", - "2024-09-12 10:50:49,425 - numba.core.ssa - DEBUG - on stmt: n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,426 - numba.core.ssa - DEBUG - first assign: n_matches\n", - "2024-09-12 10:50:49,427 - numba.core.ssa - DEBUG - replaced with: n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,427 - numba.core.ssa - DEBUG - on stmt: $48load_global.20 = global(range: )\n", - "2024-09-12 10:50:49,428 - numba.core.ssa - DEBUG - on stmt: $50load_global.21 = global(len: )\n", - "2024-09-12 10:50:49,429 - numba.core.ssa - DEBUG - on stmt: $54call_function.23 = call $50load_global.21(starts_old, func=$50load_global.21, args=[Var(starts_old, indexing.py:494)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,430 - numba.core.ssa - DEBUG - on stmt: $56call_function.24 = call $48load_global.20($54call_function.23, func=$48load_global.20, args=[Var($54call_function.23, indexing.py:538)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,430 - numba.core.ssa - DEBUG - on stmt: $58get_iter.25 = getiter(value=$56call_function.24)\n", - "2024-09-12 10:50:49,431 - numba.core.ssa - DEBUG - on stmt: $phi60.0 = $58get_iter.25\n", - "2024-09-12 10:50:49,432 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:49,433 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:49,433 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,434 - numba.core.ssa - DEBUG - on stmt: $60for_iter.1 = iternext(value=$phi60.0)\n", - "2024-09-12 10:50:49,435 - numba.core.ssa - DEBUG - on stmt: $60for_iter.2 = pair_first(value=$60for_iter.1)\n", - "2024-09-12 10:50:49,436 - numba.core.ssa - DEBUG - on stmt: $60for_iter.3 = pair_second(value=$60for_iter.1)\n", - "2024-09-12 10:50:49,436 - numba.core.ssa - DEBUG - on stmt: $phi62.1 = $60for_iter.2\n", - "2024-09-12 10:50:49,437 - numba.core.ssa - DEBUG - on stmt: branch $60for_iter.3, 62, 216\n", - "2024-09-12 10:50:49,438 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 62\n", - "2024-09-12 10:50:49,439 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,439 - numba.core.ssa - DEBUG - on stmt: j = $phi62.1\n", - "2024-09-12 10:50:49,440 - numba.core.ssa - DEBUG - on stmt: $64load_global.2 = global(range: )\n", - "2024-09-12 10:50:49,441 - numba.core.ssa - DEBUG - on stmt: $const68.4 = const(int, 0)\n", - "2024-09-12 10:50:49,441 - numba.core.ssa - DEBUG - on stmt: $70binary_subscr.5 = static_getitem(value=idx, index=0, index_var=$const68.4, fn=)\n", - "2024-09-12 10:50:49,442 - numba.core.ssa - DEBUG - on stmt: $const74.7 = const(int, 1)\n", - "2024-09-12 10:50:49,443 - numba.core.ssa - DEBUG - on stmt: $76binary_subscr.8 = static_getitem(value=idx, index=1, index_var=$const74.7, fn=)\n", - "2024-09-12 10:50:49,444 - numba.core.ssa - DEBUG - on stmt: $const80.10 = const(int, 2)\n", - "2024-09-12 10:50:49,444 - numba.core.ssa - DEBUG - on stmt: $82binary_subscr.11 = static_getitem(value=idx, index=2, index_var=$const80.10, fn=)\n", - "2024-09-12 10:50:49,445 - numba.core.ssa - DEBUG - on stmt: $84call_function.12 = call $64load_global.2($70binary_subscr.5, $76binary_subscr.8, $82binary_subscr.11, func=$64load_global.2, args=[Var($70binary_subscr.5, indexing.py:541), Var($76binary_subscr.8, indexing.py:541), Var($82binary_subscr.11, indexing.py:541)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,446 - numba.core.ssa - DEBUG - on stmt: $86get_iter.13 = getiter(value=$84call_function.12)\n", - "2024-09-12 10:50:49,447 - numba.core.ssa - DEBUG - on stmt: $phi88.1 = $86get_iter.13\n", - "2024-09-12 10:50:49,447 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:49,448 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 88\n", - "2024-09-12 10:50:49,449 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,449 - numba.core.ssa - DEBUG - on stmt: $88for_iter.2 = iternext(value=$phi88.1)\n", - "2024-09-12 10:50:49,450 - numba.core.ssa - DEBUG - on stmt: $88for_iter.3 = pair_first(value=$88for_iter.2)\n", - "2024-09-12 10:50:49,451 - numba.core.ssa - DEBUG - on stmt: $88for_iter.4 = pair_second(value=$88for_iter.2)\n", - "2024-09-12 10:50:49,452 - numba.core.ssa - DEBUG - on stmt: $phi90.2 = $88for_iter.3\n", - "2024-09-12 10:50:49,452 - numba.core.ssa - DEBUG - on stmt: branch $88for_iter.4, 90, 214\n", - "2024-09-12 10:50:49,453 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 90\n", - "2024-09-12 10:50:49,454 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,455 - numba.core.ssa - DEBUG - on stmt: p_match = $phi90.2\n", - "2024-09-12 10:50:49,455 - numba.core.ssa - DEBUG - on stmt: $92load_global.3 = global(np: )\n", - "2024-09-12 10:50:49,456 - numba.core.ssa - DEBUG - on stmt: $94load_attr.4 = getattr(value=$92load_global.3, attr=searchsorted)\n", - "2024-09-12 10:50:49,457 - numba.core.ssa - DEBUG - on stmt: $102binary_subscr.8 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,457 - numba.core.ssa - DEBUG - on stmt: $108binary_subscr.11 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:49,458 - numba.core.ssa - DEBUG - on stmt: $110build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:49,459 - numba.core.ssa - DEBUG - on stmt: $110build_slice.13 = call $110build_slice.12($102binary_subscr.8, $108binary_subscr.11, func=$110build_slice.12, args=(Var($102binary_subscr.8, indexing.py:542), Var($108binary_subscr.11, indexing.py:542)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,460 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.14 = getitem(value=c, index=$110build_slice.13, fn=)\n", - "2024-09-12 10:50:49,460 - numba.core.ssa - DEBUG - on stmt: $const116.16 = const(str, left)\n", - "2024-09-12 10:50:49,461 - numba.core.ssa - DEBUG - on stmt: $120call_function_kw.18 = call $94load_attr.4($112binary_subscr.14, p_match, func=$94load_attr.4, args=[Var($112binary_subscr.14, indexing.py:542), Var(p_match, indexing.py:541)], kws=[('side', Var($const116.16, indexing.py:542))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,462 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.21 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,462 - numba.core.ssa - DEBUG - on stmt: start = $120call_function_kw.18 + $126binary_subscr.21\n", - "2024-09-12 10:50:49,463 - numba.core.ssa - DEBUG - on stmt: $132load_global.23 = global(np: )\n", - "2024-09-12 10:50:49,464 - numba.core.ssa - DEBUG - on stmt: $134load_attr.24 = getattr(value=$132load_global.23, attr=searchsorted)\n", - "2024-09-12 10:50:49,464 - numba.core.ssa - DEBUG - on stmt: $142binary_subscr.28 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,465 - numba.core.ssa - DEBUG - on stmt: $148binary_subscr.31 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:49,466 - numba.core.ssa - DEBUG - on stmt: $150build_slice.32 = global(slice: )\n", - "2024-09-12 10:50:49,466 - numba.core.ssa - DEBUG - on stmt: $150build_slice.33 = call $150build_slice.32($142binary_subscr.28, $148binary_subscr.31, func=$150build_slice.32, args=(Var($142binary_subscr.28, indexing.py:543), Var($148binary_subscr.31, indexing.py:543)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,467 - numba.core.ssa - DEBUG - on stmt: $152binary_subscr.34 = getitem(value=c, index=$150build_slice.33, fn=)\n", - "2024-09-12 10:50:49,468 - numba.core.ssa - DEBUG - on stmt: $const156.36 = const(str, right)\n", - "2024-09-12 10:50:49,468 - numba.core.ssa - DEBUG - on stmt: $160call_function_kw.38 = call $134load_attr.24($152binary_subscr.34, p_match, func=$134load_attr.24, args=[Var($152binary_subscr.34, indexing.py:543), Var(p_match, indexing.py:541)], kws=[('side', Var($const156.36, indexing.py:543))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,469 - numba.core.ssa - DEBUG - on stmt: $166binary_subscr.41 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,470 - numba.core.ssa - DEBUG - on stmt: stop = $160call_function_kw.38 + $166binary_subscr.41\n", - "2024-09-12 10:50:49,470 - numba.core.ssa - DEBUG - on stmt: $176compare_op.45 = start != stop\n", - "2024-09-12 10:50:49,471 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:49,472 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.45, func=bool178, args=(Var($176compare_op.45, indexing.py:545),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,472 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 212\n", - "2024-09-12 10:50:49,473 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:49,473 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,474 - numba.core.ssa - DEBUG - on stmt: $182load_method.3 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:49,475 - numba.core.ssa - DEBUG - on stmt: $186call_method.5 = call $182load_method.3(start, func=$182load_method.3, args=[Var(start, indexing.py:542)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,476 - numba.core.ssa - DEBUG - on stmt: $192load_method.7 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:49,476 - numba.core.ssa - DEBUG - on stmt: $196call_method.9 = call $192load_method.7(stop, func=$192load_method.7, args=[Var(stop, indexing.py:543)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,477 - numba.core.ssa - DEBUG - on stmt: $206binary_subtract.13 = stop - start\n", - "2024-09-12 10:50:49,478 - numba.core.ssa - DEBUG - on stmt: $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:49,478 - numba.core.ssa - DEBUG - on stmt: n_matches = $208inplace_add.14\n", - "2024-09-12 10:50:49,479 - numba.core.ssa - DEBUG - replaced with: n_matches.1 = $208inplace_add.14\n", - "2024-09-12 10:50:49,480 - numba.core.ssa - DEBUG - on stmt: jump 212\n", - "2024-09-12 10:50:49,480 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 212\n", - "2024-09-12 10:50:49,481 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,482 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:49,483 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 214\n", - "2024-09-12 10:50:49,483 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,484 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:49,485 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:49,485 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,486 - numba.core.ssa - DEBUG - on stmt: $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)])\n", - "2024-09-12 10:50:49,487 - numba.core.ssa - DEBUG - on stmt: $224return_value.4 = cast(value=$222build_tuple.3)\n", - "2024-09-12 10:50:49,487 - numba.core.ssa - DEBUG - on stmt: return $224return_value.4\n", - "2024-09-12 10:50:49,488 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 180: []})\n", - "2024-09-12 10:50:49,489 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:49,490 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,490 - numba.core.ssa - DEBUG - on stmt: starts_old = arg(0, name=starts_old)\n", - "2024-09-12 10:50:49,491 - numba.core.ssa - DEBUG - on stmt: stops_old = arg(1, name=stops_old)\n", - "2024-09-12 10:50:49,492 - numba.core.ssa - DEBUG - on stmt: c = arg(2, name=c)\n", - "2024-09-12 10:50:49,492 - numba.core.ssa - DEBUG - on stmt: idx = arg(3, name=idx)\n", - "2024-09-12 10:50:49,493 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:49,494 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:49,494 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:49,495 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:49,496 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:49,496 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:49,497 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:49,498 - numba.core.ssa - DEBUG - on stmt: starts = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:534)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,498 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(numba: )\n", - "2024-09-12 10:50:49,499 - numba.core.ssa - DEBUG - on stmt: $22load_attr.9 = getattr(value=$20load_global.8, attr=typed)\n", - "2024-09-12 10:50:49,500 - numba.core.ssa - DEBUG - on stmt: $24load_attr.10 = getattr(value=$22load_attr.9, attr=List)\n", - "2024-09-12 10:50:49,500 - numba.core.ssa - DEBUG - on stmt: $26load_method.11 = getattr(value=$24load_attr.10, attr=empty_list)\n", - "2024-09-12 10:50:49,501 - numba.core.ssa - DEBUG - on stmt: $28load_global.12 = global(numba: )\n", - "2024-09-12 10:50:49,502 - numba.core.ssa - DEBUG - on stmt: $30load_attr.13 = getattr(value=$28load_global.12, attr=types)\n", - "2024-09-12 10:50:49,502 - numba.core.ssa - DEBUG - on stmt: $32load_attr.14 = getattr(value=$30load_attr.13, attr=intp)\n", - "2024-09-12 10:50:49,503 - numba.core.ssa - DEBUG - on stmt: stops = call $26load_method.11($32load_attr.14, func=$26load_method.11, args=[Var($32load_attr.14, indexing.py:535)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,504 - numba.core.ssa - DEBUG - on stmt: $38load_global.16 = global(np: )\n", - "2024-09-12 10:50:49,505 - numba.core.ssa - DEBUG - on stmt: $40load_method.17 = getattr(value=$38load_global.16, attr=intp)\n", - "2024-09-12 10:50:49,505 - numba.core.ssa - DEBUG - on stmt: $const42.18 = const(int, 0)\n", - "2024-09-12 10:50:49,506 - numba.core.ssa - DEBUG - on stmt: n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,507 - numba.core.ssa - DEBUG - on stmt: $48load_global.20 = global(range: )\n", - "2024-09-12 10:50:49,507 - numba.core.ssa - DEBUG - on stmt: $50load_global.21 = global(len: )\n", - "2024-09-12 10:50:49,508 - numba.core.ssa - DEBUG - on stmt: $54call_function.23 = call $50load_global.21(starts_old, func=$50load_global.21, args=[Var(starts_old, indexing.py:494)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,509 - numba.core.ssa - DEBUG - on stmt: $56call_function.24 = call $48load_global.20($54call_function.23, func=$48load_global.20, args=[Var($54call_function.23, indexing.py:538)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,509 - numba.core.ssa - DEBUG - on stmt: $58get_iter.25 = getiter(value=$56call_function.24)\n", - "2024-09-12 10:50:49,510 - numba.core.ssa - DEBUG - on stmt: $phi60.0 = $58get_iter.25\n", - "2024-09-12 10:50:49,511 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:49,511 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:49,512 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,513 - numba.core.ssa - DEBUG - on stmt: $60for_iter.1 = iternext(value=$phi60.0)\n", - "2024-09-12 10:50:49,513 - numba.core.ssa - DEBUG - on stmt: $60for_iter.2 = pair_first(value=$60for_iter.1)\n", - "2024-09-12 10:50:49,514 - numba.core.ssa - DEBUG - on stmt: $60for_iter.3 = pair_second(value=$60for_iter.1)\n", - "2024-09-12 10:50:49,515 - numba.core.ssa - DEBUG - on stmt: $phi62.1 = $60for_iter.2\n", - "2024-09-12 10:50:49,515 - numba.core.ssa - DEBUG - on stmt: branch $60for_iter.3, 62, 216\n", - "2024-09-12 10:50:49,516 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 62\n", - "2024-09-12 10:50:49,517 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,517 - numba.core.ssa - DEBUG - on stmt: j = $phi62.1\n", - "2024-09-12 10:50:49,518 - numba.core.ssa - DEBUG - on stmt: $64load_global.2 = global(range: )\n", - "2024-09-12 10:50:49,519 - numba.core.ssa - DEBUG - on stmt: $const68.4 = const(int, 0)\n", - "2024-09-12 10:50:49,519 - numba.core.ssa - DEBUG - on stmt: $70binary_subscr.5 = static_getitem(value=idx, index=0, index_var=$const68.4, fn=)\n", - "2024-09-12 10:50:49,520 - numba.core.ssa - DEBUG - on stmt: $const74.7 = const(int, 1)\n", - "2024-09-12 10:50:49,521 - numba.core.ssa - DEBUG - on stmt: $76binary_subscr.8 = static_getitem(value=idx, index=1, index_var=$const74.7, fn=)\n", - "2024-09-12 10:50:49,521 - numba.core.ssa - DEBUG - on stmt: $const80.10 = const(int, 2)\n", - "2024-09-12 10:50:49,522 - numba.core.ssa - DEBUG - on stmt: $82binary_subscr.11 = static_getitem(value=idx, index=2, index_var=$const80.10, fn=)\n", - "2024-09-12 10:50:49,523 - numba.core.ssa - DEBUG - on stmt: $84call_function.12 = call $64load_global.2($70binary_subscr.5, $76binary_subscr.8, $82binary_subscr.11, func=$64load_global.2, args=[Var($70binary_subscr.5, indexing.py:541), Var($76binary_subscr.8, indexing.py:541), Var($82binary_subscr.11, indexing.py:541)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,524 - numba.core.ssa - DEBUG - on stmt: $86get_iter.13 = getiter(value=$84call_function.12)\n", - "2024-09-12 10:50:49,524 - numba.core.ssa - DEBUG - on stmt: $phi88.1 = $86get_iter.13\n", - "2024-09-12 10:50:49,525 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:49,526 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 88\n", - "2024-09-12 10:50:49,526 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,527 - numba.core.ssa - DEBUG - on stmt: $88for_iter.2 = iternext(value=$phi88.1)\n", - "2024-09-12 10:50:49,527 - numba.core.ssa - DEBUG - on stmt: $88for_iter.3 = pair_first(value=$88for_iter.2)\n", - "2024-09-12 10:50:49,528 - numba.core.ssa - DEBUG - on stmt: $88for_iter.4 = pair_second(value=$88for_iter.2)\n", - "2024-09-12 10:50:49,529 - numba.core.ssa - DEBUG - on stmt: $phi90.2 = $88for_iter.3\n", - "2024-09-12 10:50:49,529 - numba.core.ssa - DEBUG - on stmt: branch $88for_iter.4, 90, 214\n", - "2024-09-12 10:50:49,530 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 90\n", - "2024-09-12 10:50:49,531 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,532 - numba.core.ssa - DEBUG - on stmt: p_match = $phi90.2\n", - "2024-09-12 10:50:49,532 - numba.core.ssa - DEBUG - on stmt: $92load_global.3 = global(np: )\n", - "2024-09-12 10:50:49,533 - numba.core.ssa - DEBUG - on stmt: $94load_attr.4 = getattr(value=$92load_global.3, attr=searchsorted)\n", - "2024-09-12 10:50:49,533 - numba.core.ssa - DEBUG - on stmt: $102binary_subscr.8 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,534 - numba.core.ssa - DEBUG - on stmt: $108binary_subscr.11 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:49,535 - numba.core.ssa - DEBUG - on stmt: $110build_slice.12 = global(slice: )\n", - "2024-09-12 10:50:49,535 - numba.core.ssa - DEBUG - on stmt: $110build_slice.13 = call $110build_slice.12($102binary_subscr.8, $108binary_subscr.11, func=$110build_slice.12, args=(Var($102binary_subscr.8, indexing.py:542), Var($108binary_subscr.11, indexing.py:542)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,536 - numba.core.ssa - DEBUG - on stmt: $112binary_subscr.14 = getitem(value=c, index=$110build_slice.13, fn=)\n", - "2024-09-12 10:50:49,537 - numba.core.ssa - DEBUG - on stmt: $const116.16 = const(str, left)\n", - "2024-09-12 10:50:49,537 - numba.core.ssa - DEBUG - on stmt: $120call_function_kw.18 = call $94load_attr.4($112binary_subscr.14, p_match, func=$94load_attr.4, args=[Var($112binary_subscr.14, indexing.py:542), Var(p_match, indexing.py:541)], kws=[('side', Var($const116.16, indexing.py:542))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,538 - numba.core.ssa - DEBUG - on stmt: $126binary_subscr.21 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,539 - numba.core.ssa - DEBUG - on stmt: start = $120call_function_kw.18 + $126binary_subscr.21\n", - "2024-09-12 10:50:49,540 - numba.core.ssa - DEBUG - on stmt: $132load_global.23 = global(np: )\n", - "2024-09-12 10:50:49,540 - numba.core.ssa - DEBUG - on stmt: $134load_attr.24 = getattr(value=$132load_global.23, attr=searchsorted)\n", - "2024-09-12 10:50:49,541 - numba.core.ssa - DEBUG - on stmt: $142binary_subscr.28 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,542 - numba.core.ssa - DEBUG - on stmt: $148binary_subscr.31 = getitem(value=stops_old, index=j, fn=)\n", - "2024-09-12 10:50:49,542 - numba.core.ssa - DEBUG - on stmt: $150build_slice.32 = global(slice: )\n", - "2024-09-12 10:50:49,543 - numba.core.ssa - DEBUG - on stmt: $150build_slice.33 = call $150build_slice.32($142binary_subscr.28, $148binary_subscr.31, func=$150build_slice.32, args=(Var($142binary_subscr.28, indexing.py:543), Var($148binary_subscr.31, indexing.py:543)), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,543 - numba.core.ssa - DEBUG - on stmt: $152binary_subscr.34 = getitem(value=c, index=$150build_slice.33, fn=)\n", - "2024-09-12 10:50:49,544 - numba.core.ssa - DEBUG - on stmt: $const156.36 = const(str, right)\n", - "2024-09-12 10:50:49,545 - numba.core.ssa - DEBUG - on stmt: $160call_function_kw.38 = call $134load_attr.24($152binary_subscr.34, p_match, func=$134load_attr.24, args=[Var($152binary_subscr.34, indexing.py:543), Var(p_match, indexing.py:541)], kws=[('side', Var($const156.36, indexing.py:543))], vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,546 - numba.core.ssa - DEBUG - on stmt: $166binary_subscr.41 = getitem(value=starts_old, index=j, fn=)\n", - "2024-09-12 10:50:49,546 - numba.core.ssa - DEBUG - on stmt: stop = $160call_function_kw.38 + $166binary_subscr.41\n", - "2024-09-12 10:50:49,547 - numba.core.ssa - DEBUG - on stmt: $176compare_op.45 = start != stop\n", - "2024-09-12 10:50:49,548 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:49,548 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.45, func=bool178, args=(Var($176compare_op.45, indexing.py:545),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,549 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 212\n", - "2024-09-12 10:50:49,549 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:49,550 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,551 - numba.core.ssa - DEBUG - on stmt: $182load_method.3 = getattr(value=starts, attr=append)\n", - "2024-09-12 10:50:49,551 - numba.core.ssa - DEBUG - on stmt: $186call_method.5 = call $182load_method.3(start, func=$182load_method.3, args=[Var(start, indexing.py:542)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,552 - numba.core.ssa - DEBUG - on stmt: $192load_method.7 = getattr(value=stops, attr=append)\n", - "2024-09-12 10:50:49,553 - numba.core.ssa - DEBUG - on stmt: $196call_method.9 = call $192load_method.7(stop, func=$192load_method.7, args=[Var(stop, indexing.py:543)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,553 - numba.core.ssa - DEBUG - on stmt: $206binary_subtract.13 = stop - start\n", - "2024-09-12 10:50:49,554 - numba.core.ssa - DEBUG - on stmt: $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:49,555 - numba.core.ssa - DEBUG - find_def var='n_matches' stmt=$208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:49,556 - numba.core.ssa - DEBUG - find_def_from_top label 180\n", - "2024-09-12 10:50:49,556 - numba.core.ssa - DEBUG - idom 90 from label 180\n", - "2024-09-12 10:50:49,557 - numba.core.ssa - DEBUG - find_def_from_bottom label 90\n", - "2024-09-12 10:50:49,557 - numba.core.ssa - DEBUG - find_def_from_top label 90\n", - "2024-09-12 10:50:49,558 - numba.core.ssa - DEBUG - idom 88 from label 90\n", - "2024-09-12 10:50:49,559 - numba.core.ssa - DEBUG - find_def_from_bottom label 88\n", - "2024-09-12 10:50:49,559 - numba.core.ssa - DEBUG - find_def_from_top label 88\n", - "2024-09-12 10:50:49,560 - numba.core.ssa - DEBUG - insert phi node n_matches.2 = phi(incoming_values=[], incoming_blocks=[]) at 88\n", - "2024-09-12 10:50:49,560 - numba.core.ssa - DEBUG - find_def_from_bottom label 212\n", - "2024-09-12 10:50:49,561 - numba.core.ssa - DEBUG - find_def_from_top label 212\n", - "2024-09-12 10:50:49,562 - numba.core.ssa - DEBUG - insert phi node n_matches.3 = phi(incoming_values=[], incoming_blocks=[]) at 212\n", - "2024-09-12 10:50:49,563 - numba.core.ssa - DEBUG - find_def_from_bottom label 90\n", - "2024-09-12 10:50:49,563 - numba.core.ssa - DEBUG - find_def_from_top label 90\n", - "2024-09-12 10:50:49,564 - numba.core.ssa - DEBUG - idom 88 from label 90\n", - "2024-09-12 10:50:49,564 - numba.core.ssa - DEBUG - find_def_from_bottom label 88\n", - "2024-09-12 10:50:49,565 - numba.core.ssa - DEBUG - incoming_def n_matches.2 = phi(incoming_values=[], incoming_blocks=[])\n", - "2024-09-12 10:50:49,566 - numba.core.ssa - DEBUG - find_def_from_bottom label 180\n", - "2024-09-12 10:50:49,566 - numba.core.ssa - DEBUG - incoming_def n_matches.1 = $208inplace_add.14\n", - "2024-09-12 10:50:49,567 - numba.core.ssa - DEBUG - incoming_def n_matches.3 = phi(incoming_values=[Var(n_matches.2, indexing.py:546), Var(n_matches.1, indexing.py:548)], incoming_blocks=[90, 180])\n", - "2024-09-12 10:50:49,568 - numba.core.ssa - DEBUG - find_def_from_bottom label 62\n", - "2024-09-12 10:50:49,568 - numba.core.ssa - DEBUG - find_def_from_top label 62\n", - "2024-09-12 10:50:49,569 - numba.core.ssa - DEBUG - idom 60 from label 62\n", - "2024-09-12 10:50:49,569 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:49,570 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:49,571 - numba.core.ssa - DEBUG - insert phi node n_matches.4 = phi(incoming_values=[], incoming_blocks=[]) at 60\n", - "2024-09-12 10:50:49,571 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:49,572 - numba.core.ssa - DEBUG - incoming_def n_matches = call $40load_method.17($const42.18, func=$40load_method.17, args=[Var($const42.18, indexing.py:536)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,578 - numba.core.ssa - DEBUG - find_def_from_bottom label 214\n", - "2024-09-12 10:50:49,579 - numba.core.ssa - DEBUG - find_def_from_top label 214\n", - "2024-09-12 10:50:49,579 - numba.core.ssa - DEBUG - idom 88 from label 214\n", - "2024-09-12 10:50:49,580 - numba.core.ssa - DEBUG - find_def_from_bottom label 88\n", - "2024-09-12 10:50:49,581 - numba.core.ssa - DEBUG - incoming_def n_matches.2 = phi(incoming_values=[Var(n_matches.3, indexing.py:546)], incoming_blocks=[212])\n", - "2024-09-12 10:50:49,581 - numba.core.ssa - DEBUG - incoming_def n_matches.4 = phi(incoming_values=[Var(n_matches, indexing.py:536), Var(n_matches.2, indexing.py:546)], incoming_blocks=[0, 214])\n", - "2024-09-12 10:50:49,582 - numba.core.ssa - DEBUG - replaced with: $208inplace_add.14 = inplace_binop(fn=, immutable_fn=, lhs=n_matches.2, rhs=$206binary_subtract.13, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:49,583 - numba.core.ssa - DEBUG - on stmt: n_matches.1 = $208inplace_add.14\n", - "2024-09-12 10:50:49,583 - numba.core.ssa - DEBUG - on stmt: jump 212\n", - "2024-09-12 10:50:49,584 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 212\n", - "2024-09-12 10:50:49,584 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,585 - numba.core.ssa - DEBUG - on stmt: jump 88\n", - "2024-09-12 10:50:49,585 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 214\n", - "2024-09-12 10:50:49,586 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,587 - numba.core.ssa - DEBUG - on stmt: jump 60\n", - "2024-09-12 10:50:49,587 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:49,588 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,588 - numba.core.ssa - DEBUG - on stmt: $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)])\n", - "2024-09-12 10:50:49,589 - numba.core.ssa - DEBUG - find_def var='n_matches' stmt=$222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches, indexing.py:536)])\n", - "2024-09-12 10:50:49,590 - numba.core.ssa - DEBUG - find_def_from_top label 216\n", - "2024-09-12 10:50:49,590 - numba.core.ssa - DEBUG - idom 60 from label 216\n", - "2024-09-12 10:50:49,591 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:49,594 - numba.core.ssa - DEBUG - replaced with: $222build_tuple.3 = build_tuple(items=[Var(starts, indexing.py:534), Var(stops, indexing.py:535), Var(n_matches.4, indexing.py:546)])\n", - "2024-09-12 10:50:49,595 - numba.core.ssa - DEBUG - on stmt: $224return_value.4 = cast(value=$222build_tuple.3)\n", - "2024-09-12 10:50:49,595 - numba.core.ssa - DEBUG - on stmt: return $224return_value.4\n", - "2024-09-12 10:50:49,633 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3773)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3774)\n", - " 4\tLOAD_FAST(arg=0, lineno=3774)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=3774)\n", - " 8\tSTORE_FAST(arg=3, lineno=3774)\n", - " 10\tLOAD_DEREF(arg=0, lineno=3775)\n", - " 12\tLOAD_FAST(arg=0, lineno=3775)\n", - " 14\tLOAD_FAST(arg=1, lineno=3775)\n", - " 16\tLOAD_FAST(arg=1, lineno=3775)\n", - " 18\tLOAD_CONST(arg=1, lineno=3775)\n", - " 20\tLOAD_FAST(arg=3, lineno=3775)\n", - " 22\tLOAD_FAST(arg=3, lineno=3775)\n", - " 24\tCALL_FUNCTION(arg=6, lineno=3775)\n", - " 26\tRETURN_VALUE(arg=None, lineno=3775)\n", - "2024-09-12 10:50:49,637 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:49,639 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,639 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:49,640 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3773)\n", - "2024-09-12 10:50:49,640 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,641 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3774)\n", - "2024-09-12 10:50:49,641 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,646 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=3774)\n", - "2024-09-12 10:50:49,647 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:49,647 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=3774)\n", - "2024-09-12 10:50:49,648 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$a4.1']\n", - "2024-09-12 10:50:49,648 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=3, lineno=3774)\n", - "2024-09-12 10:50:49,648 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-09-12 10:50:49,649 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_DEREF(arg=0, lineno=3775)\n", - "2024-09-12 10:50:49,649 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,650 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=0, lineno=3775)\n", - "2024-09-12 10:50:49,650 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3']\n", - "2024-09-12 10:50:49,651 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:49,651 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4']\n", - "2024-09-12 10:50:49,656 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:49,656 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5']\n", - "2024-09-12 10:50:49,656 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:49,657 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6']\n", - "2024-09-12 10:50:49,657 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-09-12 10:50:49,658 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7']\n", - "2024-09-12 10:50:49,658 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-09-12 10:50:49,659 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8']\n", - "2024-09-12 10:50:49,659 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=CALL_FUNCTION(arg=6, lineno=3775)\n", - "2024-09-12 10:50:49,659 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9']\n", - "2024-09-12 10:50:49,660 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=RETURN_VALUE(arg=None, lineno=3775)\n", - "2024-09-12 10:50:49,660 - numba.core.byteflow - DEBUG - stack ['$24call_function.10']\n", - "2024-09-12 10:50:49,661 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:49,661 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:49,662 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:49,662 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:49,662 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:49,663 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:49,663 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:49,664 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:49,664 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:49,664 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$a4.1'}), (6, {'func': '$2load_global.0', 'args': ['$a4.1'], 'res': '$6call_function.2'}), (8, {'value': '$6call_function.2'}), (10, {'res': '$10load_deref.3'}), (12, {'res': '$a12.4'}), (14, {'res': '$v14.5'}), (16, {'res': '$v16.6'}), (18, {'res': '$const18.7'}), (20, {'res': '$n20.8'}), (22, {'res': '$n22.9'}), (24, {'func': '$10load_deref.3', 'args': ['$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9'], 'res': '$24call_function.10'}), (26, {'retval': '$24call_function.10', 'castval': '$26return_value.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:49,665 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " side = arg(2, name=side) ['side']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'a', 'n']\n", - " $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f2dc32ed000>) ['$10load_deref.3']\n", - " $const18.7 = const(int, 0) ['$const18.7']\n", - " $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_deref.3', '$24call_function.10', '$const18.7', 'a', 'n', 'n', 'v', 'v']\n", - " $26return_value.11 = cast(value=$24call_function.10) ['$24call_function.10', '$26return_value.11']\n", - " return $26return_value.11 ['$26return_value.11']\n", - "\n", - "2024-09-12 10:50:49,674 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:49,675 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,675 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:49,676 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:49,676 - numba.core.ssa - DEBUG - on stmt: side = arg(2, name=side)\n", - "2024-09-12 10:50:49,677 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-09-12 10:50:49,677 - numba.core.ssa - DEBUG - on stmt: n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,677 - numba.core.ssa - DEBUG - on stmt: $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f2dc32ed000>)\n", - "2024-09-12 10:50:49,678 - numba.core.ssa - DEBUG - on stmt: $const18.7 = const(int, 0)\n", - "2024-09-12 10:50:49,678 - numba.core.ssa - DEBUG - on stmt: $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,679 - numba.core.ssa - DEBUG - on stmt: $26return_value.11 = cast(value=$24call_function.10)\n", - "2024-09-12 10:50:49,679 - numba.core.ssa - DEBUG - on stmt: return $26return_value.11\n", - "2024-09-12 10:50:49,680 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_deref.3': [],\n", - " '$24call_function.10': [],\n", - " '$26return_value.11': [],\n", - " '$2load_global.0': [],\n", - " '$const18.7': [],\n", - " 'a': [],\n", - " 'n': [],\n", - " 'side': [],\n", - " 'v': []})\n", - "2024-09-12 10:50:49,680 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:49,684 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3678)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3701)\n", - " 4\tLOAD_METHOD(arg=1, lineno=3701)\n", - " 6\tLOAD_FAST(arg=1, lineno=3701)\n", - " 8\tCALL_METHOD(arg=1, lineno=3701)\n", - " 10\tPOP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - " 12\tLOAD_GLOBAL(arg=2, lineno=3704)\n", - " 14\tLOAD_FAST(arg=5, lineno=3704)\n", - " 16\tLOAD_CONST(arg=1, lineno=3704)\n", - " 18\tLOAD_CONST(arg=2, lineno=3704)\n", - " 20\tCALL_FUNCTION(arg=3, lineno=3704)\n", - " 22\tGET_ITER(arg=None, lineno=3704)\n", - "> 24\tFOR_ITER(arg=15, lineno=3704)\n", - " 26\tSTORE_FAST(arg=6, lineno=3704)\n", - " 28\tLOAD_GLOBAL(arg=0, lineno=3705)\n", - " 30\tLOAD_METHOD(arg=1, lineno=3705)\n", - " 32\tLOAD_FAST(arg=0, lineno=3705)\n", - " 34\tLOAD_FAST(arg=6, lineno=3705)\n", - " 36\tLOAD_CONST(arg=3, lineno=3705)\n", - " 38\tBINARY_SUBTRACT(arg=None, lineno=3705)\n", - " 40\tBINARY_SUBSCR(arg=None, lineno=3705)\n", - " 42\tCALL_METHOD(arg=1, lineno=3705)\n", - " 44\tPOP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - " 46\tLOAD_FAST(arg=6, lineno=3706)\n", - " 48\tROT_TWO(arg=None, lineno=3706)\n", - " 50\tPOP_TOP(arg=None, lineno=3706)\n", - " 52\tRETURN_VALUE(arg=None, lineno=3706)\n", - "> 54\tJUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "> 56\tLOAD_CONST(arg=1, lineno=3707)\n", - " 58\tRETURN_VALUE(arg=None, lineno=3707)\n", - "> 60\tLOAD_FAST(arg=2, lineno=3709)\n", - " 62\tLOAD_FAST(arg=1, lineno=3709)\n", - " 64\tCOMPARE_OP(arg=0, lineno=3709)\n", - " 66\tPOP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - " 68\tLOAD_FAST(arg=5, lineno=3710)\n", - " 70\tSTORE_FAST(arg=4, lineno=3710)\n", - " 72\tJUMP_FORWARD(arg=12, lineno=3710)\n", - "> 74\tLOAD_CONST(arg=1, lineno=3712)\n", - " 76\tSTORE_FAST(arg=3, lineno=3712)\n", - " 78\tLOAD_FAST(arg=4, lineno=3713)\n", - " 80\tLOAD_FAST(arg=5, lineno=3713)\n", - " 82\tCOMPARE_OP(arg=0, lineno=3713)\n", - " 84\tPOP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - " 86\tLOAD_FAST(arg=4, lineno=3713)\n", - " 88\tLOAD_CONST(arg=3, lineno=3713)\n", - " 90\tBINARY_ADD(arg=None, lineno=3713)\n", - " 92\tJUMP_FORWARD(arg=1, lineno=3713)\n", - "> 94\tLOAD_FAST(arg=5, lineno=3713)\n", - "> 96\tSTORE_FAST(arg=4, lineno=3713)\n", - "> 98\tLOAD_FAST(arg=4, lineno=3715)\n", - " 100\tLOAD_FAST(arg=3, lineno=3715)\n", - " 102\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 104\tPOP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "> 106\tLOAD_FAST(arg=3, lineno=3716)\n", - " 108\tLOAD_FAST(arg=4, lineno=3716)\n", - " 110\tBINARY_ADD(arg=None, lineno=3716)\n", - " 112\tLOAD_CONST(arg=3, lineno=3716)\n", - " 114\tBINARY_RSHIFT(arg=None, lineno=3716)\n", - " 116\tSTORE_FAST(arg=7, lineno=3716)\n", - " 118\tLOAD_DEREF(arg=0, lineno=3717)\n", - " 120\tLOAD_FAST(arg=0, lineno=3717)\n", - " 122\tLOAD_FAST(arg=7, lineno=3717)\n", - " 124\tBINARY_SUBSCR(arg=None, lineno=3717)\n", - " 126\tLOAD_FAST(arg=1, lineno=3717)\n", - " 128\tCALL_FUNCTION(arg=2, lineno=3717)\n", - " 130\tPOP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - " 132\tLOAD_FAST(arg=7, lineno=3719)\n", - " 134\tLOAD_CONST(arg=3, lineno=3719)\n", - " 136\tBINARY_ADD(arg=None, lineno=3719)\n", - " 138\tSTORE_FAST(arg=3, lineno=3719)\n", - " 140\tJUMP_FORWARD(arg=2, lineno=3719)\n", - "> 142\tLOAD_FAST(arg=7, lineno=3722)\n", - " 144\tSTORE_FAST(arg=4, lineno=3722)\n", - "> 146\tLOAD_FAST(arg=4, lineno=3715)\n", - " 148\tLOAD_FAST(arg=3, lineno=3715)\n", - " 150\tCOMPARE_OP(arg=4, lineno=3715)\n", - " 152\tPOP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "> 154\tLOAD_FAST(arg=3, lineno=3723)\n", - " 156\tRETURN_VALUE(arg=None, lineno=3723)\n", - "2024-09-12 10:50:49,684 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:49,685 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,685 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:49,686 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3678)\n", - "2024-09-12 10:50:49,686 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,687 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3701)\n", - "2024-09-12 10:50:49,687 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,687 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_METHOD(arg=1, lineno=3701)\n", - "2024-09-12 10:50:49,688 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:49,688 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_FAST(arg=1, lineno=3701)\n", - "2024-09-12 10:50:49,689 - numba.core.byteflow - DEBUG - stack ['$4load_method.1']\n", - "2024-09-12 10:50:49,692 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=CALL_METHOD(arg=1, lineno=3701)\n", - "2024-09-12 10:50:49,693 - numba.core.byteflow - DEBUG - stack ['$4load_method.1', '$v6.2']\n", - "2024-09-12 10:50:49,693 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=POP_JUMP_IF_FALSE(arg=31, lineno=3701)\n", - "2024-09-12 10:50:49,693 - numba.core.byteflow - DEBUG - stack ['$8call_method.3']\n", - "2024-09-12 10:50:49,694 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=12, stack=(), blockstack=(), npush=0), Edge(pc=60, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,694 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=12 nstack_initial=0), State(pc_initial=60 nstack_initial=0)])\n", - "2024-09-12 10:50:49,695 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,695 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=12 nstack_initial=0)\n", - "2024-09-12 10:50:49,696 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_GLOBAL(arg=2, lineno=3704)\n", - "2024-09-12 10:50:49,696 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,696 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=5, lineno=3704)\n", - "2024-09-12 10:50:49,697 - numba.core.byteflow - DEBUG - stack ['$12load_global.0']\n", - "2024-09-12 10:50:49,697 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_CONST(arg=1, lineno=3704)\n", - "2024-09-12 10:50:49,698 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1']\n", - "2024-09-12 10:50:49,698 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=2, lineno=3704)\n", - "2024-09-12 10:50:49,702 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2']\n", - "2024-09-12 10:50:49,703 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=CALL_FUNCTION(arg=3, lineno=3704)\n", - "2024-09-12 10:50:49,703 - numba.core.byteflow - DEBUG - stack ['$12load_global.0', '$n14.1', '$const16.2', '$const18.3']\n", - "2024-09-12 10:50:49,704 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=GET_ITER(arg=None, lineno=3704)\n", - "2024-09-12 10:50:49,704 - numba.core.byteflow - DEBUG - stack ['$20call_function.4']\n", - "2024-09-12 10:50:49,705 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$22get_iter.5',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,705 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=60 nstack_initial=0), State(pc_initial=24 nstack_initial=1)])\n", - "2024-09-12 10:50:49,705 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,706 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=60 nstack_initial=0)\n", - "2024-09-12 10:50:49,706 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=LOAD_FAST(arg=2, lineno=3709)\n", - "2024-09-12 10:50:49,707 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,707 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_FAST(arg=1, lineno=3709)\n", - "2024-09-12 10:50:49,707 - numba.core.byteflow - DEBUG - stack ['$v_last60.0']\n", - "2024-09-12 10:50:49,708 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=COMPARE_OP(arg=0, lineno=3709)\n", - "2024-09-12 10:50:49,708 - numba.core.byteflow - DEBUG - stack ['$v_last60.0', '$v62.1']\n", - "2024-09-12 10:50:49,709 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=POP_JUMP_IF_FALSE(arg=38, lineno=3709)\n", - "2024-09-12 10:50:49,709 - numba.core.byteflow - DEBUG - stack ['$64compare_op.2']\n", - "2024-09-12 10:50:49,709 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=68, stack=(), blockstack=(), npush=0), Edge(pc=74, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,710 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0)])\n", - "2024-09-12 10:50:49,710 - numba.core.byteflow - DEBUG - stack: ['$phi24.0']\n", - "2024-09-12 10:50:49,711 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=24 nstack_initial=1)\n", - "2024-09-12 10:50:49,711 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=FOR_ITER(arg=15, lineno=3704)\n", - "2024-09-12 10:50:49,711 - numba.core.byteflow - DEBUG - stack ['$phi24.0']\n", - "2024-09-12 10:50:49,712 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=56, stack=(), blockstack=(), npush=0), Edge(pc=26, stack=('$phi24.0', '$24for_iter.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,712 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=68 nstack_initial=0), State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2)])\n", - "2024-09-12 10:50:49,713 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,713 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=68 nstack_initial=0)\n", - "2024-09-12 10:50:49,714 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=LOAD_FAST(arg=5, lineno=3710)\n", - "2024-09-12 10:50:49,714 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,714 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=STORE_FAST(arg=4, lineno=3710)\n", - "2024-09-12 10:50:49,715 - numba.core.byteflow - DEBUG - stack ['$n68.0']\n", - "2024-09-12 10:50:49,715 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=JUMP_FORWARD(arg=12, lineno=3710)\n", - "2024-09-12 10:50:49,716 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,716 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,716 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=0), State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:49,717 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,717 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=0)\n", - "2024-09-12 10:50:49,718 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=LOAD_CONST(arg=1, lineno=3712)\n", - "2024-09-12 10:50:49,718 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,718 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=STORE_FAST(arg=3, lineno=3712)\n", - "2024-09-12 10:50:49,719 - numba.core.byteflow - DEBUG - stack ['$const74.0']\n", - "2024-09-12 10:50:49,719 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-09-12 10:50:49,730 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,730 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-09-12 10:50:49,731 - numba.core.byteflow - DEBUG - stack ['$hi78.1']\n", - "2024-09-12 10:50:49,731 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=COMPARE_OP(arg=0, lineno=3713)\n", - "2024-09-12 10:50:49,731 - numba.core.byteflow - DEBUG - stack ['$hi78.1', '$n80.2']\n", - "2024-09-12 10:50:49,732 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=POP_JUMP_IF_FALSE(arg=48, lineno=3713)\n", - "2024-09-12 10:50:49,732 - numba.core.byteflow - DEBUG - stack ['$82compare_op.3']\n", - "2024-09-12 10:50:49,733 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=86, stack=(), blockstack=(), npush=0), Edge(pc=94, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,733 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=0), State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-09-12 10:50:49,733 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,734 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=0)\n", - "2024-09-12 10:50:49,734 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=LOAD_CONST(arg=1, lineno=3707)\n", - "2024-09-12 10:50:49,734 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,735 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=RETURN_VALUE(arg=None, lineno=3707)\n", - "2024-09-12 10:50:49,735 - numba.core.byteflow - DEBUG - stack ['$const56.0']\n", - "2024-09-12 10:50:49,736 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:49,736 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=26 nstack_initial=2), State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0)])\n", - "2024-09-12 10:50:49,736 - numba.core.byteflow - DEBUG - stack: ['$phi26.0', '$phi26.1']\n", - "2024-09-12 10:50:49,737 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=26 nstack_initial=2)\n", - "2024-09-12 10:50:49,737 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=STORE_FAST(arg=6, lineno=3704)\n", - "2024-09-12 10:50:49,737 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$phi26.1']\n", - "2024-09-12 10:50:49,738 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=LOAD_GLOBAL(arg=0, lineno=3705)\n", - "2024-09-12 10:50:49,738 - numba.core.byteflow - DEBUG - stack ['$phi26.0']\n", - "2024-09-12 10:50:49,739 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=LOAD_METHOD(arg=1, lineno=3705)\n", - "2024-09-12 10:50:49,739 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$28load_global.2']\n", - "2024-09-12 10:50:49,739 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=LOAD_FAST(arg=0, lineno=3705)\n", - "2024-09-12 10:50:49,740 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3']\n", - "2024-09-12 10:50:49,740 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=LOAD_FAST(arg=6, lineno=3705)\n", - "2024-09-12 10:50:49,740 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4']\n", - "2024-09-12 10:50:49,741 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_CONST(arg=3, lineno=3705)\n", - "2024-09-12 10:50:49,741 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5']\n", - "2024-09-12 10:50:49,741 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=BINARY_SUBTRACT(arg=None, lineno=3705)\n", - "2024-09-12 10:50:49,742 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$i34.5', '$const36.6']\n", - "2024-09-12 10:50:49,742 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=BINARY_SUBSCR(arg=None, lineno=3705)\n", - "2024-09-12 10:50:49,743 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$a32.4', '$38binary_subtract.7']\n", - "2024-09-12 10:50:49,743 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=CALL_METHOD(arg=1, lineno=3705)\n", - "2024-09-12 10:50:49,743 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$30load_method.3', '$40binary_subscr.8']\n", - "2024-09-12 10:50:49,744 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=POP_JUMP_IF_TRUE(arg=28, lineno=3705)\n", - "2024-09-12 10:50:49,744 - numba.core.byteflow - DEBUG - stack ['$phi26.0', '$42call_method.9']\n", - "2024-09-12 10:50:49,744 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=46, stack=('$phi26.0',), blockstack=(), npush=0), Edge(pc=54, stack=('$phi26.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,745 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1)])\n", - "2024-09-12 10:50:49,745 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,746 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=98 nstack_initial=0)\n", - "2024-09-12 10:50:49,746 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-09-12 10:50:49,746 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,747 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-09-12 10:50:49,747 - numba.core.byteflow - DEBUG - stack ['$hi98.0']\n", - "2024-09-12 10:50:49,747 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-09-12 10:50:49,748 - numba.core.byteflow - DEBUG - stack ['$hi98.0', '$lo100.1']\n", - "2024-09-12 10:50:49,748 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=POP_JUMP_IF_FALSE(arg=78, lineno=3715)\n", - "2024-09-12 10:50:49,748 - numba.core.byteflow - DEBUG - stack ['$102compare_op.2']\n", - "2024-09-12 10:50:49,749 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=106, stack=(), blockstack=(), npush=0), Edge(pc=154, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,749 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=86 nstack_initial=0), State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0)])\n", - "2024-09-12 10:50:49,750 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,750 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=86 nstack_initial=0)\n", - "2024-09-12 10:50:49,750 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=4, lineno=3713)\n", - "2024-09-12 10:50:49,751 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,751 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_CONST(arg=3, lineno=3713)\n", - "2024-09-12 10:50:49,752 - numba.core.byteflow - DEBUG - stack ['$hi86.0']\n", - "2024-09-12 10:50:49,752 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=BINARY_ADD(arg=None, lineno=3713)\n", - "2024-09-12 10:50:49,752 - numba.core.byteflow - DEBUG - stack ['$hi86.0', '$const88.1']\n", - "2024-09-12 10:50:49,753 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=JUMP_FORWARD(arg=1, lineno=3713)\n", - "2024-09-12 10:50:49,753 - numba.core.byteflow - DEBUG - stack ['$90binary_add.2']\n", - "2024-09-12 10:50:49,754 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$90binary_add.2',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,754 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=94 nstack_initial=0), State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1)])\n", - "2024-09-12 10:50:49,754 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,755 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=94 nstack_initial=0)\n", - "2024-09-12 10:50:49,755 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=LOAD_FAST(arg=5, lineno=3713)\n", - "2024-09-12 10:50:49,755 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,756 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=96, stack=('$n94.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,756 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=46 nstack_initial=1), State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-09-12 10:50:49,757 - numba.core.byteflow - DEBUG - stack: ['$phi46.0']\n", - "2024-09-12 10:50:49,757 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=46 nstack_initial=1)\n", - "2024-09-12 10:50:49,757 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=6, lineno=3706)\n", - "2024-09-12 10:50:49,758 - numba.core.byteflow - DEBUG - stack ['$phi46.0']\n", - "2024-09-12 10:50:49,758 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=ROT_TWO(arg=None, lineno=3706)\n", - "2024-09-12 10:50:49,758 - numba.core.byteflow - DEBUG - stack ['$phi46.0', '$i46.1']\n", - "2024-09-12 10:50:49,759 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=POP_TOP(arg=None, lineno=3706)\n", - "2024-09-12 10:50:49,759 - numba.core.byteflow - DEBUG - stack ['$i46.1', '$phi46.0']\n", - "2024-09-12 10:50:49,760 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=RETURN_VALUE(arg=None, lineno=3706)\n", - "2024-09-12 10:50:49,760 - numba.core.byteflow - DEBUG - stack ['$i46.1']\n", - "2024-09-12 10:50:49,760 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:49,761 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=1), State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1)])\n", - "2024-09-12 10:50:49,761 - numba.core.byteflow - DEBUG - stack: ['$phi54.0']\n", - "2024-09-12 10:50:49,770 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=1)\n", - "2024-09-12 10:50:49,770 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=JUMP_ABSOLUTE(arg=13, lineno=3705)\n", - "2024-09-12 10:50:49,771 - numba.core.byteflow - DEBUG - stack ['$phi54.0']\n", - "2024-09-12 10:50:49,771 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=24, stack=('$phi54.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,772 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1)])\n", - "2024-09-12 10:50:49,772 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,772 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=106 nstack_initial=0)\n", - "2024-09-12 10:50:49,773 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=LOAD_FAST(arg=3, lineno=3716)\n", - "2024-09-12 10:50:49,773 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,773 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=LOAD_FAST(arg=4, lineno=3716)\n", - "2024-09-12 10:50:49,774 - numba.core.byteflow - DEBUG - stack ['$lo106.0']\n", - "2024-09-12 10:50:49,774 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=BINARY_ADD(arg=None, lineno=3716)\n", - "2024-09-12 10:50:49,775 - numba.core.byteflow - DEBUG - stack ['$lo106.0', '$hi108.1']\n", - "2024-09-12 10:50:49,775 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=3, lineno=3716)\n", - "2024-09-12 10:50:49,775 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2']\n", - "2024-09-12 10:50:49,776 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BINARY_RSHIFT(arg=None, lineno=3716)\n", - "2024-09-12 10:50:49,776 - numba.core.byteflow - DEBUG - stack ['$110binary_add.2', '$const112.3']\n", - "2024-09-12 10:50:49,777 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=STORE_FAST(arg=7, lineno=3716)\n", - "2024-09-12 10:50:49,777 - numba.core.byteflow - DEBUG - stack ['$114binary_rshift.4']\n", - "2024-09-12 10:50:49,777 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_DEREF(arg=0, lineno=3717)\n", - "2024-09-12 10:50:49,778 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,778 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=LOAD_FAST(arg=0, lineno=3717)\n", - "2024-09-12 10:50:49,778 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5']\n", - "2024-09-12 10:50:49,779 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=LOAD_FAST(arg=7, lineno=3717)\n", - "2024-09-12 10:50:49,779 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6']\n", - "2024-09-12 10:50:49,780 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=BINARY_SUBSCR(arg=None, lineno=3717)\n", - "2024-09-12 10:50:49,780 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$a120.6', '$mid122.7']\n", - "2024-09-12 10:50:49,780 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_FAST(arg=1, lineno=3717)\n", - "2024-09-12 10:50:49,781 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8']\n", - "2024-09-12 10:50:49,781 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=CALL_FUNCTION(arg=2, lineno=3717)\n", - "2024-09-12 10:50:49,781 - numba.core.byteflow - DEBUG - stack ['$118load_deref.5', '$124binary_subscr.8', '$v126.9']\n", - "2024-09-12 10:50:49,782 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=POP_JUMP_IF_FALSE(arg=72, lineno=3717)\n", - "2024-09-12 10:50:49,782 - numba.core.byteflow - DEBUG - stack ['$128call_function.10']\n", - "2024-09-12 10:50:49,783 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=132, stack=(), blockstack=(), npush=0), Edge(pc=142, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,783 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-09-12 10:50:49,783 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,784 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=154 nstack_initial=0)\n", - "2024-09-12 10:50:49,784 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_FAST(arg=3, lineno=3723)\n", - "2024-09-12 10:50:49,784 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,785 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=RETURN_VALUE(arg=None, lineno=3723)\n", - "2024-09-12 10:50:49,785 - numba.core.byteflow - DEBUG - stack ['$lo154.0']\n", - "2024-09-12 10:50:49,786 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:49,786 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0)])\n", - "2024-09-12 10:50:49,786 - numba.core.byteflow - DEBUG - stack: ['$phi96.0']\n", - "2024-09-12 10:50:49,787 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=96 nstack_initial=1)\n", - "2024-09-12 10:50:49,787 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=STORE_FAST(arg=4, lineno=3713)\n", - "2024-09-12 10:50:49,787 - numba.core.byteflow - DEBUG - stack ['$phi96.0']\n", - "2024-09-12 10:50:49,788 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=98, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,788 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=96 nstack_initial=1), State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:49,788 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=24 nstack_initial=1), State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:49,789 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=132 nstack_initial=0), State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0)])\n", - "2024-09-12 10:50:49,789 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,790 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=132 nstack_initial=0)\n", - "2024-09-12 10:50:49,790 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=LOAD_FAST(arg=7, lineno=3719)\n", - "2024-09-12 10:50:49,790 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,791 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=LOAD_CONST(arg=3, lineno=3719)\n", - "2024-09-12 10:50:49,791 - numba.core.byteflow - DEBUG - stack ['$mid132.0']\n", - "2024-09-12 10:50:49,792 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=BINARY_ADD(arg=None, lineno=3719)\n", - "2024-09-12 10:50:49,792 - numba.core.byteflow - DEBUG - stack ['$mid132.0', '$const134.1']\n", - "2024-09-12 10:50:49,792 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=STORE_FAST(arg=3, lineno=3719)\n", - "2024-09-12 10:50:49,793 - numba.core.byteflow - DEBUG - stack ['$136binary_add.2']\n", - "2024-09-12 10:50:49,793 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=JUMP_FORWARD(arg=2, lineno=3719)\n", - "2024-09-12 10:50:49,793 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,794 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,794 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=142 nstack_initial=0), State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-09-12 10:50:49,795 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,795 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=142 nstack_initial=0)\n", - "2024-09-12 10:50:49,795 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=7, lineno=3722)\n", - "2024-09-12 10:50:49,796 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,796 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=STORE_FAST(arg=4, lineno=3722)\n", - "2024-09-12 10:50:49,796 - numba.core.byteflow - DEBUG - stack ['$mid142.0']\n", - "2024-09-12 10:50:49,797 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=146, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,797 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=98 nstack_initial=0), State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-09-12 10:50:49,798 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=146 nstack_initial=0)])\n", - "2024-09-12 10:50:49,798 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:49,798 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=146 nstack_initial=0)\n", - "2024-09-12 10:50:49,799 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=LOAD_FAST(arg=4, lineno=3715)\n", - "2024-09-12 10:50:49,799 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:49,800 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=LOAD_FAST(arg=3, lineno=3715)\n", - "2024-09-12 10:50:49,800 - numba.core.byteflow - DEBUG - stack ['$hi146.0']\n", - "2024-09-12 10:50:49,800 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=COMPARE_OP(arg=4, lineno=3715)\n", - "2024-09-12 10:50:49,801 - numba.core.byteflow - DEBUG - stack ['$hi146.0', '$lo148.1']\n", - "2024-09-12 10:50:49,801 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=POP_JUMP_IF_TRUE(arg=54, lineno=3715)\n", - "2024-09-12 10:50:49,801 - numba.core.byteflow - DEBUG - stack ['$150compare_op.2']\n", - "2024-09-12 10:50:49,802 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=154, stack=(), blockstack=(), npush=0), Edge(pc=106, stack=(), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:49,802 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=146 nstack_initial=0), State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-09-12 10:50:49,803 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=154 nstack_initial=0), State(pc_initial=106 nstack_initial=0)])\n", - "2024-09-12 10:50:49,803 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=106 nstack_initial=0)])\n", - "2024-09-12 10:50:49,803 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:49,804 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=12 nstack_initial=0): set(),\n", - " State(pc_initial=24 nstack_initial=1): {'$phi24.0'},\n", - " State(pc_initial=26 nstack_initial=2): {'$phi26.1'},\n", - " State(pc_initial=46 nstack_initial=1): set(),\n", - " State(pc_initial=54 nstack_initial=1): set(),\n", - " State(pc_initial=56 nstack_initial=0): set(),\n", - " State(pc_initial=60 nstack_initial=0): set(),\n", - " State(pc_initial=68 nstack_initial=0): set(),\n", - " State(pc_initial=74 nstack_initial=0): set(),\n", - " State(pc_initial=86 nstack_initial=0): set(),\n", - " State(pc_initial=94 nstack_initial=0): set(),\n", - " State(pc_initial=96 nstack_initial=1): {'$phi96.0'},\n", - " State(pc_initial=98 nstack_initial=0): set(),\n", - " State(pc_initial=106 nstack_initial=0): set(),\n", - " State(pc_initial=132 nstack_initial=0): set(),\n", - " State(pc_initial=142 nstack_initial=0): set(),\n", - " State(pc_initial=146 nstack_initial=0): set(),\n", - " State(pc_initial=154 nstack_initial=0): set()})\n", - "2024-09-12 10:50:49,804 - numba.core.byteflow - DEBUG - defmap: {'$phi24.0': State(pc_initial=12 nstack_initial=0),\n", - " '$phi26.1': State(pc_initial=24 nstack_initial=1),\n", - " '$phi96.0': State(pc_initial=86 nstack_initial=0)}\n", - "2024-09-12 10:50:49,805 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi54.0', State(pc_initial=54 nstack_initial=1))},\n", - " '$phi26.0': {('$phi24.0', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi54.0': {('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:49,805 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0)),\n", - " ('$phi26.0', State(pc_initial=26 nstack_initial=2))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:49,806 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:49,807 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi24.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2',\n", - " State(pc_initial=24 nstack_initial=1))},\n", - " '$phi46.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi54.0': {('$22get_iter.5',\n", - " State(pc_initial=12 nstack_initial=0))},\n", - " '$phi96.0': {('$90binary_add.2',\n", - " State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}})\n", - "2024-09-12 10:50:49,807 - numba.core.byteflow - DEBUG - keep phismap: {'$phi24.0': {('$22get_iter.5', State(pc_initial=12 nstack_initial=0))},\n", - " '$phi26.1': {('$24for_iter.2', State(pc_initial=24 nstack_initial=1))},\n", - " '$phi96.0': {('$90binary_add.2', State(pc_initial=86 nstack_initial=0)),\n", - " ('$n94.0', State(pc_initial=94 nstack_initial=0))}}\n", - "2024-09-12 10:50:49,808 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=12 nstack_initial=0): {'$phi24.0': '$22get_iter.5'},\n", - " State(pc_initial=24 nstack_initial=1): {'$phi26.1': '$24for_iter.2'},\n", - " State(pc_initial=86 nstack_initial=0): {'$phi96.0': '$90binary_add.2'},\n", - " State(pc_initial=94 nstack_initial=0): {'$phi96.0': '$n94.0'}})\n", - "2024-09-12 10:50:49,808 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:49,809 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_method.1'}), (6, {'res': '$v6.2'}), (8, {'func': '$4load_method.1', 'args': ['$v6.2'], 'res': '$8call_method.3'}), (10, {'pred': '$8call_method.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={12: (), 60: ()})\n", - "2024-09-12 10:50:49,809 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=12 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((12, {'res': '$12load_global.0'}), (14, {'res': '$n14.1'}), (16, {'res': '$const16.2'}), (18, {'res': '$const18.3'}), (20, {'func': '$12load_global.0', 'args': ['$n14.1', '$const16.2', '$const18.3'], 'res': '$20call_function.4'}), (22, {'value': '$20call_function.4', 'res': '$22get_iter.5'})), outgoing_phis={'$phi24.0': '$22get_iter.5'}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$22get_iter.5',)})\n", - "2024-09-12 10:50:49,809 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=24 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((24, {'iterator': '$phi24.0', 'pair': '$24for_iter.1', 'indval': '$24for_iter.2', 'pred': '$24for_iter.3'}),), outgoing_phis={'$phi26.1': '$24for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={56: (), 26: ('$phi24.0', '$24for_iter.2')})\n", - "2024-09-12 10:50:49,810 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=26 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((26, {'value': '$phi26.1'}), (28, {'res': '$28load_global.2'}), (30, {'item': '$28load_global.2', 'res': '$30load_method.3'}), (32, {'res': '$a32.4'}), (34, {'res': '$i34.5'}), (36, {'res': '$const36.6'}), (38, {'lhs': '$i34.5', 'rhs': '$const36.6', 'res': '$38binary_subtract.7'}), (40, {'index': '$38binary_subtract.7', 'target': '$a32.4', 'res': '$40binary_subscr.8'}), (42, {'func': '$30load_method.3', 'args': ['$40binary_subscr.8'], 'res': '$42call_method.9'}), (44, {'pred': '$42call_method.9'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={46: ('$phi26.0',), 54: ('$phi26.0',)})\n", - "2024-09-12 10:50:49,810 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=46 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((46, {'res': '$i46.1'}), (52, {'retval': '$i46.1', 'castval': '$52return_value.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:49,811 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((54, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={24: ('$phi54.0',)})\n", - "2024-09-12 10:50:49,811 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((56, {'res': '$const56.0'}), (58, {'retval': '$const56.0', 'castval': '$58return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:49,812 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=60 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((60, {'res': '$v_last60.0'}), (62, {'res': '$v62.1'}), (64, {'lhs': '$v_last60.0', 'rhs': '$v62.1', 'res': '$64compare_op.2'}), (66, {'pred': '$64compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={68: (), 74: ()})\n", - "2024-09-12 10:50:49,812 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=68 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((68, {'res': '$n68.0'}), (70, {'value': '$n68.0'}), (72, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-09-12 10:50:49,812 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((74, {'res': '$const74.0'}), (76, {'value': '$const74.0'}), (78, {'res': '$hi78.1'}), (80, {'res': '$n80.2'}), (82, {'lhs': '$hi78.1', 'rhs': '$n80.2', 'res': '$82compare_op.3'}), (84, {'pred': '$82compare_op.3'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={86: (), 94: ()})\n", - "2024-09-12 10:50:49,813 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=86 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((86, {'res': '$hi86.0'}), (88, {'res': '$const88.1'}), (90, {'lhs': '$hi86.0', 'rhs': '$const88.1', 'res': '$90binary_add.2'}), (92, {})), outgoing_phis={'$phi96.0': '$90binary_add.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$90binary_add.2',)})\n", - "2024-09-12 10:50:49,813 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=94 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((94, {'res': '$n94.0'}),), outgoing_phis={'$phi96.0': '$n94.0'}, blockstack=(), active_try_block=None, outgoing_edgepushed={96: ('$n94.0',)})\n", - "2024-09-12 10:50:49,813 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=96 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((96, {'value': '$phi96.0'}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={98: ()})\n", - "2024-09-12 10:50:49,814 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=98 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((98, {'res': '$hi98.0'}), (100, {'res': '$lo100.1'}), (102, {'lhs': '$hi98.0', 'rhs': '$lo100.1', 'res': '$102compare_op.2'}), (104, {'pred': '$102compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={106: (), 154: ()})\n", - "2024-09-12 10:50:49,814 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=106 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((106, {'res': '$lo106.0'}), (108, {'res': '$hi108.1'}), (110, {'lhs': '$lo106.0', 'rhs': '$hi108.1', 'res': '$110binary_add.2'}), (112, {'res': '$const112.3'}), (114, {'lhs': '$110binary_add.2', 'rhs': '$const112.3', 'res': '$114binary_rshift.4'}), (116, {'value': '$114binary_rshift.4'}), (118, {'res': '$118load_deref.5'}), (120, {'res': '$a120.6'}), (122, {'res': '$mid122.7'}), (124, {'index': '$mid122.7', 'target': '$a120.6', 'res': '$124binary_subscr.8'}), (126, {'res': '$v126.9'}), (128, {'func': '$118load_deref.5', 'args': ['$124binary_subscr.8', '$v126.9'], 'res': '$128call_function.10'}), (130, {'pred': '$128call_function.10'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={132: (), 142: ()})\n", - "2024-09-12 10:50:49,815 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=132 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((132, {'res': '$mid132.0'}), (134, {'res': '$const134.1'}), (136, {'lhs': '$mid132.0', 'rhs': '$const134.1', 'res': '$136binary_add.2'}), (138, {'value': '$136binary_add.2'}), (140, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-09-12 10:50:49,815 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=142 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((142, {'res': '$mid142.0'}), (144, {'value': '$mid142.0'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={146: ()})\n", - "2024-09-12 10:50:49,815 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=146 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((146, {'res': '$hi146.0'}), (148, {'res': '$lo148.1'}), (150, {'lhs': '$hi146.0', 'rhs': '$lo148.1', 'res': '$150compare_op.2'}), (152, {'pred': '$150compare_op.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={154: (), 106: ()})\n", - "2024-09-12 10:50:49,816 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=154 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((154, {'res': '$lo154.0'}), (156, {'retval': '$lo154.0', 'castval': '$156return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:49,820 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " v_last = arg(2, name=v_last) ['v_last']\n", - " lo = arg(3, name=lo) ['lo']\n", - " hi = arg(4, name=hi) ['hi']\n", - " n = arg(5, name=n) ['n']\n", - " $2load_global.0 = global(np: ) ['$2load_global.0']\n", - " $4load_method.1 = getattr(value=$2load_global.0, attr=isnan) ['$2load_global.0', '$4load_method.1']\n", - " $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$4load_method.1', '$8call_method.3', 'v']\n", - " bool10 = global(bool: ) ['bool10']\n", - " $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None) ['$10pred', '$8call_method.3', 'bool10']\n", - " branch $10pred, 12, 60 ['$10pred']\n", - "label 12:\n", - " $12load_global.0 = global(range: ) ['$12load_global.0']\n", - " $const16.2 = const(int, 0) ['$const16.2']\n", - " $const18.3 = const(int, -1) ['$const18.3']\n", - " $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None) ['$12load_global.0', '$20call_function.4', '$const16.2', '$const18.3', 'n']\n", - " $22get_iter.5 = getiter(value=$20call_function.4) ['$20call_function.4', '$22get_iter.5']\n", - " $phi24.0 = $22get_iter.5 ['$22get_iter.5', '$phi24.0']\n", - " jump 24 []\n", - "label 24:\n", - " $24for_iter.1 = iternext(value=$phi24.0) ['$24for_iter.1', '$phi24.0']\n", - " $24for_iter.2 = pair_first(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.2']\n", - " $24for_iter.3 = pair_second(value=$24for_iter.1) ['$24for_iter.1', '$24for_iter.3']\n", - " $phi26.1 = $24for_iter.2 ['$24for_iter.2', '$phi26.1']\n", - " branch $24for_iter.3, 26, 56 ['$24for_iter.3']\n", - "label 26:\n", - " i = $phi26.1 ['$phi26.1', 'i']\n", - " $28load_global.2 = global(np: ) ['$28load_global.2']\n", - " $30load_method.3 = getattr(value=$28load_global.2, attr=isnan) ['$28load_global.2', '$30load_method.3']\n", - " $const36.6 = const(int, 1) ['$const36.6']\n", - " $38binary_subtract.7 = i - $const36.6 ['$38binary_subtract.7', '$const36.6', 'i']\n", - " $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=) ['$38binary_subtract.7', '$40binary_subscr.8', 'a']\n", - " $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None) ['$30load_method.3', '$40binary_subscr.8', '$42call_method.9']\n", - " bool44 = global(bool: ) ['bool44']\n", - " $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None) ['$42call_method.9', '$44pred', 'bool44']\n", - " branch $44pred, 54, 46 ['$44pred']\n", - "label 46:\n", - " $52return_value.2 = cast(value=i) ['$52return_value.2', 'i']\n", - " return $52return_value.2 ['$52return_value.2']\n", - "label 54:\n", - " jump 24 []\n", - "label 56:\n", - " $const56.0 = const(int, 0) ['$const56.0']\n", - " $58return_value.1 = cast(value=$const56.0) ['$58return_value.1', '$const56.0']\n", - " return $58return_value.1 ['$58return_value.1']\n", - "label 60:\n", - " $64compare_op.2 = v_last < v ['$64compare_op.2', 'v', 'v_last']\n", - " bool66 = global(bool: ) ['bool66']\n", - " $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None) ['$64compare_op.2', '$66pred', 'bool66']\n", - " branch $66pred, 68, 74 ['$66pred']\n", - "label 68:\n", - " hi = n ['hi', 'n']\n", - " jump 98 []\n", - "label 74:\n", - " lo = const(int, 0) ['lo']\n", - " $82compare_op.3 = hi < n ['$82compare_op.3', 'hi', 'n']\n", - " bool84 = global(bool: ) ['bool84']\n", - " $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None) ['$82compare_op.3', '$84pred', 'bool84']\n", - " branch $84pred, 86, 94 ['$84pred']\n", - "label 86:\n", - " $const88.1 = const(int, 1) ['$const88.1']\n", - " $90binary_add.2 = hi + $const88.1 ['$90binary_add.2', '$const88.1', 'hi']\n", - " $phi96.0 = $90binary_add.2 ['$90binary_add.2', '$phi96.0']\n", - " jump 96 []\n", - "label 94:\n", - " $phi96.0 = n ['$phi96.0', 'n']\n", - " jump 96 []\n", - "label 96:\n", - " hi = $phi96.0 ['$phi96.0', 'hi']\n", - " jump 98 []\n", - "label 98:\n", - " $102compare_op.2 = hi > lo ['$102compare_op.2', 'hi', 'lo']\n", - " bool104 = global(bool: ) ['bool104']\n", - " $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$102compare_op.2', '$104pred', 'bool104']\n", - " branch $104pred, 106, 154 ['$104pred']\n", - "label 106:\n", - " $110binary_add.2 = lo + hi ['$110binary_add.2', 'hi', 'lo']\n", - " $const112.3 = const(int, 1) ['$const112.3']\n", - " mid = $110binary_add.2 >> $const112.3 ['$110binary_add.2', '$const112.3', 'mid']\n", - " $118load_deref.5 = freevar(func: ) ['$118load_deref.5']\n", - " $124binary_subscr.8 = getitem(value=a, index=mid, fn=) ['$124binary_subscr.8', 'a', 'mid']\n", - " $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None) ['$118load_deref.5', '$124binary_subscr.8', '$128call_function.10', 'v']\n", - " bool130 = global(bool: ) ['bool130']\n", - " $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None) ['$128call_function.10', '$130pred', 'bool130']\n", - " branch $130pred, 132, 142 ['$130pred']\n", - "label 132:\n", - " $const134.1 = const(int, 1) ['$const134.1']\n", - " lo = mid + $const134.1 ['$const134.1', 'lo', 'mid']\n", - " jump 146 []\n", - "label 142:\n", - " hi = mid ['hi', 'mid']\n", - " jump 146 []\n", - "label 146:\n", - " $150compare_op.2 = hi > lo ['$150compare_op.2', 'hi', 'lo']\n", - " bool152 = global(bool: ) ['bool152']\n", - " $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None) ['$150compare_op.2', '$152pred', 'bool152']\n", - " branch $152pred, 106, 154 ['$152pred']\n", - "label 154:\n", - " $156return_value.1 = cast(value=lo) ['$156return_value.1', 'lo']\n", - " return $156return_value.1 ['$156return_value.1']\n", - "\n", - "2024-09-12 10:50:49,846 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:49,847 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,847 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:49,847 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:49,848 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:49,848 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:49,849 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:49,849 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:49,849 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:49,850 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:49,850 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,850 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:49,851 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,851 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:49,851 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 12\n", - "2024-09-12 10:50:49,852 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,852 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:49,853 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:49,853 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:49,853 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,854 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:49,854 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:49,854 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:49,855 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 24\n", - "2024-09-12 10:50:49,855 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,856 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:49,856 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:49,856 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:49,857 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:49,857 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:49,857 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 26\n", - "2024-09-12 10:50:49,858 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,858 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:49,858 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:49,859 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:49,859 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:49,860 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:49,860 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:49,860 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,861 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:49,861 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,861 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:49,862 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 46\n", - "2024-09-12 10:50:49,862 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,862 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:49,863 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:49,863 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-09-12 10:50:49,863 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,864 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:49,864 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-09-12 10:50:49,865 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,865 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:49,865 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:49,866 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:49,866 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 60\n", - "2024-09-12 10:50:49,866 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,867 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:49,867 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:49,867 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,868 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:49,868 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 68\n", - "2024-09-12 10:50:49,869 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,869 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:49,869 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:49,870 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-09-12 10:50:49,870 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,871 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-09-12 10:50:49,871 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:49,871 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:49,872 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,872 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:49,873 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 86\n", - "2024-09-12 10:50:49,873 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,873 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:49,874 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:49,874 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:49,874 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:49,875 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 94\n", - "2024-09-12 10:50:49,875 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,876 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:49,876 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:49,876 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 96\n", - "2024-09-12 10:50:49,877 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,877 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:49,877 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:49,878 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 98\n", - "2024-09-12 10:50:49,878 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,878 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:49,879 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:49,879 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,880 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:49,880 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 106\n", - "2024-09-12 10:50:49,880 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,881 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:49,881 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:49,881 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:49,882 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:49,882 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:49,883 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,883 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:49,883 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,884 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:49,884 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 132\n", - "2024-09-12 10:50:49,884 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,885 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:49,885 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-09-12 10:50:49,890 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:49,890 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 142\n", - "2024-09-12 10:50:49,891 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,891 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:49,891 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:49,892 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 146\n", - "2024-09-12 10:50:49,892 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,893 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:49,893 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:49,893 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,894 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:49,894 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 154\n", - "2024-09-12 10:50:49,894 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,895 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:49,895 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:49,896 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$102compare_op.2': [],\n", - " '$104pred': [],\n", - " '$10pred': [],\n", - " '$110binary_add.2': [],\n", - " '$118load_deref.5': [],\n", - " '$124binary_subscr.8': [],\n", - " '$128call_function.10': [],\n", - " '$12load_global.0': [],\n", - " '$130pred': [],\n", - " '$150compare_op.2': [],\n", - " '$152pred': [],\n", - " '$156return_value.1': [],\n", - " '$20call_function.4': [],\n", - " '$22get_iter.5': [],\n", - " '$24for_iter.1': [],\n", - " '$24for_iter.2': [],\n", - " '$24for_iter.3': [],\n", - " '$28load_global.2': [],\n", - " '$2load_global.0': [],\n", - " '$30load_method.3': [],\n", - " '$38binary_subtract.7': [],\n", - " '$40binary_subscr.8': [],\n", - " '$42call_method.9': [],\n", - " '$44pred': [],\n", - " '$4load_method.1': [],\n", - " '$52return_value.2': [],\n", - " '$58return_value.1': [],\n", - " '$64compare_op.2': [],\n", - " '$66pred': [],\n", - " '$82compare_op.3': [],\n", - " '$84pred': [],\n", - " '$8call_method.3': [],\n", - " '$90binary_add.2': [],\n", - " '$const112.3': [],\n", - " '$const134.1': [],\n", - " '$const16.2': [],\n", - " '$const18.3': [],\n", - " '$const36.6': [],\n", - " '$const56.0': [],\n", - " '$const88.1': [],\n", - " '$phi24.0': [],\n", - " '$phi26.1': [],\n", - " '$phi96.0': [,\n", - " ],\n", - " 'a': [],\n", - " 'bool10': [],\n", - " 'bool104': [],\n", - " 'bool130': [],\n", - " 'bool152': [],\n", - " 'bool44': [],\n", - " 'bool66': [],\n", - " 'bool84': [],\n", - " 'hi': [,\n", - " ,\n", - " ,\n", - " ],\n", - " 'i': [],\n", - " 'lo': [,\n", - " ,\n", - " ],\n", - " 'mid': [],\n", - " 'n': [],\n", - " 'v': [],\n", - " 'v_last': []})\n", - "2024-09-12 10:50:49,897 - numba.core.ssa - DEBUG - SSA violators {'lo', 'hi', '$phi96.0'}\n", - "2024-09-12 10:50:49,897 - numba.core.ssa - DEBUG - Fix SSA violator on var lo\n", - "2024-09-12 10:50:49,897 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:49,898 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,898 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:49,898 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:49,899 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:49,899 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:49,899 - numba.core.ssa - DEBUG - first assign: lo\n", - "2024-09-12 10:50:49,900 - numba.core.ssa - DEBUG - replaced with: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:49,900 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:49,901 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:49,901 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:49,901 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:49,902 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,902 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:49,903 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,903 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:49,903 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:49,904 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,904 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:49,904 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:49,905 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:49,905 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,906 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:49,906 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:49,906 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:49,907 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:49,907 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,907 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:49,908 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:49,908 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:49,908 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:49,909 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:49,909 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:49,910 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,910 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:49,910 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:49,911 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:49,911 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:49,911 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:49,912 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:49,912 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,912 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:49,913 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,913 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:49,914 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:49,914 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,914 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:49,915 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:49,915 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:49,915 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,916 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:49,916 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:49,916 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,917 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:49,917 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:49,917 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:49,918 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:49,918 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,919 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:49,919 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:49,919 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,920 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:49,920 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:49,920 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,921 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:49,921 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:49,922 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:49,922 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,922 - numba.core.ssa - DEBUG - on stmt: lo = const(int, 0)\n", - "2024-09-12 10:50:49,923 - numba.core.ssa - DEBUG - replaced with: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:49,923 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:49,923 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:49,924 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,924 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:49,925 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:49,925 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,925 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:49,926 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:49,926 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:49,927 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:49,927 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:49,927 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,928 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:49,928 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:49,928 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:49,929 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,929 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:49,929 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:49,930 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:49,930 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,931 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:49,931 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:49,931 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,932 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:49,932 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:49,932 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,933 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:49,933 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:49,934 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:49,934 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:49,934 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:49,935 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,935 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:49,936 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,936 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:49,936 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:49,937 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,937 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:49,937 - numba.core.ssa - DEBUG - on stmt: lo = mid + $const134.1\n", - "2024-09-12 10:50:49,938 - numba.core.ssa - DEBUG - replaced with: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:49,938 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:49,938 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:49,939 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,939 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:49,940 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:49,940 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:49,940 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,941 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:49,941 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:49,941 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,942 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:49,942 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:49,942 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,943 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:49,943 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:49,944 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 74: [],\n", - " 132: []})\n", - "2024-09-12 10:50:49,944 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:49,944 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,945 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:49,945 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:49,945 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:49,946 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:49,946 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:49,947 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:49,947 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:49,947 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:49,948 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,948 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:49,948 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,949 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:49,949 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:49,949 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,950 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:49,950 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:49,951 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:49,951 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,951 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:49,952 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:49,952 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:49,953 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:49,953 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,953 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:49,954 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:49,954 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:49,954 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:49,955 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:49,955 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:49,955 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,956 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:49,956 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:49,956 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:49,957 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:49,957 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:49,958 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:49,958 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,958 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:49,977 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,985 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:49,985 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:49,986 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,986 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:49,986 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:49,987 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:49,987 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,987 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:49,988 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:49,988 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,988 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:49,989 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:49,989 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:49,989 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:49,990 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,990 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:49,991 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:49,991 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,991 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:49,992 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:49,992 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,992 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:49,993 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:49,993 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:49,994 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,994 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:49,994 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:49,995 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:49,995 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:49,996 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:49,996 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:49,996 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,997 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:49,997 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:49,997 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:49,998 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:49,998 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:49,999 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:49,999 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:49,999 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:50,000 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:50,000 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,000 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:50,001 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:50,006 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:50,006 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,007 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:50,007 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$102compare_op.2 = hi > lo\n", - "2024-09-12 10:50:50,007 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-09-12 10:50:50,008 - numba.core.ssa - DEBUG - insert phi node lo.3 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-09-12 10:50:50,008 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:50,009 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:50,009 - numba.core.ssa - DEBUG - idom 74 from label 96\n", - "2024-09-12 10:50:50,009 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:50,010 - numba.core.ssa - DEBUG - incoming_def lo.1 = const(int, 0)\n", - "2024-09-12 10:50:50,010 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-09-12 10:50:50,010 - numba.core.ssa - DEBUG - find_def_from_top label 68\n", - "2024-09-12 10:50:50,011 - numba.core.ssa - DEBUG - idom 60 from label 68\n", - "2024-09-12 10:50:50,011 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:50,011 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:50,012 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-09-12 10:50:50,012 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:50,012 - numba.core.ssa - DEBUG - incoming_def lo = arg(3, name=lo)\n", - "2024-09-12 10:50:50,013 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:50,013 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:50,014 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,014 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:50,015 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:50,015 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,015 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:50,016 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$110binary_add.2 = lo + hi\n", - "2024-09-12 10:50:50,016 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-09-12 10:50:50,016 - numba.core.ssa - DEBUG - insert phi node lo.4 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-09-12 10:50:50,017 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-09-12 10:50:50,017 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:50,018 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-09-12 10:50:50,018 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-09-12 10:50:50,018 - numba.core.ssa - DEBUG - insert phi node lo.5 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-09-12 10:50:50,019 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-09-12 10:50:50,019 - numba.core.ssa - DEBUG - incoming_def lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:50,020 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-09-12 10:50:50,020 - numba.core.ssa - DEBUG - find_def_from_top label 142\n", - "2024-09-12 10:50:50,020 - numba.core.ssa - DEBUG - idom 106 from label 142\n", - "2024-09-12 10:50:50,021 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-09-12 10:50:50,021 - numba.core.ssa - DEBUG - incoming_def lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-09-12 10:50:50,021 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:50,022 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:50,022 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:50,023 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:50,023 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:50,028 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:50,028 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,029 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:50,029 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,029 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:50,030 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:50,030 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,030 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:50,031 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:50,031 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,032 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:50,032 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,032 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:50,033 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,033 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:50,034 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,034 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:50,036 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$150compare_op.2 = hi > lo\n", - "2024-09-12 10:50:50,036 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:50,037 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:50,037 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,037 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:50,038 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:50,038 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,039 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:50,039 - numba.core.ssa - DEBUG - find_def var='lo' stmt=$156return_value.1 = cast(value=lo)\n", - "2024-09-12 10:50:50,039 - numba.core.ssa - DEBUG - find_def_from_top label 154\n", - "2024-09-12 10:50:50,040 - numba.core.ssa - DEBUG - insert phi node lo.6 = phi(incoming_values=[], incoming_blocks=[]) at 154\n", - "2024-09-12 10:50:50,040 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-09-12 10:50:50,040 - numba.core.ssa - DEBUG - incoming_def lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:50,041 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-09-12 10:50:50,041 - numba.core.ssa - DEBUG - incoming_def lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:50,042 - numba.core.ssa - DEBUG - replaced with: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:50,042 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:50,042 - numba.core.ssa - DEBUG - Fix SSA violator on var hi\n", - "2024-09-12 10:50:50,043 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:50,043 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,044 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:50,044 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:50,044 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:50,045 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:50,045 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:50,045 - numba.core.ssa - DEBUG - first assign: hi\n", - "2024-09-12 10:50:50,046 - numba.core.ssa - DEBUG - replaced with: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:50,046 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:50,047 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:50,047 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:50,047 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,048 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:50,048 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,048 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:50,049 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:50,049 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,050 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:50,050 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:50,050 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:50,051 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,051 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:50,051 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:50,052 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:50,052 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:50,052 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,053 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:50,053 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:50,054 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:50,054 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:50,054 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:50,055 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:50,055 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,055 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:50,056 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:50,056 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:50,057 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:50,057 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:50,057 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:50,058 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,058 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:50,058 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,059 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:50,059 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:50,060 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,060 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:50,060 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:50,061 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:50,061 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,061 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:50,062 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:50,062 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,062 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:50,063 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:50,063 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:50,063 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:50,064 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,064 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:50,065 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:50,065 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,065 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:50,066 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:50,066 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,066 - numba.core.ssa - DEBUG - on stmt: hi = n\n", - "2024-09-12 10:50:50,067 - numba.core.ssa - DEBUG - replaced with: hi.1 = n\n", - "2024-09-12 10:50:50,067 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:50,067 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:50,068 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,068 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:50,068 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:50,069 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:50,069 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,070 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:50,070 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:50,070 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,071 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:50,071 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:50,071 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:50,072 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:50,072 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:50,073 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,073 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:50,073 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:50,074 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:50,074 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,075 - numba.core.ssa - DEBUG - on stmt: hi = $phi96.0\n", - "2024-09-12 10:50:50,075 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0\n", - "2024-09-12 10:50:50,075 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:50,076 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:50,076 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,076 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:50,077 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:50,077 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:50,077 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,078 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:50,078 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:50,079 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,079 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,079 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:50,079 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:50,080 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:50,080 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:50,081 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:50,081 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,081 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:50,082 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,082 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:50,082 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:50,083 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,083 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:50,084 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:50,084 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,084 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:50,085 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,085 - numba.core.ssa - DEBUG - on stmt: hi = mid\n", - "2024-09-12 10:50:50,085 - numba.core.ssa - DEBUG - replaced with: hi.3 = mid\n", - "2024-09-12 10:50:50,086 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,086 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:50,087 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,087 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:50,087 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:50,088 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:50,088 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,089 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:50,089 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:50,089 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,090 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,090 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:50,090 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:50,091 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {0: [],\n", - " 68: [],\n", - " 96: [],\n", - " 142: []})\n", - "2024-09-12 10:50:50,091 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:50,092 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,092 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:50,092 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:50,093 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:50,093 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:50,093 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:50,094 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:50,094 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:50,095 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:50,095 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,095 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:50,096 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,096 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:50,097 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:50,097 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,097 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:50,098 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:50,098 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:50,098 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,099 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:50,099 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:50,117 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:50,118 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:50,119 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,119 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:50,119 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:50,120 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:50,120 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:50,120 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:50,121 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:50,121 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,121 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:50,122 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:50,122 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:50,122 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:50,123 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:50,123 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:50,124 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,124 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:50,124 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,125 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:50,125 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:50,126 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,126 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:50,126 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:50,127 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:50,127 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,127 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:50,128 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:50,128 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,129 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:50,129 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:50,129 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:50,130 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:50,130 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,130 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:50,131 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:50,131 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,132 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:50,132 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:50,132 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,133 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-09-12 10:50:50,133 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:50,133 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:50,134 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,134 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:50,134 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:50,135 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$82compare_op.3 = hi < n\n", - "2024-09-12 10:50:50,135 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-09-12 10:50:50,136 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-09-12 10:50:50,136 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:50,136 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:50,137 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-09-12 10:50:50,137 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:50,137 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:50,138 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,138 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:50,138 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:50,139 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,139 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:50,139 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:50,140 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:50,140 - numba.core.ssa - DEBUG - find_def_from_top label 86\n", - "2024-09-12 10:50:50,141 - numba.core.ssa - DEBUG - idom 74 from label 86\n", - "2024-09-12 10:50:50,141 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:50,141 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-09-12 10:50:50,142 - numba.core.ssa - DEBUG - idom 60 from label 74\n", - "2024-09-12 10:50:50,142 - numba.core.ssa - DEBUG - find_def_from_bottom label 60\n", - "2024-09-12 10:50:50,142 - numba.core.ssa - DEBUG - find_def_from_top label 60\n", - "2024-09-12 10:50:50,143 - numba.core.ssa - DEBUG - idom 0 from label 60\n", - "2024-09-12 10:50:50,143 - numba.core.ssa - DEBUG - find_def_from_bottom label 0\n", - "2024-09-12 10:50:50,143 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:50,144 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:50,144 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:50,144 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,145 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:50,145 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:50,145 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:50,146 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,146 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-09-12 10:50:50,147 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:50,147 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:50,147 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,148 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:50,148 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:50,148 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$102compare_op.2 = hi > lo.3\n", - "2024-09-12 10:50:50,149 - numba.core.ssa - DEBUG - find_def_from_top label 98\n", - "2024-09-12 10:50:50,149 - numba.core.ssa - DEBUG - insert phi node hi.4 = phi(incoming_values=[], incoming_blocks=[]) at 98\n", - "2024-09-12 10:50:50,150 - numba.core.ssa - DEBUG - find_def_from_bottom label 96\n", - "2024-09-12 10:50:50,150 - numba.core.ssa - DEBUG - incoming_def hi.2 = $phi96.0\n", - "2024-09-12 10:50:50,150 - numba.core.ssa - DEBUG - find_def_from_bottom label 68\n", - "2024-09-12 10:50:50,151 - numba.core.ssa - DEBUG - incoming_def hi.1 = n\n", - "2024-09-12 10:50:50,151 - numba.core.ssa - DEBUG - replaced with: $102compare_op.2 = hi.4 > lo.3\n", - "2024-09-12 10:50:50,151 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:50,152 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,152 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:50,152 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:50,153 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,153 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,154 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:50,154 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$110binary_add.2 = lo.4 + hi\n", - "2024-09-12 10:50:50,154 - numba.core.ssa - DEBUG - find_def_from_top label 106\n", - "2024-09-12 10:50:50,155 - numba.core.ssa - DEBUG - insert phi node hi.5 = phi(incoming_values=[], incoming_blocks=[]) at 106\n", - "2024-09-12 10:50:50,155 - numba.core.ssa - DEBUG - find_def_from_bottom label 98\n", - "2024-09-12 10:50:50,155 - numba.core.ssa - DEBUG - incoming_def hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:50,156 - numba.core.ssa - DEBUG - find_def_from_bottom label 146\n", - "2024-09-12 10:50:50,156 - numba.core.ssa - DEBUG - find_def_from_top label 146\n", - "2024-09-12 10:50:50,156 - numba.core.ssa - DEBUG - insert phi node hi.6 = phi(incoming_values=[], incoming_blocks=[]) at 146\n", - "2024-09-12 10:50:50,157 - numba.core.ssa - DEBUG - find_def_from_bottom label 132\n", - "2024-09-12 10:50:50,157 - numba.core.ssa - DEBUG - find_def_from_top label 132\n", - "2024-09-12 10:50:50,157 - numba.core.ssa - DEBUG - idom 106 from label 132\n", - "2024-09-12 10:50:50,158 - numba.core.ssa - DEBUG - find_def_from_bottom label 106\n", - "2024-09-12 10:50:50,158 - numba.core.ssa - DEBUG - incoming_def hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715)], incoming_blocks=[98])\n", - "2024-09-12 10:50:50,159 - numba.core.ssa - DEBUG - find_def_from_bottom label 142\n", - "2024-09-12 10:50:50,159 - numba.core.ssa - DEBUG - incoming_def hi.3 = mid\n", - "2024-09-12 10:50:50,159 - numba.core.ssa - DEBUG - incoming_def hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:50,160 - numba.core.ssa - DEBUG - replaced with: $110binary_add.2 = lo.4 + hi.5\n", - "2024-09-12 10:50:50,160 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:50,161 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:50,161 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:50,161 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:50,162 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,162 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:50,163 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,163 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:50,163 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:50,164 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,164 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:50,164 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:50,165 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,165 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:50,166 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,166 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-09-12 10:50:50,166 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,167 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:50,167 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,167 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:50,168 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:50,168 - numba.core.ssa - DEBUG - find_def var='hi' stmt=$150compare_op.2 = hi > lo.5\n", - "2024-09-12 10:50:50,169 - numba.core.ssa - DEBUG - replaced with: $150compare_op.2 = hi.6 > lo.5\n", - "2024-09-12 10:50:50,169 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:50,169 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,170 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:50,170 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:50,171 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,171 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,171 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:50,172 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:50,172 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi96.0\n", - "2024-09-12 10:50:50,173 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:50,173 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,173 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:50,174 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:50,174 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:50,174 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:50,175 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:50,175 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:50,176 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:50,176 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:50,176 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,177 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:50,177 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,177 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:50,178 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:50,179 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,179 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:50,179 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:50,180 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:50,180 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,180 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:50,181 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:50,181 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:50,182 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:50,182 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,182 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:50,183 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:50,183 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:50,184 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:50,184 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:50,184 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:50,185 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,185 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:50,185 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:50,186 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:50,186 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:50,186 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:50,187 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:50,187 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,188 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:50,188 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,188 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:50,189 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:50,189 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,189 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:50,190 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:50,190 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:50,191 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,191 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:50,191 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:50,192 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,192 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:50,192 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:50,193 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:50,193 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:50,193 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,194 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:50,194 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:50,216 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,216 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:50,217 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:50,217 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,217 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-09-12 10:50:50,218 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:50,218 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:50,218 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,219 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:50,219 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:50,220 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:50,220 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,220 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:50,221 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:50,221 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,222 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:50,222 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:50,222 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:50,223 - numba.core.ssa - DEBUG - first assign: $phi96.0\n", - "2024-09-12 10:50:50,223 - numba.core.ssa - DEBUG - replaced with: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:50,224 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:50,224 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:50,224 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,225 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = n\n", - "2024-09-12 10:50:50,225 - numba.core.ssa - DEBUG - replaced with: $phi96.0.1 = n\n", - "2024-09-12 10:50:50,225 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:50,226 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:50,226 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,227 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-09-12 10:50:50,227 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:50,227 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:50,228 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,228 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:50,228 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:50,229 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-09-12 10:50:50,229 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:50,230 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,230 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:50,230 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:50,231 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,231 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,231 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,232 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-09-12 10:50:50,232 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:50,233 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:50,233 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:50,233 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:50,234 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,234 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:50,234 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,235 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:50,235 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:50,236 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,236 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:50,236 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:50,237 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,237 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:50,238 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,238 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-09-12 10:50:50,238 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,239 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:50,239 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,239 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:50,240 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:50,240 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-09-12 10:50:50,241 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:50,241 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,241 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:50,242 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:50,242 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,243 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,243 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:50,243 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:50,244 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {86: [],\n", - " 94: []})\n", - "2024-09-12 10:50:50,244 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:50,245 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,245 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:50,245 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:50,246 - numba.core.ssa - DEBUG - on stmt: v_last = arg(2, name=v_last)\n", - "2024-09-12 10:50:50,246 - numba.core.ssa - DEBUG - on stmt: lo = arg(3, name=lo)\n", - "2024-09-12 10:50:50,246 - numba.core.ssa - DEBUG - on stmt: hi = arg(4, name=hi)\n", - "2024-09-12 10:50:50,247 - numba.core.ssa - DEBUG - on stmt: n = arg(5, name=n)\n", - "2024-09-12 10:50:50,247 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(np: )\n", - "2024-09-12 10:50:50,248 - numba.core.ssa - DEBUG - on stmt: $4load_method.1 = getattr(value=$2load_global.0, attr=isnan)\n", - "2024-09-12 10:50:50,248 - numba.core.ssa - DEBUG - on stmt: $8call_method.3 = call $4load_method.1(v, func=$4load_method.1, args=[Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,248 - numba.core.ssa - DEBUG - on stmt: bool10 = global(bool: )\n", - "2024-09-12 10:50:50,249 - numba.core.ssa - DEBUG - on stmt: $10pred = call bool10($8call_method.3, func=bool10, args=(Var($8call_method.3, arraymath.py:3701),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,249 - numba.core.ssa - DEBUG - on stmt: branch $10pred, 12, 60\n", - "2024-09-12 10:50:50,250 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 12\n", - "2024-09-12 10:50:50,250 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,250 - numba.core.ssa - DEBUG - on stmt: $12load_global.0 = global(range: )\n", - "2024-09-12 10:50:50,251 - numba.core.ssa - DEBUG - on stmt: $const16.2 = const(int, 0)\n", - "2024-09-12 10:50:50,251 - numba.core.ssa - DEBUG - on stmt: $const18.3 = const(int, -1)\n", - "2024-09-12 10:50:50,251 - numba.core.ssa - DEBUG - on stmt: $20call_function.4 = call $12load_global.0(n, $const16.2, $const18.3, func=$12load_global.0, args=[Var(n, arraymath.py:3678), Var($const16.2, arraymath.py:3704), Var($const18.3, arraymath.py:3704)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,252 - numba.core.ssa - DEBUG - on stmt: $22get_iter.5 = getiter(value=$20call_function.4)\n", - "2024-09-12 10:50:50,252 - numba.core.ssa - DEBUG - on stmt: $phi24.0 = $22get_iter.5\n", - "2024-09-12 10:50:50,252 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:50,253 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 24\n", - "2024-09-12 10:50:50,253 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,253 - numba.core.ssa - DEBUG - on stmt: $24for_iter.1 = iternext(value=$phi24.0)\n", - "2024-09-12 10:50:50,254 - numba.core.ssa - DEBUG - on stmt: $24for_iter.2 = pair_first(value=$24for_iter.1)\n", - "2024-09-12 10:50:50,254 - numba.core.ssa - DEBUG - on stmt: $24for_iter.3 = pair_second(value=$24for_iter.1)\n", - "2024-09-12 10:50:50,255 - numba.core.ssa - DEBUG - on stmt: $phi26.1 = $24for_iter.2\n", - "2024-09-12 10:50:50,255 - numba.core.ssa - DEBUG - on stmt: branch $24for_iter.3, 26, 56\n", - "2024-09-12 10:50:50,255 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 26\n", - "2024-09-12 10:50:50,256 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,256 - numba.core.ssa - DEBUG - on stmt: i = $phi26.1\n", - "2024-09-12 10:50:50,256 - numba.core.ssa - DEBUG - on stmt: $28load_global.2 = global(np: )\n", - "2024-09-12 10:50:50,257 - numba.core.ssa - DEBUG - on stmt: $30load_method.3 = getattr(value=$28load_global.2, attr=isnan)\n", - "2024-09-12 10:50:50,257 - numba.core.ssa - DEBUG - on stmt: $const36.6 = const(int, 1)\n", - "2024-09-12 10:50:50,257 - numba.core.ssa - DEBUG - on stmt: $38binary_subtract.7 = i - $const36.6\n", - "2024-09-12 10:50:50,258 - numba.core.ssa - DEBUG - on stmt: $40binary_subscr.8 = getitem(value=a, index=$38binary_subtract.7, fn=)\n", - "2024-09-12 10:50:50,258 - numba.core.ssa - DEBUG - on stmt: $42call_method.9 = call $30load_method.3($40binary_subscr.8, func=$30load_method.3, args=[Var($40binary_subscr.8, arraymath.py:3705)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,259 - numba.core.ssa - DEBUG - on stmt: bool44 = global(bool: )\n", - "2024-09-12 10:50:50,259 - numba.core.ssa - DEBUG - on stmt: $44pred = call bool44($42call_method.9, func=bool44, args=(Var($42call_method.9, arraymath.py:3705),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,259 - numba.core.ssa - DEBUG - on stmt: branch $44pred, 54, 46\n", - "2024-09-12 10:50:50,260 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 46\n", - "2024-09-12 10:50:50,260 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,261 - numba.core.ssa - DEBUG - on stmt: $52return_value.2 = cast(value=i)\n", - "2024-09-12 10:50:50,261 - numba.core.ssa - DEBUG - on stmt: return $52return_value.2\n", - "2024-09-12 10:50:50,261 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:50,262 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,262 - numba.core.ssa - DEBUG - on stmt: jump 24\n", - "2024-09-12 10:50:50,262 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:50,263 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,263 - numba.core.ssa - DEBUG - on stmt: $const56.0 = const(int, 0)\n", - "2024-09-12 10:50:50,263 - numba.core.ssa - DEBUG - on stmt: $58return_value.1 = cast(value=$const56.0)\n", - "2024-09-12 10:50:50,264 - numba.core.ssa - DEBUG - on stmt: return $58return_value.1\n", - "2024-09-12 10:50:50,264 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 60\n", - "2024-09-12 10:50:50,265 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,265 - numba.core.ssa - DEBUG - on stmt: $64compare_op.2 = v_last < v\n", - "2024-09-12 10:50:50,265 - numba.core.ssa - DEBUG - on stmt: bool66 = global(bool: )\n", - "2024-09-12 10:50:50,266 - numba.core.ssa - DEBUG - on stmt: $66pred = call bool66($64compare_op.2, func=bool66, args=(Var($64compare_op.2, arraymath.py:3709),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,266 - numba.core.ssa - DEBUG - on stmt: branch $66pred, 68, 74\n", - "2024-09-12 10:50:50,266 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 68\n", - "2024-09-12 10:50:50,267 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,279 - numba.core.ssa - DEBUG - on stmt: hi.1 = n\n", - "2024-09-12 10:50:50,281 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:50,282 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:50,282 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,283 - numba.core.ssa - DEBUG - on stmt: lo.1 = const(int, 0)\n", - "2024-09-12 10:50:50,283 - numba.core.ssa - DEBUG - on stmt: $82compare_op.3 = hi < n\n", - "2024-09-12 10:50:50,283 - numba.core.ssa - DEBUG - on stmt: bool84 = global(bool: )\n", - "2024-09-12 10:50:50,284 - numba.core.ssa - DEBUG - on stmt: $84pred = call bool84($82compare_op.3, func=bool84, args=(Var($82compare_op.3, arraymath.py:3713),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,284 - numba.core.ssa - DEBUG - on stmt: branch $84pred, 86, 94\n", - "2024-09-12 10:50:50,284 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 86\n", - "2024-09-12 10:50:50,285 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,285 - numba.core.ssa - DEBUG - on stmt: $const88.1 = const(int, 1)\n", - "2024-09-12 10:50:50,285 - numba.core.ssa - DEBUG - on stmt: $90binary_add.2 = hi + $const88.1\n", - "2024-09-12 10:50:50,286 - numba.core.ssa - DEBUG - on stmt: $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:50,286 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:50,287 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 94\n", - "2024-09-12 10:50:50,287 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,287 - numba.core.ssa - DEBUG - on stmt: $phi96.0.1 = n\n", - "2024-09-12 10:50:50,288 - numba.core.ssa - DEBUG - on stmt: jump 96\n", - "2024-09-12 10:50:50,288 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 96\n", - "2024-09-12 10:50:50,289 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,289 - numba.core.ssa - DEBUG - on stmt: hi.2 = $phi96.0\n", - "2024-09-12 10:50:50,290 - numba.core.ssa - DEBUG - find_def var='$phi96.0' stmt=hi.2 = $phi96.0\n", - "2024-09-12 10:50:50,293 - numba.core.ssa - DEBUG - find_def_from_top label 96\n", - "2024-09-12 10:50:50,293 - numba.core.ssa - DEBUG - insert phi node $phi96.0.2 = phi(incoming_values=[], incoming_blocks=[]) at 96\n", - "2024-09-12 10:50:50,294 - numba.core.ssa - DEBUG - find_def_from_bottom label 94\n", - "2024-09-12 10:50:50,294 - numba.core.ssa - DEBUG - incoming_def $phi96.0.1 = n\n", - "2024-09-12 10:50:50,295 - numba.core.ssa - DEBUG - find_def_from_bottom label 86\n", - "2024-09-12 10:50:50,296 - numba.core.ssa - DEBUG - incoming_def $phi96.0 = $90binary_add.2\n", - "2024-09-12 10:50:50,296 - numba.core.ssa - DEBUG - replaced with: hi.2 = $phi96.0.2\n", - "2024-09-12 10:50:50,297 - numba.core.ssa - DEBUG - on stmt: jump 98\n", - "2024-09-12 10:50:50,297 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 98\n", - "2024-09-12 10:50:50,297 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,298 - numba.core.ssa - DEBUG - on stmt: hi.4 = phi(incoming_values=[Var(hi.2, arraymath.py:3713), Var(hi.1, arraymath.py:3710)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:50,298 - numba.core.ssa - DEBUG - on stmt: lo.3 = phi(incoming_values=[Var(lo.1, arraymath.py:3712), Var(lo, arraymath.py:3678)], incoming_blocks=[96, 68])\n", - "2024-09-12 10:50:50,300 - numba.core.ssa - DEBUG - on stmt: $102compare_op.2 = hi.4 > lo.3\n", - "2024-09-12 10:50:50,300 - numba.core.ssa - DEBUG - on stmt: bool104 = global(bool: )\n", - "2024-09-12 10:50:50,301 - numba.core.ssa - DEBUG - on stmt: $104pred = call bool104($102compare_op.2, func=bool104, args=(Var($102compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,301 - numba.core.ssa - DEBUG - on stmt: branch $104pred, 106, 154\n", - "2024-09-12 10:50:50,302 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 106\n", - "2024-09-12 10:50:50,303 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,303 - numba.core.ssa - DEBUG - on stmt: hi.5 = phi(incoming_values=[Var(hi.4, arraymath.py:3715), Var(hi.6, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,304 - numba.core.ssa - DEBUG - on stmt: lo.4 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,304 - numba.core.ssa - DEBUG - on stmt: $110binary_add.2 = lo.4 + hi.5\n", - "2024-09-12 10:50:50,305 - numba.core.ssa - DEBUG - on stmt: $const112.3 = const(int, 1)\n", - "2024-09-12 10:50:50,305 - numba.core.ssa - DEBUG - on stmt: mid = $110binary_add.2 >> $const112.3\n", - "2024-09-12 10:50:50,306 - numba.core.ssa - DEBUG - on stmt: $118load_deref.5 = freevar(func: )\n", - "2024-09-12 10:50:50,306 - numba.core.ssa - DEBUG - on stmt: $124binary_subscr.8 = getitem(value=a, index=mid, fn=)\n", - "2024-09-12 10:50:50,307 - numba.core.ssa - DEBUG - on stmt: $128call_function.10 = call $118load_deref.5($124binary_subscr.8, v, func=$118load_deref.5, args=[Var($124binary_subscr.8, arraymath.py:3717), Var(v, arraymath.py:3678)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,308 - numba.core.ssa - DEBUG - on stmt: bool130 = global(bool: )\n", - "2024-09-12 10:50:50,309 - numba.core.ssa - DEBUG - on stmt: $130pred = call bool130($128call_function.10, func=bool130, args=(Var($128call_function.10, arraymath.py:3717),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,309 - numba.core.ssa - DEBUG - on stmt: branch $130pred, 132, 142\n", - "2024-09-12 10:50:50,310 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 132\n", - "2024-09-12 10:50:50,310 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,311 - numba.core.ssa - DEBUG - on stmt: $const134.1 = const(int, 1)\n", - "2024-09-12 10:50:50,311 - numba.core.ssa - DEBUG - on stmt: lo.2 = mid + $const134.1\n", - "2024-09-12 10:50:50,312 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,312 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 142\n", - "2024-09-12 10:50:50,313 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,313 - numba.core.ssa - DEBUG - on stmt: hi.3 = mid\n", - "2024-09-12 10:50:50,313 - numba.core.ssa - DEBUG - on stmt: jump 146\n", - "2024-09-12 10:50:50,314 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 146\n", - "2024-09-12 10:50:50,314 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,315 - numba.core.ssa - DEBUG - on stmt: hi.6 = phi(incoming_values=[Var(hi.5, arraymath.py:3716), Var(hi.3, arraymath.py:3722)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:50,315 - numba.core.ssa - DEBUG - on stmt: lo.5 = phi(incoming_values=[Var(lo.2, arraymath.py:3719), Var(lo.4, arraymath.py:3716)], incoming_blocks=[132, 142])\n", - "2024-09-12 10:50:50,317 - numba.core.ssa - DEBUG - on stmt: $150compare_op.2 = hi.6 > lo.5\n", - "2024-09-12 10:50:50,318 - numba.core.ssa - DEBUG - on stmt: bool152 = global(bool: )\n", - "2024-09-12 10:50:50,318 - numba.core.ssa - DEBUG - on stmt: $152pred = call bool152($150compare_op.2, func=bool152, args=(Var($150compare_op.2, arraymath.py:3715),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,319 - numba.core.ssa - DEBUG - on stmt: branch $152pred, 106, 154\n", - "2024-09-12 10:50:50,319 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 154\n", - "2024-09-12 10:50:50,320 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,321 - numba.core.ssa - DEBUG - on stmt: lo.6 = phi(incoming_values=[Var(lo.3, arraymath.py:3715), Var(lo.5, arraymath.py:3716)], incoming_blocks=[98, 146])\n", - "2024-09-12 10:50:50,321 - numba.core.ssa - DEBUG - on stmt: $156return_value.1 = cast(value=lo.6)\n", - "2024-09-12 10:50:50,322 - numba.core.ssa - DEBUG - on stmt: return $156return_value.1\n", - "2024-09-12 10:50:50,504 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=3773)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=3774)\n", - " 4\tLOAD_FAST(arg=0, lineno=3774)\n", - " 6\tCALL_FUNCTION(arg=1, lineno=3774)\n", - " 8\tSTORE_FAST(arg=3, lineno=3774)\n", - " 10\tLOAD_DEREF(arg=0, lineno=3775)\n", - " 12\tLOAD_FAST(arg=0, lineno=3775)\n", - " 14\tLOAD_FAST(arg=1, lineno=3775)\n", - " 16\tLOAD_FAST(arg=1, lineno=3775)\n", - " 18\tLOAD_CONST(arg=1, lineno=3775)\n", - " 20\tLOAD_FAST(arg=3, lineno=3775)\n", - " 22\tLOAD_FAST(arg=3, lineno=3775)\n", - " 24\tCALL_FUNCTION(arg=6, lineno=3775)\n", - " 26\tRETURN_VALUE(arg=None, lineno=3775)\n", - "2024-09-12 10:50:50,505 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:50,506 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:50,506 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:50,507 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=3773)\n", - "2024-09-12 10:50:50,508 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:50,508 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=3774)\n", - "2024-09-12 10:50:50,509 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:50,509 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_FAST(arg=0, lineno=3774)\n", - "2024-09-12 10:50:50,510 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:50,511 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=CALL_FUNCTION(arg=1, lineno=3774)\n", - "2024-09-12 10:50:50,511 - numba.core.byteflow - DEBUG - stack ['$2load_global.0', '$a4.1']\n", - "2024-09-12 10:50:50,512 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=STORE_FAST(arg=3, lineno=3774)\n", - "2024-09-12 10:50:50,513 - numba.core.byteflow - DEBUG - stack ['$6call_function.2']\n", - "2024-09-12 10:50:50,513 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_DEREF(arg=0, lineno=3775)\n", - "2024-09-12 10:50:50,514 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:50,514 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_FAST(arg=0, lineno=3775)\n", - "2024-09-12 10:50:50,515 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3']\n", - "2024-09-12 10:50:50,516 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:50,516 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4']\n", - "2024-09-12 10:50:50,517 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=LOAD_FAST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:50,518 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5']\n", - "2024-09-12 10:50:50,518 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=LOAD_CONST(arg=1, lineno=3775)\n", - "2024-09-12 10:50:50,519 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6']\n", - "2024-09-12 10:50:50,519 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-09-12 10:50:50,520 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7']\n", - "2024-09-12 10:50:50,521 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_FAST(arg=3, lineno=3775)\n", - "2024-09-12 10:50:50,521 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8']\n", - "2024-09-12 10:50:50,522 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=CALL_FUNCTION(arg=6, lineno=3775)\n", - "2024-09-12 10:50:50,523 - numba.core.byteflow - DEBUG - stack ['$10load_deref.3', '$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9']\n", - "2024-09-12 10:50:50,523 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=RETURN_VALUE(arg=None, lineno=3775)\n", - "2024-09-12 10:50:50,524 - numba.core.byteflow - DEBUG - stack ['$24call_function.10']\n", - "2024-09-12 10:50:50,524 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:50,525 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:50,526 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(, {State(pc_initial=0 nstack_initial=0): set()})\n", - "2024-09-12 10:50:50,526 - numba.core.byteflow - DEBUG - defmap: {}\n", - "2024-09-12 10:50:50,527 - numba.core.byteflow - DEBUG - phismap: defaultdict(, {})\n", - "2024-09-12 10:50:50,528 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(, {})\n", - "2024-09-12 10:50:50,528 - numba.core.byteflow - DEBUG - keep phismap: {}\n", - "2024-09-12 10:50:50,529 - numba.core.byteflow - DEBUG - new_out: defaultdict(, {})\n", - "2024-09-12 10:50:50,529 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:50,530 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'res': '$a4.1'}), (6, {'func': '$2load_global.0', 'args': ['$a4.1'], 'res': '$6call_function.2'}), (8, {'value': '$6call_function.2'}), (10, {'res': '$10load_deref.3'}), (12, {'res': '$a12.4'}), (14, {'res': '$v14.5'}), (16, {'res': '$v16.6'}), (18, {'res': '$const18.7'}), (20, {'res': '$n20.8'}), (22, {'res': '$n22.9'}), (24, {'func': '$10load_deref.3', 'args': ['$a12.4', '$v14.5', '$v16.6', '$const18.7', '$n20.8', '$n22.9'], 'res': '$24call_function.10'}), (26, {'retval': '$24call_function.10', 'castval': '$26return_value.11'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:50,532 - numba.core.interpreter - DEBUG - label 0:\n", - " a = arg(0, name=a) ['a']\n", - " v = arg(1, name=v) ['v']\n", - " side = arg(2, name=side) ['side']\n", - " $2load_global.0 = global(len: ) ['$2load_global.0']\n", - " n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None) ['$2load_global.0', 'a', 'n']\n", - " $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f2dc32ed090>) ['$10load_deref.3']\n", - " $const18.7 = const(int, 0) ['$const18.7']\n", - " $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None) ['$10load_deref.3', '$24call_function.10', '$const18.7', 'a', 'n', 'n', 'v', 'v']\n", - " $26return_value.11 = cast(value=$24call_function.10) ['$24call_function.10', '$26return_value.11']\n", - " return $26return_value.11 ['$26return_value.11']\n", - "\n", - "2024-09-12 10:50:50,539 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:50,540 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:50,540 - numba.core.ssa - DEBUG - on stmt: a = arg(0, name=a)\n", - "2024-09-12 10:50:50,541 - numba.core.ssa - DEBUG - on stmt: v = arg(1, name=v)\n", - "2024-09-12 10:50:50,542 - numba.core.ssa - DEBUG - on stmt: side = arg(2, name=side)\n", - "2024-09-12 10:50:50,542 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(len: )\n", - "2024-09-12 10:50:50,543 - numba.core.ssa - DEBUG - on stmt: n = call $2load_global.0(a, func=$2load_global.0, args=[Var(a, arraymath.py:3773)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,544 - numba.core.ssa - DEBUG - on stmt: $10load_deref.3 = freevar(loop_impl: .searchsorted_inner at 0x7f2dc32ed090>)\n", - "2024-09-12 10:50:50,544 - numba.core.ssa - DEBUG - on stmt: $const18.7 = const(int, 0)\n", - "2024-09-12 10:50:50,545 - numba.core.ssa - DEBUG - on stmt: $24call_function.10 = call $10load_deref.3(a, v, v, $const18.7, n, n, func=$10load_deref.3, args=[Var(a, arraymath.py:3773), Var(v, arraymath.py:3773), Var(v, arraymath.py:3773), Var($const18.7, arraymath.py:3775), Var(n, arraymath.py:3774), Var(n, arraymath.py:3774)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:50,546 - numba.core.ssa - DEBUG - on stmt: $26return_value.11 = cast(value=$24call_function.10)\n", - "2024-09-12 10:50:50,546 - numba.core.ssa - DEBUG - on stmt: return $26return_value.11\n", - "2024-09-12 10:50:50,547 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$10load_deref.3': [],\n", - " '$24call_function.10': [],\n", - " '$26return_value.11': [],\n", - " '$2load_global.0': [],\n", - " '$const18.7': [],\n", - " 'a': [],\n", - " 'n': [],\n", - " 'side': [],\n", - " 'v': []})\n", - "2024-09-12 10:50:50,548 - numba.core.ssa - DEBUG - SSA violators set()\n", - "2024-09-12 10:50:50,873 - numba.core.byteflow - DEBUG - bytecode dump:\n", - "> 0\tNOP(arg=None, lineno=553)\n", - " 2\tLOAD_GLOBAL(arg=0, lineno=586)\n", - " 4\tLOAD_ATTR(arg=1, lineno=586)\n", - " 6\tLOAD_ATTR(arg=2, lineno=586)\n", - " 8\tLOAD_METHOD(arg=3, lineno=586)\n", - " 10\tLOAD_GLOBAL(arg=0, lineno=586)\n", - " 12\tLOAD_ATTR(arg=4, lineno=586)\n", - " 14\tLOAD_ATTR(arg=5, lineno=586)\n", - " 16\tCALL_METHOD(arg=1, lineno=586)\n", - " 18\tSTORE_FAST(arg=4, lineno=586)\n", - " 20\tLOAD_GLOBAL(arg=6, lineno=589)\n", - " 22\tLOAD_GLOBAL(arg=7, lineno=589)\n", - " 24\tLOAD_FAST(arg=0, lineno=589)\n", - " 26\tCALL_FUNCTION(arg=1, lineno=589)\n", - " 28\tCALL_FUNCTION(arg=1, lineno=589)\n", - " 30\tGET_ITER(arg=None, lineno=589)\n", - "> 32\tFOR_ITER(arg=100, lineno=589)\n", - " 34\tSTORE_FAST(arg=5, lineno=589)\n", - " 36\tLOAD_GLOBAL(arg=6, lineno=591)\n", - " 38\tLOAD_FAST(arg=0, lineno=591)\n", - " 40\tLOAD_FAST(arg=5, lineno=591)\n", - " 42\tBINARY_SUBSCR(arg=None, lineno=591)\n", - " 44\tLOAD_FAST(arg=1, lineno=591)\n", - " 46\tLOAD_FAST(arg=5, lineno=591)\n", - " 48\tBINARY_SUBSCR(arg=None, lineno=591)\n", - " 50\tCALL_FUNCTION(arg=2, lineno=591)\n", - " 52\tGET_ITER(arg=None, lineno=591)\n", - "> 54\tFOR_ITER(arg=88, lineno=591)\n", - " 56\tSTORE_FAST(arg=6, lineno=591)\n", - " 58\tLOAD_CONST(arg=1, lineno=592)\n", - " 60\tSTORE_FAST(arg=7, lineno=592)\n", - " 62\tLOAD_GLOBAL(arg=6, lineno=595)\n", - " 64\tLOAD_GLOBAL(arg=7, lineno=595)\n", - " 66\tLOAD_FAST(arg=3, lineno=595)\n", - " 68\tCALL_FUNCTION(arg=1, lineno=595)\n", - " 70\tCALL_FUNCTION(arg=1, lineno=595)\n", - " 72\tGET_ITER(arg=None, lineno=595)\n", - "> 74\tFOR_ITER(arg=70, lineno=595)\n", - " 76\tSTORE_FAST(arg=8, lineno=595)\n", - " 78\tLOAD_FAST(arg=3, lineno=596)\n", - " 80\tLOAD_FAST(arg=8, lineno=596)\n", - " 82\tBINARY_SUBSCR(arg=None, lineno=596)\n", - " 84\tSTORE_FAST(arg=9, lineno=596)\n", - " 86\tLOAD_FAST(arg=2, lineno=597)\n", - " 88\tLOAD_FAST(arg=8, lineno=597)\n", - " 90\tLOAD_FAST(arg=6, lineno=597)\n", - " 92\tBUILD_TUPLE(arg=2, lineno=597)\n", - " 94\tBINARY_SUBSCR(arg=None, lineno=597)\n", - " 96\tSTORE_FAST(arg=10, lineno=597)\n", - " 98\tLOAD_FAST(arg=7, lineno=599)\n", - " 100\tLOAD_FAST(arg=10, lineno=599)\n", - " 102\tLOAD_FAST(arg=9, lineno=599)\n", - " 104\tLOAD_CONST(arg=2, lineno=599)\n", - " 106\tBINARY_SUBSCR(arg=None, lineno=599)\n", - " 108\tBINARY_SUBTRACT(arg=None, lineno=599)\n", - " 110\tLOAD_FAST(arg=9, lineno=599)\n", - " 112\tLOAD_CONST(arg=3, lineno=599)\n", - " 114\tBINARY_SUBSCR(arg=None, lineno=599)\n", - " 116\tBINARY_MODULO(arg=None, lineno=599)\n", - " 118\tLOAD_CONST(arg=2, lineno=599)\n", - " 120\tCOMPARE_OP(arg=2, lineno=599)\n", - " 122\tJUMP_IF_FALSE_OR_POP(arg=106, lineno=599)\n", - " 124\tLOAD_FAST(arg=9, lineno=600)\n", - " 126\tLOAD_CONST(arg=3, lineno=600)\n", - " 128\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 130\tLOAD_CONST(arg=2, lineno=600)\n", - " 132\tCOMPARE_OP(arg=4, lineno=600)\n", - " 134\tPOP_JUMP_IF_FALSE(arg=85, lineno=600)\n", - " 136\tLOAD_FAST(arg=9, lineno=600)\n", - " 138\tLOAD_CONST(arg=2, lineno=600)\n", - " 140\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 142\tLOAD_FAST(arg=10, lineno=600)\n", - " 144\tDUP_TOP(arg=None, lineno=600)\n", - " 146\tROT_THREE(arg=None, lineno=600)\n", - " 148\tCOMPARE_OP(arg=1, lineno=600)\n", - " 150\tJUMP_IF_FALSE_OR_POP(arg=82, lineno=600)\n", - " 152\tLOAD_FAST(arg=9, lineno=600)\n", - " 154\tLOAD_CONST(arg=4, lineno=600)\n", - " 156\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 158\tCOMPARE_OP(arg=0, lineno=600)\n", - " 160\tJUMP_FORWARD(arg=2, lineno=600)\n", - "> 162\tROT_TWO(arg=None, lineno=600)\n", - " 164\tPOP_TOP(arg=None, lineno=600)\n", - "> 166\tJUMP_IF_TRUE_OR_POP(arg=106, lineno=600)\n", - "> 168\tLOAD_FAST(arg=9, lineno=600)\n", - " 170\tLOAD_CONST(arg=3, lineno=600)\n", - " 172\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 174\tLOAD_CONST(arg=2, lineno=600)\n", - " 176\tCOMPARE_OP(arg=0, lineno=600)\n", - " 178\tJUMP_IF_FALSE_OR_POP(arg=106, lineno=600)\n", - " 180\tLOAD_FAST(arg=9, lineno=600)\n", - " 182\tLOAD_CONST(arg=2, lineno=600)\n", - " 184\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 186\tLOAD_FAST(arg=10, lineno=600)\n", - " 188\tDUP_TOP(arg=None, lineno=600)\n", - " 190\tROT_THREE(arg=None, lineno=600)\n", - " 192\tCOMPARE_OP(arg=5, lineno=600)\n", - " 194\tJUMP_IF_FALSE_OR_POP(arg=104, lineno=600)\n", - " 196\tLOAD_FAST(arg=9, lineno=600)\n", - " 198\tLOAD_CONST(arg=4, lineno=600)\n", - " 200\tBINARY_SUBSCR(arg=None, lineno=600)\n", - " 202\tCOMPARE_OP(arg=4, lineno=600)\n", - " 204\tJUMP_FORWARD(arg=2, lineno=600)\n", - "> 206\tROT_TWO(arg=None, lineno=600)\n", - " 208\tPOP_TOP(arg=None, lineno=600)\n", - "> 210\tINPLACE_AND(arg=None, lineno=599)\n", - " 212\tSTORE_FAST(arg=7, lineno=599)\n", - " 214\tJUMP_ABSOLUTE(arg=38, lineno=599)\n", - "> 216\tLOAD_FAST(arg=7, lineno=604)\n", - " 218\tPOP_JUMP_IF_FALSE(arg=116, lineno=604)\n", - " 220\tLOAD_FAST(arg=4, lineno=605)\n", - " 222\tLOAD_METHOD(arg=8, lineno=605)\n", - " 224\tLOAD_FAST(arg=6, lineno=605)\n", - " 226\tCALL_METHOD(arg=1, lineno=605)\n", - " 228\tPOP_TOP(arg=None, lineno=605)\n", - "> 230\tJUMP_ABSOLUTE(arg=28, lineno=605)\n", - "> 232\tJUMP_ABSOLUTE(arg=17, lineno=591)\n", - "> 234\tLOAD_FAST(arg=4, lineno=607)\n", - " 236\tRETURN_VALUE(arg=None, lineno=607)\n", - "2024-09-12 10:50:50,874 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=0 nstack_initial=0)])\n", - "2024-09-12 10:50:50,875 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:50,875 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=0 nstack_initial=0)\n", - "2024-09-12 10:50:50,876 - numba.core.byteflow - DEBUG - dispatch pc=0, inst=NOP(arg=None, lineno=553)\n", - "2024-09-12 10:50:50,877 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:50,877 - numba.core.byteflow - DEBUG - dispatch pc=2, inst=LOAD_GLOBAL(arg=0, lineno=586)\n", - "2024-09-12 10:50:50,878 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:50,879 - numba.core.byteflow - DEBUG - dispatch pc=4, inst=LOAD_ATTR(arg=1, lineno=586)\n", - "2024-09-12 10:50:50,879 - numba.core.byteflow - DEBUG - stack ['$2load_global.0']\n", - "2024-09-12 10:50:50,880 - numba.core.byteflow - DEBUG - dispatch pc=6, inst=LOAD_ATTR(arg=2, lineno=586)\n", - "2024-09-12 10:50:50,880 - numba.core.byteflow - DEBUG - stack ['$4load_attr.1']\n", - "2024-09-12 10:50:50,881 - numba.core.byteflow - DEBUG - dispatch pc=8, inst=LOAD_METHOD(arg=3, lineno=586)\n", - "2024-09-12 10:50:50,882 - numba.core.byteflow - DEBUG - stack ['$6load_attr.2']\n", - "2024-09-12 10:50:50,882 - numba.core.byteflow - DEBUG - dispatch pc=10, inst=LOAD_GLOBAL(arg=0, lineno=586)\n", - "2024-09-12 10:50:50,883 - numba.core.byteflow - DEBUG - stack ['$8load_method.3']\n", - "2024-09-12 10:50:50,884 - numba.core.byteflow - DEBUG - dispatch pc=12, inst=LOAD_ATTR(arg=4, lineno=586)\n", - "2024-09-12 10:50:50,884 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$10load_global.4']\n", - "2024-09-12 10:50:50,885 - numba.core.byteflow - DEBUG - dispatch pc=14, inst=LOAD_ATTR(arg=5, lineno=586)\n", - "2024-09-12 10:50:50,886 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$12load_attr.5']\n", - "2024-09-12 10:50:50,886 - numba.core.byteflow - DEBUG - dispatch pc=16, inst=CALL_METHOD(arg=1, lineno=586)\n", - "2024-09-12 10:50:50,887 - numba.core.byteflow - DEBUG - stack ['$8load_method.3', '$14load_attr.6']\n", - "2024-09-12 10:50:50,888 - numba.core.byteflow - DEBUG - dispatch pc=18, inst=STORE_FAST(arg=4, lineno=586)\n", - "2024-09-12 10:50:50,888 - numba.core.byteflow - DEBUG - stack ['$16call_method.7']\n", - "2024-09-12 10:50:50,889 - numba.core.byteflow - DEBUG - dispatch pc=20, inst=LOAD_GLOBAL(arg=6, lineno=589)\n", - "2024-09-12 10:50:50,890 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:50,890 - numba.core.byteflow - DEBUG - dispatch pc=22, inst=LOAD_GLOBAL(arg=7, lineno=589)\n", - "2024-09-12 10:50:50,891 - numba.core.byteflow - DEBUG - stack ['$20load_global.8']\n", - "2024-09-12 10:50:50,891 - numba.core.byteflow - DEBUG - dispatch pc=24, inst=LOAD_FAST(arg=0, lineno=589)\n", - "2024-09-12 10:50:50,892 - numba.core.byteflow - DEBUG - stack ['$20load_global.8', '$22load_global.9']\n", - "2024-09-12 10:50:50,893 - numba.core.byteflow - DEBUG - dispatch pc=26, inst=CALL_FUNCTION(arg=1, lineno=589)\n", - "2024-09-12 10:50:50,893 - numba.core.byteflow - DEBUG - stack ['$20load_global.8', '$22load_global.9', '$starts24.10']\n", - "2024-09-12 10:50:50,894 - numba.core.byteflow - DEBUG - dispatch pc=28, inst=CALL_FUNCTION(arg=1, lineno=589)\n", - "2024-09-12 10:50:50,895 - numba.core.byteflow - DEBUG - stack ['$20load_global.8', '$26call_function.11']\n", - "2024-09-12 10:50:50,895 - numba.core.byteflow - DEBUG - dispatch pc=30, inst=GET_ITER(arg=None, lineno=589)\n", - "2024-09-12 10:50:50,896 - numba.core.byteflow - DEBUG - stack ['$28call_function.12']\n", - "2024-09-12 10:50:50,897 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=32, stack=('$30get_iter.13',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:50,897 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=1)])\n", - "2024-09-12 10:50:50,898 - numba.core.byteflow - DEBUG - stack: ['$phi32.0']\n", - "2024-09-12 10:50:50,899 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=32 nstack_initial=1)\n", - "2024-09-12 10:50:50,899 - numba.core.byteflow - DEBUG - dispatch pc=32, inst=FOR_ITER(arg=100, lineno=589)\n", - "2024-09-12 10:50:50,900 - numba.core.byteflow - DEBUG - stack ['$phi32.0']\n", - "2024-09-12 10:50:50,901 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=234, stack=(), blockstack=(), npush=0), Edge(pc=34, stack=('$phi32.0', '$32for_iter.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:50,902 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=234 nstack_initial=0), State(pc_initial=34 nstack_initial=2)])\n", - "2024-09-12 10:50:50,902 - numba.core.byteflow - DEBUG - stack: []\n", - "2024-09-12 10:50:50,903 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=234 nstack_initial=0)\n", - "2024-09-12 10:50:50,904 - numba.core.byteflow - DEBUG - dispatch pc=234, inst=LOAD_FAST(arg=4, lineno=607)\n", - "2024-09-12 10:50:50,910 - numba.core.byteflow - DEBUG - stack []\n", - "2024-09-12 10:50:50,910 - numba.core.byteflow - DEBUG - dispatch pc=236, inst=RETURN_VALUE(arg=None, lineno=607)\n", - "2024-09-12 10:50:50,911 - numba.core.byteflow - DEBUG - stack ['$mask234.0']\n", - "2024-09-12 10:50:50,912 - numba.core.byteflow - DEBUG - end state. edges=[]\n", - "2024-09-12 10:50:50,913 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=34 nstack_initial=2)])\n", - "2024-09-12 10:50:50,913 - numba.core.byteflow - DEBUG - stack: ['$phi34.0', '$phi34.1']\n", - "2024-09-12 10:50:50,914 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=34 nstack_initial=2)\n", - "2024-09-12 10:50:50,915 - numba.core.byteflow - DEBUG - dispatch pc=34, inst=STORE_FAST(arg=5, lineno=589)\n", - "2024-09-12 10:50:50,916 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$phi34.1']\n", - "2024-09-12 10:50:50,916 - numba.core.byteflow - DEBUG - dispatch pc=36, inst=LOAD_GLOBAL(arg=6, lineno=591)\n", - "2024-09-12 10:50:50,917 - numba.core.byteflow - DEBUG - stack ['$phi34.0']\n", - "2024-09-12 10:50:50,918 - numba.core.byteflow - DEBUG - dispatch pc=38, inst=LOAD_FAST(arg=0, lineno=591)\n", - "2024-09-12 10:50:50,919 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2']\n", - "2024-09-12 10:50:50,920 - numba.core.byteflow - DEBUG - dispatch pc=40, inst=LOAD_FAST(arg=5, lineno=591)\n", - "2024-09-12 10:50:50,920 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$starts38.3']\n", - "2024-09-12 10:50:50,921 - numba.core.byteflow - DEBUG - dispatch pc=42, inst=BINARY_SUBSCR(arg=None, lineno=591)\n", - "2024-09-12 10:50:50,922 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$starts38.3', '$i40.4']\n", - "2024-09-12 10:50:50,923 - numba.core.byteflow - DEBUG - dispatch pc=44, inst=LOAD_FAST(arg=1, lineno=591)\n", - "2024-09-12 10:50:50,924 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$42binary_subscr.5']\n", - "2024-09-12 10:50:50,924 - numba.core.byteflow - DEBUG - dispatch pc=46, inst=LOAD_FAST(arg=5, lineno=591)\n", - "2024-09-12 10:50:50,925 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$42binary_subscr.5', '$stops44.6']\n", - "2024-09-12 10:50:50,926 - numba.core.byteflow - DEBUG - dispatch pc=48, inst=BINARY_SUBSCR(arg=None, lineno=591)\n", - "2024-09-12 10:50:50,927 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$42binary_subscr.5', '$stops44.6', '$i46.7']\n", - "2024-09-12 10:50:50,927 - numba.core.byteflow - DEBUG - dispatch pc=50, inst=CALL_FUNCTION(arg=2, lineno=591)\n", - "2024-09-12 10:50:50,928 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$36load_global.2', '$42binary_subscr.5', '$48binary_subscr.8']\n", - "2024-09-12 10:50:50,929 - numba.core.byteflow - DEBUG - dispatch pc=52, inst=GET_ITER(arg=None, lineno=591)\n", - "2024-09-12 10:50:50,930 - numba.core.byteflow - DEBUG - stack ['$phi34.0', '$50call_function.9']\n", - "2024-09-12 10:50:50,930 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=54, stack=('$phi34.0', '$52get_iter.10'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:50,931 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=2)])\n", - "2024-09-12 10:50:50,932 - numba.core.byteflow - DEBUG - stack: ['$phi54.0', '$phi54.1']\n", - "2024-09-12 10:50:50,933 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=54 nstack_initial=2)\n", - "2024-09-12 10:50:50,934 - numba.core.byteflow - DEBUG - dispatch pc=54, inst=FOR_ITER(arg=88, lineno=591)\n", - "2024-09-12 10:50:50,935 - numba.core.byteflow - DEBUG - stack ['$phi54.0', '$phi54.1']\n", - "2024-09-12 10:50:50,935 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=232, stack=('$phi54.0',), blockstack=(), npush=0), Edge(pc=56, stack=('$phi54.0', '$phi54.1', '$54for_iter.3'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:50,936 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=232 nstack_initial=1), State(pc_initial=56 nstack_initial=3)])\n", - "2024-09-12 10:50:50,937 - numba.core.byteflow - DEBUG - stack: ['$phi232.0']\n", - "2024-09-12 10:50:50,938 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=232 nstack_initial=1)\n", - "2024-09-12 10:50:50,938 - numba.core.byteflow - DEBUG - dispatch pc=232, inst=JUMP_ABSOLUTE(arg=17, lineno=591)\n", - "2024-09-12 10:50:50,939 - numba.core.byteflow - DEBUG - stack ['$phi232.0']\n", - "2024-09-12 10:50:50,940 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=32, stack=('$phi232.0',), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:50,941 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=56 nstack_initial=3), State(pc_initial=32 nstack_initial=1)])\n", - "2024-09-12 10:50:50,942 - numba.core.byteflow - DEBUG - stack: ['$phi56.0', '$phi56.1', '$phi56.2']\n", - "2024-09-12 10:50:50,943 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=56 nstack_initial=3)\n", - "2024-09-12 10:50:50,943 - numba.core.byteflow - DEBUG - dispatch pc=56, inst=STORE_FAST(arg=6, lineno=591)\n", - "2024-09-12 10:50:50,944 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$phi56.2']\n", - "2024-09-12 10:50:50,945 - numba.core.byteflow - DEBUG - dispatch pc=58, inst=LOAD_CONST(arg=1, lineno=592)\n", - "2024-09-12 10:50:50,946 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1']\n", - "2024-09-12 10:50:50,947 - numba.core.byteflow - DEBUG - dispatch pc=60, inst=STORE_FAST(arg=7, lineno=592)\n", - "2024-09-12 10:50:50,947 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$const58.3']\n", - "2024-09-12 10:50:50,948 - numba.core.byteflow - DEBUG - dispatch pc=62, inst=LOAD_GLOBAL(arg=6, lineno=595)\n", - "2024-09-12 10:50:50,949 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1']\n", - "2024-09-12 10:50:50,950 - numba.core.byteflow - DEBUG - dispatch pc=64, inst=LOAD_GLOBAL(arg=7, lineno=595)\n", - "2024-09-12 10:50:50,951 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$62load_global.4']\n", - "2024-09-12 10:50:50,952 - numba.core.byteflow - DEBUG - dispatch pc=66, inst=LOAD_FAST(arg=3, lineno=595)\n", - "2024-09-12 10:50:50,952 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$62load_global.4', '$64load_global.5']\n", - "2024-09-12 10:50:50,953 - numba.core.byteflow - DEBUG - dispatch pc=68, inst=CALL_FUNCTION(arg=1, lineno=595)\n", - "2024-09-12 10:50:50,954 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$62load_global.4', '$64load_global.5', '$indices66.6']\n", - "2024-09-12 10:50:50,955 - numba.core.byteflow - DEBUG - dispatch pc=70, inst=CALL_FUNCTION(arg=1, lineno=595)\n", - "2024-09-12 10:50:50,956 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$62load_global.4', '$68call_function.7']\n", - "2024-09-12 10:50:50,956 - numba.core.byteflow - DEBUG - dispatch pc=72, inst=GET_ITER(arg=None, lineno=595)\n", - "2024-09-12 10:50:50,957 - numba.core.byteflow - DEBUG - stack ['$phi56.0', '$phi56.1', '$70call_function.8']\n", - "2024-09-12 10:50:50,958 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=74, stack=('$phi56.0', '$phi56.1', '$72get_iter.9'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:50,959 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=32 nstack_initial=1), State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:50,960 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:50,961 - numba.core.byteflow - DEBUG - stack: ['$phi74.0', '$phi74.1', '$phi74.2']\n", - "2024-09-12 10:50:50,961 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=74 nstack_initial=3)\n", - "2024-09-12 10:50:50,962 - numba.core.byteflow - DEBUG - dispatch pc=74, inst=FOR_ITER(arg=70, lineno=595)\n", - "2024-09-12 10:50:50,963 - numba.core.byteflow - DEBUG - stack ['$phi74.0', '$phi74.1', '$phi74.2']\n", - "2024-09-12 10:50:50,964 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=216, stack=('$phi74.0', '$phi74.1'), blockstack=(), npush=0), Edge(pc=76, stack=('$phi74.0', '$phi74.1', '$phi74.2', '$74for_iter.4'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:50,965 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=216 nstack_initial=2), State(pc_initial=76 nstack_initial=4)])\n", - "2024-09-12 10:50:50,966 - numba.core.byteflow - DEBUG - stack: ['$phi216.0', '$phi216.1']\n", - "2024-09-12 10:50:50,966 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=216 nstack_initial=2)\n", - "2024-09-12 10:50:50,967 - numba.core.byteflow - DEBUG - dispatch pc=216, inst=LOAD_FAST(arg=7, lineno=604)\n", - "2024-09-12 10:50:50,968 - numba.core.byteflow - DEBUG - stack ['$phi216.0', '$phi216.1']\n", - "2024-09-12 10:50:50,969 - numba.core.byteflow - DEBUG - dispatch pc=218, inst=POP_JUMP_IF_FALSE(arg=116, lineno=604)\n", - "2024-09-12 10:50:50,970 - numba.core.byteflow - DEBUG - stack ['$phi216.0', '$phi216.1', '$match216.2']\n", - "2024-09-12 10:50:50,970 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=220, stack=('$phi216.0', '$phi216.1'), blockstack=(), npush=0), Edge(pc=230, stack=('$phi216.0', '$phi216.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:50,971 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=76 nstack_initial=4), State(pc_initial=220 nstack_initial=2), State(pc_initial=230 nstack_initial=2)])\n", - "2024-09-12 10:50:50,972 - numba.core.byteflow - DEBUG - stack: ['$phi76.0', '$phi76.1', '$phi76.2', '$phi76.3']\n", - "2024-09-12 10:50:50,973 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=76 nstack_initial=4)\n", - "2024-09-12 10:50:50,974 - numba.core.byteflow - DEBUG - dispatch pc=76, inst=STORE_FAST(arg=8, lineno=595)\n", - "2024-09-12 10:50:50,974 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$phi76.3']\n", - "2024-09-12 10:50:50,975 - numba.core.byteflow - DEBUG - dispatch pc=78, inst=LOAD_FAST(arg=3, lineno=596)\n", - "2024-09-12 10:50:50,976 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2']\n", - "2024-09-12 10:50:50,977 - numba.core.byteflow - DEBUG - dispatch pc=80, inst=LOAD_FAST(arg=8, lineno=596)\n", - "2024-09-12 10:50:50,978 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$indices78.4']\n", - "2024-09-12 10:50:50,978 - numba.core.byteflow - DEBUG - dispatch pc=82, inst=BINARY_SUBSCR(arg=None, lineno=596)\n", - "2024-09-12 10:50:50,979 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$indices78.4', '$k80.5']\n", - "2024-09-12 10:50:50,980 - numba.core.byteflow - DEBUG - dispatch pc=84, inst=STORE_FAST(arg=9, lineno=596)\n", - "2024-09-12 10:50:50,981 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$82binary_subscr.6']\n", - "2024-09-12 10:50:50,981 - numba.core.byteflow - DEBUG - dispatch pc=86, inst=LOAD_FAST(arg=2, lineno=597)\n", - "2024-09-12 10:50:50,982 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2']\n", - "2024-09-12 10:50:50,983 - numba.core.byteflow - DEBUG - dispatch pc=88, inst=LOAD_FAST(arg=8, lineno=597)\n", - "2024-09-12 10:50:50,984 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$coords86.7']\n", - "2024-09-12 10:50:50,985 - numba.core.byteflow - DEBUG - dispatch pc=90, inst=LOAD_FAST(arg=6, lineno=597)\n", - "2024-09-12 10:50:50,985 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$coords86.7', '$k88.8']\n", - "2024-09-12 10:50:50,986 - numba.core.byteflow - DEBUG - dispatch pc=92, inst=BUILD_TUPLE(arg=2, lineno=597)\n", - "2024-09-12 10:50:50,987 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$coords86.7', '$k88.8', '$j90.9']\n", - "2024-09-12 10:50:50,988 - numba.core.byteflow - DEBUG - dispatch pc=94, inst=BINARY_SUBSCR(arg=None, lineno=597)\n", - "2024-09-12 10:50:50,988 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$coords86.7', '$92build_tuple.10']\n", - "2024-09-12 10:50:50,989 - numba.core.byteflow - DEBUG - dispatch pc=96, inst=STORE_FAST(arg=10, lineno=597)\n", - "2024-09-12 10:50:50,990 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$94binary_subscr.11']\n", - "2024-09-12 10:50:50,991 - numba.core.byteflow - DEBUG - dispatch pc=98, inst=LOAD_FAST(arg=7, lineno=599)\n", - "2024-09-12 10:50:50,991 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2']\n", - "2024-09-12 10:50:50,992 - numba.core.byteflow - DEBUG - dispatch pc=100, inst=LOAD_FAST(arg=10, lineno=599)\n", - "2024-09-12 10:50:50,993 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12']\n", - "2024-09-12 10:50:50,994 - numba.core.byteflow - DEBUG - dispatch pc=102, inst=LOAD_FAST(arg=9, lineno=599)\n", - "2024-09-12 10:50:50,994 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$elem100.13']\n", - "2024-09-12 10:50:50,995 - numba.core.byteflow - DEBUG - dispatch pc=104, inst=LOAD_CONST(arg=2, lineno=599)\n", - "2024-09-12 10:50:50,996 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$elem100.13', '$idx102.14']\n", - "2024-09-12 10:50:50,997 - numba.core.byteflow - DEBUG - dispatch pc=106, inst=BINARY_SUBSCR(arg=None, lineno=599)\n", - "2024-09-12 10:50:50,997 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$elem100.13', '$idx102.14', '$const104.15']\n", - "2024-09-12 10:50:50,998 - numba.core.byteflow - DEBUG - dispatch pc=108, inst=BINARY_SUBTRACT(arg=None, lineno=599)\n", - "2024-09-12 10:50:50,999 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$elem100.13', '$106binary_subscr.16']\n", - "2024-09-12 10:50:51,000 - numba.core.byteflow - DEBUG - dispatch pc=110, inst=LOAD_FAST(arg=9, lineno=599)\n", - "2024-09-12 10:50:51,000 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$108binary_subtract.17']\n", - "2024-09-12 10:50:51,001 - numba.core.byteflow - DEBUG - dispatch pc=112, inst=LOAD_CONST(arg=3, lineno=599)\n", - "2024-09-12 10:50:51,002 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$108binary_subtract.17', '$idx110.18']\n", - "2024-09-12 10:50:51,002 - numba.core.byteflow - DEBUG - dispatch pc=114, inst=BINARY_SUBSCR(arg=None, lineno=599)\n", - "2024-09-12 10:50:51,003 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$108binary_subtract.17', '$idx110.18', '$const112.19']\n", - "2024-09-12 10:50:51,004 - numba.core.byteflow - DEBUG - dispatch pc=116, inst=BINARY_MODULO(arg=None, lineno=599)\n", - "2024-09-12 10:50:51,004 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$108binary_subtract.17', '$114binary_subscr.20']\n", - "2024-09-12 10:50:51,005 - numba.core.byteflow - DEBUG - dispatch pc=118, inst=LOAD_CONST(arg=2, lineno=599)\n", - "2024-09-12 10:50:51,006 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$116binary_modulo.21']\n", - "2024-09-12 10:50:51,007 - numba.core.byteflow - DEBUG - dispatch pc=120, inst=COMPARE_OP(arg=2, lineno=599)\n", - "2024-09-12 10:50:51,007 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$116binary_modulo.21', '$const118.22']\n", - "2024-09-12 10:50:51,008 - numba.core.byteflow - DEBUG - dispatch pc=122, inst=JUMP_IF_FALSE_OR_POP(arg=106, lineno=599)\n", - "2024-09-12 10:50:51,009 - numba.core.byteflow - DEBUG - stack ['$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$120compare_op.23']\n", - "2024-09-12 10:50:51,010 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=124, stack=('$phi76.0', '$phi76.1', '$phi76.2', '$match98.12'), blockstack=(), npush=0), Edge(pc=210, stack=('$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$120compare_op.23'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,011 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=220 nstack_initial=2), State(pc_initial=230 nstack_initial=2), State(pc_initial=124 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,011 - numba.core.byteflow - DEBUG - stack: ['$phi220.0', '$phi220.1']\n", - "2024-09-12 10:50:51,012 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=220 nstack_initial=2)\n", - "2024-09-12 10:50:51,013 - numba.core.byteflow - DEBUG - dispatch pc=220, inst=LOAD_FAST(arg=4, lineno=605)\n", - "2024-09-12 10:50:51,013 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1']\n", - "2024-09-12 10:50:51,014 - numba.core.byteflow - DEBUG - dispatch pc=222, inst=LOAD_METHOD(arg=8, lineno=605)\n", - "2024-09-12 10:50:51,015 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$mask220.2']\n", - "2024-09-12 10:50:51,016 - numba.core.byteflow - DEBUG - dispatch pc=224, inst=LOAD_FAST(arg=6, lineno=605)\n", - "2024-09-12 10:50:51,016 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$222load_method.3']\n", - "2024-09-12 10:50:51,017 - numba.core.byteflow - DEBUG - dispatch pc=226, inst=CALL_METHOD(arg=1, lineno=605)\n", - "2024-09-12 10:50:51,018 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$222load_method.3', '$j224.4']\n", - "2024-09-12 10:50:51,019 - numba.core.byteflow - DEBUG - dispatch pc=228, inst=POP_TOP(arg=None, lineno=605)\n", - "2024-09-12 10:50:51,019 - numba.core.byteflow - DEBUG - stack ['$phi220.0', '$phi220.1', '$226call_method.5']\n", - "2024-09-12 10:50:51,020 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=230, stack=('$phi220.0', '$phi220.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,021 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=230 nstack_initial=2), State(pc_initial=124 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=230 nstack_initial=2)])\n", - "2024-09-12 10:50:51,021 - numba.core.byteflow - DEBUG - stack: ['$phi230.0', '$phi230.1']\n", - "2024-09-12 10:50:51,022 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=230 nstack_initial=2)\n", - "2024-09-12 10:50:51,023 - numba.core.byteflow - DEBUG - dispatch pc=230, inst=JUMP_ABSOLUTE(arg=28, lineno=605)\n", - "2024-09-12 10:50:51,024 - numba.core.byteflow - DEBUG - stack ['$phi230.0', '$phi230.1']\n", - "2024-09-12 10:50:51,024 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=54, stack=('$phi230.0', '$phi230.1'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,025 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=124 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=230 nstack_initial=2), State(pc_initial=54 nstack_initial=2)])\n", - "2024-09-12 10:50:51,026 - numba.core.byteflow - DEBUG - stack: ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3']\n", - "2024-09-12 10:50:51,026 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=124 nstack_initial=4)\n", - "2024-09-12 10:50:51,027 - numba.core.byteflow - DEBUG - dispatch pc=124, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:51,028 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3']\n", - "2024-09-12 10:50:51,028 - numba.core.byteflow - DEBUG - dispatch pc=126, inst=LOAD_CONST(arg=3, lineno=600)\n", - "2024-09-12 10:50:51,029 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$idx124.4']\n", - "2024-09-12 10:50:51,030 - numba.core.byteflow - DEBUG - dispatch pc=128, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,030 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$idx124.4', '$const126.5']\n", - "2024-09-12 10:50:51,031 - numba.core.byteflow - DEBUG - dispatch pc=130, inst=LOAD_CONST(arg=2, lineno=600)\n", - "2024-09-12 10:50:51,032 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$128binary_subscr.6']\n", - "2024-09-12 10:50:51,033 - numba.core.byteflow - DEBUG - dispatch pc=132, inst=COMPARE_OP(arg=4, lineno=600)\n", - "2024-09-12 10:50:51,033 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$128binary_subscr.6', '$const130.7']\n", - "2024-09-12 10:50:51,034 - numba.core.byteflow - DEBUG - dispatch pc=134, inst=POP_JUMP_IF_FALSE(arg=85, lineno=600)\n", - "2024-09-12 10:50:51,035 - numba.core.byteflow - DEBUG - stack ['$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3', '$132compare_op.8']\n", - "2024-09-12 10:50:51,035 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=136, stack=('$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3'), blockstack=(), npush=0), Edge(pc=168, stack=('$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,036 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5), State(pc_initial=230 nstack_initial=2), State(pc_initial=54 nstack_initial=2), State(pc_initial=136 nstack_initial=4), State(pc_initial=168 nstack_initial=4)])\n", - "2024-09-12 10:50:51,037 - numba.core.byteflow - DEBUG - stack: ['$phi210.0', '$phi210.1', '$phi210.2', '$phi210.3', '$phi210.4']\n", - "2024-09-12 10:50:51,038 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=210 nstack_initial=5)\n", - "2024-09-12 10:50:51,038 - numba.core.byteflow - DEBUG - dispatch pc=210, inst=INPLACE_AND(arg=None, lineno=599)\n", - "2024-09-12 10:50:51,039 - numba.core.byteflow - DEBUG - stack ['$phi210.0', '$phi210.1', '$phi210.2', '$phi210.3', '$phi210.4']\n", - "2024-09-12 10:50:51,040 - numba.core.byteflow - DEBUG - dispatch pc=212, inst=STORE_FAST(arg=7, lineno=599)\n", - "2024-09-12 10:50:51,040 - numba.core.byteflow - DEBUG - stack ['$phi210.0', '$phi210.1', '$phi210.2', '$210inplace_and.5']\n", - "2024-09-12 10:50:51,041 - numba.core.byteflow - DEBUG - dispatch pc=214, inst=JUMP_ABSOLUTE(arg=38, lineno=599)\n", - "2024-09-12 10:50:51,042 - numba.core.byteflow - DEBUG - stack ['$phi210.0', '$phi210.1', '$phi210.2']\n", - "2024-09-12 10:50:51,042 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=74, stack=('$phi210.0', '$phi210.1', '$phi210.2'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,043 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=230 nstack_initial=2), State(pc_initial=54 nstack_initial=2), State(pc_initial=136 nstack_initial=4), State(pc_initial=168 nstack_initial=4), State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:51,044 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=54 nstack_initial=2), State(pc_initial=136 nstack_initial=4), State(pc_initial=168 nstack_initial=4), State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:51,045 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=136 nstack_initial=4), State(pc_initial=168 nstack_initial=4), State(pc_initial=74 nstack_initial=3)])\n", - "2024-09-12 10:50:51,045 - numba.core.byteflow - DEBUG - stack: ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3']\n", - "2024-09-12 10:50:51,046 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=136 nstack_initial=4)\n", - "2024-09-12 10:50:51,047 - numba.core.byteflow - DEBUG - dispatch pc=136, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:51,047 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3']\n", - "2024-09-12 10:50:51,048 - numba.core.byteflow - DEBUG - dispatch pc=138, inst=LOAD_CONST(arg=2, lineno=600)\n", - "2024-09-12 10:50:51,049 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$idx136.4']\n", - "2024-09-12 10:50:51,049 - numba.core.byteflow - DEBUG - dispatch pc=140, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,050 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$idx136.4', '$const138.5']\n", - "2024-09-12 10:50:51,051 - numba.core.byteflow - DEBUG - dispatch pc=142, inst=LOAD_FAST(arg=10, lineno=600)\n", - "2024-09-12 10:50:51,051 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$140binary_subscr.6']\n", - "2024-09-12 10:50:51,052 - numba.core.byteflow - DEBUG - dispatch pc=144, inst=DUP_TOP(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,053 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$140binary_subscr.6', '$elem142.7']\n", - "2024-09-12 10:50:51,054 - numba.core.byteflow - DEBUG - dispatch pc=146, inst=ROT_THREE(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,054 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$140binary_subscr.6', '$elem142.7', '$144dup_top.8']\n", - "2024-09-12 10:50:51,055 - numba.core.byteflow - DEBUG - dispatch pc=148, inst=COMPARE_OP(arg=1, lineno=600)\n", - "2024-09-12 10:50:51,055 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8', '$140binary_subscr.6', '$elem142.7']\n", - "2024-09-12 10:50:51,056 - numba.core.byteflow - DEBUG - dispatch pc=150, inst=JUMP_IF_FALSE_OR_POP(arg=82, lineno=600)\n", - "2024-09-12 10:50:51,057 - numba.core.byteflow - DEBUG - stack ['$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8', '$148compare_op.9']\n", - "2024-09-12 10:50:51,058 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=152, stack=('$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8'), blockstack=(), npush=0), Edge(pc=162, stack=('$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8', '$148compare_op.9'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,058 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=168 nstack_initial=4), State(pc_initial=74 nstack_initial=3), State(pc_initial=152 nstack_initial=5), State(pc_initial=162 nstack_initial=6)])\n", - "2024-09-12 10:50:51,059 - numba.core.byteflow - DEBUG - stack: ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3']\n", - "2024-09-12 10:50:51,060 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=168 nstack_initial=4)\n", - "2024-09-12 10:50:51,060 - numba.core.byteflow - DEBUG - dispatch pc=168, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:51,061 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3']\n", - "2024-09-12 10:50:51,062 - numba.core.byteflow - DEBUG - dispatch pc=170, inst=LOAD_CONST(arg=3, lineno=600)\n", - "2024-09-12 10:50:51,063 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$idx168.4']\n", - "2024-09-12 10:50:51,063 - numba.core.byteflow - DEBUG - dispatch pc=172, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,064 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$idx168.4', '$const170.5']\n", - "2024-09-12 10:50:51,065 - numba.core.byteflow - DEBUG - dispatch pc=174, inst=LOAD_CONST(arg=2, lineno=600)\n", - "2024-09-12 10:50:51,065 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$172binary_subscr.6']\n", - "2024-09-12 10:50:51,066 - numba.core.byteflow - DEBUG - dispatch pc=176, inst=COMPARE_OP(arg=0, lineno=600)\n", - "2024-09-12 10:50:51,067 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$172binary_subscr.6', '$const174.7']\n", - "2024-09-12 10:50:51,067 - numba.core.byteflow - DEBUG - dispatch pc=178, inst=JUMP_IF_FALSE_OR_POP(arg=106, lineno=600)\n", - "2024-09-12 10:50:51,068 - numba.core.byteflow - DEBUG - stack ['$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$176compare_op.8']\n", - "2024-09-12 10:50:51,069 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=180, stack=('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3'), blockstack=(), npush=0), Edge(pc=210, stack=('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$176compare_op.8'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,069 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=74 nstack_initial=3), State(pc_initial=152 nstack_initial=5), State(pc_initial=162 nstack_initial=6), State(pc_initial=180 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,070 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=152 nstack_initial=5), State(pc_initial=162 nstack_initial=6), State(pc_initial=180 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,071 - numba.core.byteflow - DEBUG - stack: ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4']\n", - "2024-09-12 10:50:51,071 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=152 nstack_initial=5)\n", - "2024-09-12 10:50:51,072 - numba.core.byteflow - DEBUG - dispatch pc=152, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:51,073 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4']\n", - "2024-09-12 10:50:51,073 - numba.core.byteflow - DEBUG - dispatch pc=154, inst=LOAD_CONST(arg=4, lineno=600)\n", - "2024-09-12 10:50:51,074 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4', '$idx152.5']\n", - "2024-09-12 10:50:51,075 - numba.core.byteflow - DEBUG - dispatch pc=156, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,075 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4', '$idx152.5', '$const154.6']\n", - "2024-09-12 10:50:51,076 - numba.core.byteflow - DEBUG - dispatch pc=158, inst=COMPARE_OP(arg=0, lineno=600)\n", - "2024-09-12 10:50:51,076 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$phi152.4', '$156binary_subscr.7']\n", - "2024-09-12 10:50:51,077 - numba.core.byteflow - DEBUG - dispatch pc=160, inst=JUMP_FORWARD(arg=2, lineno=600)\n", - "2024-09-12 10:50:51,078 - numba.core.byteflow - DEBUG - stack ['$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$158compare_op.8']\n", - "2024-09-12 10:50:51,078 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=166, stack=('$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$158compare_op.8'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,079 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=162 nstack_initial=6), State(pc_initial=180 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=166 nstack_initial=5)])\n", - "2024-09-12 10:50:51,080 - numba.core.byteflow - DEBUG - stack: ['$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.4', '$phi162.5']\n", - "2024-09-12 10:50:51,080 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=162 nstack_initial=6)\n", - "2024-09-12 10:50:51,081 - numba.core.byteflow - DEBUG - dispatch pc=162, inst=ROT_TWO(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,082 - numba.core.byteflow - DEBUG - stack ['$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.4', '$phi162.5']\n", - "2024-09-12 10:50:51,082 - numba.core.byteflow - DEBUG - dispatch pc=164, inst=POP_TOP(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,083 - numba.core.byteflow - DEBUG - stack ['$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.5', '$phi162.4']\n", - "2024-09-12 10:50:51,083 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=166, stack=('$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.5'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,084 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=180 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=166 nstack_initial=5), State(pc_initial=166 nstack_initial=5)])\n", - "2024-09-12 10:50:51,085 - numba.core.byteflow - DEBUG - stack: ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3']\n", - "2024-09-12 10:50:51,085 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=180 nstack_initial=4)\n", - "2024-09-12 10:50:51,086 - numba.core.byteflow - DEBUG - dispatch pc=180, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:51,087 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3']\n", - "2024-09-12 10:50:51,087 - numba.core.byteflow - DEBUG - dispatch pc=182, inst=LOAD_CONST(arg=2, lineno=600)\n", - "2024-09-12 10:50:51,088 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$idx180.4']\n", - "2024-09-12 10:50:51,089 - numba.core.byteflow - DEBUG - dispatch pc=184, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,089 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$idx180.4', '$const182.5']\n", - "2024-09-12 10:50:51,090 - numba.core.byteflow - DEBUG - dispatch pc=186, inst=LOAD_FAST(arg=10, lineno=600)\n", - "2024-09-12 10:50:51,091 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$184binary_subscr.6']\n", - "2024-09-12 10:50:51,091 - numba.core.byteflow - DEBUG - dispatch pc=188, inst=DUP_TOP(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,092 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$184binary_subscr.6', '$elem186.7']\n", - "2024-09-12 10:50:51,092 - numba.core.byteflow - DEBUG - dispatch pc=190, inst=ROT_THREE(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,093 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$184binary_subscr.6', '$elem186.7', '$188dup_top.8']\n", - "2024-09-12 10:50:51,114 - numba.core.byteflow - DEBUG - dispatch pc=192, inst=COMPARE_OP(arg=5, lineno=600)\n", - "2024-09-12 10:50:51,128 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8', '$184binary_subscr.6', '$elem186.7']\n", - "2024-09-12 10:50:51,129 - numba.core.byteflow - DEBUG - dispatch pc=194, inst=JUMP_IF_FALSE_OR_POP(arg=104, lineno=600)\n", - "2024-09-12 10:50:51,129 - numba.core.byteflow - DEBUG - stack ['$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8', '$192compare_op.9']\n", - "2024-09-12 10:50:51,130 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=196, stack=('$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8'), blockstack=(), npush=0), Edge(pc=206, stack=('$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8', '$192compare_op.9'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,130 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5), State(pc_initial=166 nstack_initial=5), State(pc_initial=166 nstack_initial=5), State(pc_initial=196 nstack_initial=5), State(pc_initial=206 nstack_initial=6)])\n", - "2024-09-12 10:50:51,131 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=166 nstack_initial=5), State(pc_initial=166 nstack_initial=5), State(pc_initial=196 nstack_initial=5), State(pc_initial=206 nstack_initial=6)])\n", - "2024-09-12 10:50:51,132 - numba.core.byteflow - DEBUG - stack: ['$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$phi166.4']\n", - "2024-09-12 10:50:51,133 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=166 nstack_initial=5)\n", - "2024-09-12 10:50:51,133 - numba.core.byteflow - DEBUG - dispatch pc=166, inst=JUMP_IF_TRUE_OR_POP(arg=106, lineno=600)\n", - "2024-09-12 10:50:51,134 - numba.core.byteflow - DEBUG - stack ['$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$phi166.4']\n", - "2024-09-12 10:50:51,135 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=168, stack=('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3'), blockstack=(), npush=0), Edge(pc=210, stack=('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$phi166.4'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,135 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=166 nstack_initial=5), State(pc_initial=196 nstack_initial=5), State(pc_initial=206 nstack_initial=6), State(pc_initial=168 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,136 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=196 nstack_initial=5), State(pc_initial=206 nstack_initial=6), State(pc_initial=168 nstack_initial=4), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,137 - numba.core.byteflow - DEBUG - stack: ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4']\n", - "2024-09-12 10:50:51,137 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=196 nstack_initial=5)\n", - "2024-09-12 10:50:51,138 - numba.core.byteflow - DEBUG - dispatch pc=196, inst=LOAD_FAST(arg=9, lineno=600)\n", - "2024-09-12 10:50:51,138 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4']\n", - "2024-09-12 10:50:51,139 - numba.core.byteflow - DEBUG - dispatch pc=198, inst=LOAD_CONST(arg=4, lineno=600)\n", - "2024-09-12 10:50:51,139 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4', '$idx196.5']\n", - "2024-09-12 10:50:51,140 - numba.core.byteflow - DEBUG - dispatch pc=200, inst=BINARY_SUBSCR(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,140 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4', '$idx196.5', '$const198.6']\n", - "2024-09-12 10:50:51,141 - numba.core.byteflow - DEBUG - dispatch pc=202, inst=COMPARE_OP(arg=4, lineno=600)\n", - "2024-09-12 10:50:51,141 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$phi196.4', '$200binary_subscr.7']\n", - "2024-09-12 10:50:51,142 - numba.core.byteflow - DEBUG - dispatch pc=204, inst=JUMP_FORWARD(arg=2, lineno=600)\n", - "2024-09-12 10:50:51,142 - numba.core.byteflow - DEBUG - stack ['$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$202compare_op.8']\n", - "2024-09-12 10:50:51,143 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=210, stack=('$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$202compare_op.8'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,143 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=206 nstack_initial=6), State(pc_initial=168 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,144 - numba.core.byteflow - DEBUG - stack: ['$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.4', '$phi206.5']\n", - "2024-09-12 10:50:51,147 - numba.core.byteflow - DEBUG - state.pc_initial: State(pc_initial=206 nstack_initial=6)\n", - "2024-09-12 10:50:51,147 - numba.core.byteflow - DEBUG - dispatch pc=206, inst=ROT_TWO(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,148 - numba.core.byteflow - DEBUG - stack ['$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.4', '$phi206.5']\n", - "2024-09-12 10:50:51,148 - numba.core.byteflow - DEBUG - dispatch pc=208, inst=POP_TOP(arg=None, lineno=600)\n", - "2024-09-12 10:50:51,149 - numba.core.byteflow - DEBUG - stack ['$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.5', '$phi206.4']\n", - "2024-09-12 10:50:51,149 - numba.core.byteflow - DEBUG - end state. edges=[Edge(pc=210, stack=('$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.5'), blockstack=(), npush=0)]\n", - "2024-09-12 10:50:51,150 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=168 nstack_initial=4), State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,152 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,152 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5), State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,152 - numba.core.byteflow - DEBUG - pending: deque([State(pc_initial=210 nstack_initial=5)])\n", - "2024-09-12 10:50:51,153 - numba.core.byteflow - DEBUG - -------------------------Prune PHIs-------------------------\n", - "2024-09-12 10:50:51,154 - numba.core.byteflow - DEBUG - Used_phis: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): set(),\n", - " State(pc_initial=32 nstack_initial=1): {'$phi32.0'},\n", - " State(pc_initial=34 nstack_initial=2): {'$phi34.1'},\n", - " State(pc_initial=54 nstack_initial=2): {'$phi54.1'},\n", - " State(pc_initial=56 nstack_initial=3): {'$phi56.2'},\n", - " State(pc_initial=74 nstack_initial=3): {'$phi74.2'},\n", - " State(pc_initial=76 nstack_initial=4): {'$phi76.3'},\n", - " State(pc_initial=124 nstack_initial=4): set(),\n", - " State(pc_initial=136 nstack_initial=4): set(),\n", - " State(pc_initial=152 nstack_initial=5): {'$phi152.4'},\n", - " State(pc_initial=162 nstack_initial=6): set(),\n", - " State(pc_initial=166 nstack_initial=5): {'$phi166.4'},\n", - " State(pc_initial=168 nstack_initial=4): set(),\n", - " State(pc_initial=180 nstack_initial=4): set(),\n", - " State(pc_initial=196 nstack_initial=5): {'$phi196.4'},\n", - " State(pc_initial=206 nstack_initial=6): set(),\n", - " State(pc_initial=210 nstack_initial=5): {'$phi210.4', '$phi210.3'},\n", - " State(pc_initial=216 nstack_initial=2): set(),\n", - " State(pc_initial=220 nstack_initial=2): set(),\n", - " State(pc_initial=230 nstack_initial=2): set(),\n", - " State(pc_initial=232 nstack_initial=1): set(),\n", - " State(pc_initial=234 nstack_initial=0): set()})\n", - "2024-09-12 10:50:51,155 - numba.core.byteflow - DEBUG - defmap: {'$phi124.3': State(pc_initial=76 nstack_initial=4),\n", - " '$phi152.4': State(pc_initial=136 nstack_initial=4),\n", - " '$phi162.4': State(pc_initial=136 nstack_initial=4),\n", - " '$phi162.5': State(pc_initial=136 nstack_initial=4),\n", - " '$phi166.4': State(pc_initial=152 nstack_initial=5),\n", - " '$phi196.4': State(pc_initial=180 nstack_initial=4),\n", - " '$phi206.4': State(pc_initial=180 nstack_initial=4),\n", - " '$phi206.5': State(pc_initial=180 nstack_initial=4),\n", - " '$phi210.3': State(pc_initial=76 nstack_initial=4),\n", - " '$phi210.4': State(pc_initial=76 nstack_initial=4),\n", - " '$phi32.0': State(pc_initial=0 nstack_initial=0),\n", - " '$phi34.1': State(pc_initial=32 nstack_initial=1),\n", - " '$phi54.1': State(pc_initial=34 nstack_initial=2),\n", - " '$phi56.2': State(pc_initial=54 nstack_initial=2),\n", - " '$phi74.2': State(pc_initial=56 nstack_initial=3),\n", - " '$phi76.3': State(pc_initial=74 nstack_initial=3)}\n", - "2024-09-12 10:50:51,156 - numba.core.byteflow - DEBUG - phismap: defaultdict(,\n", - " {'$phi124.0': {('$phi76.0', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi124.1': {('$phi76.1', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi124.2': {('$phi76.2', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi124.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi136.0': {('$phi124.0',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi136.1': {('$phi124.1',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi136.2': {('$phi124.2',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi136.3': {('$phi124.3',\n", - " State(pc_initial=124 nstack_initial=4))},\n", - " '$phi152.0': {('$phi136.0',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi152.1': {('$phi136.1',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi152.2': {('$phi136.2',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi152.3': {('$phi136.3',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi152.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.0': {('$phi136.0',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.1': {('$phi136.1',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.2': {('$phi136.2',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.3': {('$phi136.3',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.5': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.0': {('$phi152.0',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.0',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi166.1': {('$phi152.1',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.1',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi166.2': {('$phi152.2',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.2',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi166.3': {('$phi152.3',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.3',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi166.4': {('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$phi162.5',\n", - " State(pc_initial=162 nstack_initial=6))},\n", - " '$phi168.0': {('$phi124.0',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=5))},\n", - " '$phi168.1': {('$phi124.1',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=5))},\n", - " '$phi168.2': {('$phi124.2',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi166.2',\n", - " State(pc_initial=166 nstack_initial=5))},\n", - " '$phi168.3': {('$phi124.3',\n", - " State(pc_initial=124 nstack_initial=4)),\n", - " ('$phi166.3',\n", - " State(pc_initial=166 nstack_initial=5))},\n", - " '$phi180.0': {('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=4))},\n", - " '$phi180.1': {('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=4))},\n", - " '$phi180.2': {('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=4))},\n", - " '$phi180.3': {('$phi168.3',\n", - " State(pc_initial=168 nstack_initial=4))},\n", - " '$phi196.0': {('$phi180.0',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi196.1': {('$phi180.1',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi196.2': {('$phi180.2',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi196.3': {('$phi180.3',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi196.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.0': {('$phi180.0',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.1': {('$phi180.1',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.2': {('$phi180.2',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.3': {('$phi180.3',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.5': {('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.0': {('$phi166.0',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi168.0',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$phi196.0',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi206.0',\n", - " State(pc_initial=206 nstack_initial=6)),\n", - " ('$phi76.0', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.1': {('$phi166.1',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi168.1',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$phi196.1',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi206.1',\n", - " State(pc_initial=206 nstack_initial=6)),\n", - " ('$phi76.1', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.2': {('$phi166.2',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi168.2',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$phi196.2',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi206.2',\n", - " State(pc_initial=206 nstack_initial=6)),\n", - " ('$phi76.2', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$phi166.3',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi168.3',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$phi196.3',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi206.3',\n", - " State(pc_initial=206 nstack_initial=6))},\n", - " '$phi210.4': {('$120compare_op.23',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$176compare_op.8',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$202compare_op.8',\n", - " State(pc_initial=196 nstack_initial=5)),\n", - " ('$phi166.4',\n", - " State(pc_initial=166 nstack_initial=5)),\n", - " ('$phi206.5',\n", - " State(pc_initial=206 nstack_initial=6))},\n", - " '$phi216.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi216.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi220.0': {('$phi216.0',\n", - " State(pc_initial=216 nstack_initial=2))},\n", - " '$phi220.1': {('$phi216.1',\n", - " State(pc_initial=216 nstack_initial=2))},\n", - " '$phi230.0': {('$phi216.0',\n", - " State(pc_initial=216 nstack_initial=2)),\n", - " ('$phi220.0',\n", - " State(pc_initial=220 nstack_initial=2))},\n", - " '$phi230.1': {('$phi216.1',\n", - " State(pc_initial=216 nstack_initial=2)),\n", - " ('$phi220.1',\n", - " State(pc_initial=220 nstack_initial=2))},\n", - " '$phi232.0': {('$phi54.0', State(pc_initial=54 nstack_initial=2))},\n", - " '$phi32.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi232.0',\n", - " State(pc_initial=232 nstack_initial=1))},\n", - " '$phi34.0': {('$phi32.0', State(pc_initial=32 nstack_initial=1))},\n", - " '$phi34.1': {('$32for_iter.2',\n", - " State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.0': {('$phi230.0', State(pc_initial=230 nstack_initial=2)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi54.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2)),\n", - " ('$phi230.1',\n", - " State(pc_initial=230 nstack_initial=2))},\n", - " '$phi56.0': {('$phi54.0', State(pc_initial=54 nstack_initial=2))},\n", - " '$phi56.1': {('$phi54.1', State(pc_initial=54 nstack_initial=2))},\n", - " '$phi56.2': {('$54for_iter.3',\n", - " State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.0': {('$phi210.0', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi74.1': {('$phi210.1', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi74.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3)),\n", - " ('$phi210.2',\n", - " State(pc_initial=210 nstack_initial=5))},\n", - " '$phi76.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi76.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi76.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4',\n", - " State(pc_initial=74 nstack_initial=3))}})\n", - "2024-09-12 10:50:51,161 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi124.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi124.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi124.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi124.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi136.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi136.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi136.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi136.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi152.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi152.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi152.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi162.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi162.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi162.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi162.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.5': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi166.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi166.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi166.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi166.4': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5))},\n", - " '$phi168.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi168.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi168.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi168.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi180.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi180.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi180.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi180.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi196.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi196.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi196.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi206.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi206.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi206.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi206.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.5': {('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.0': {('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi210.1': {('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi210.2': {('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi210.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.4': {('$120compare_op.23',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$176compare_op.8',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4)),\n", - " ('$202compare_op.8',\n", - " State(pc_initial=196 nstack_initial=5))},\n", - " '$phi216.0': {('$phi210.0',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi216.1': {('$phi210.1',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi220.0': {('$phi210.0',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi220.1': {('$phi210.1',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi230.0': {('$phi210.0',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi230.1': {('$phi210.1',\n", - " State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi232.0': {('$phi230.0',\n", - " State(pc_initial=230 nstack_initial=2)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi32.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi230.0', State(pc_initial=230 nstack_initial=2)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi34.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi230.0', State(pc_initial=230 nstack_initial=2)),\n", - " ('$phi34.0', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi34.1': {('$32for_iter.2',\n", - " State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi210.0', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi54.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2)),\n", - " ('$phi210.1', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi56.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi210.0', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.0', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi56.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2)),\n", - " ('$phi210.1', State(pc_initial=210 nstack_initial=5)),\n", - " ('$phi56.1', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi56.2': {('$54for_iter.3',\n", - " State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0)),\n", - " ('$phi74.0', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi74.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2)),\n", - " ('$phi74.1', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi74.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3)),\n", - " ('$phi74.2', State(pc_initial=74 nstack_initial=3))},\n", - " '$phi76.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi76.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi76.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4',\n", - " State(pc_initial=74 nstack_initial=3))}})\n", - "2024-09-12 10:50:51,166 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi124.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi124.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi124.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi124.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi136.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi136.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi136.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi136.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi152.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi152.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi152.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi162.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi162.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi162.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi162.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.5': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi166.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi166.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi166.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi166.4': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5))},\n", - " '$phi168.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi168.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi168.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi168.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi180.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi180.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi180.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi180.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi196.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi196.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi196.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi206.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi206.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi206.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi206.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.5': {('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi210.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi210.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi210.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.4': {('$120compare_op.23',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$176compare_op.8',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4)),\n", - " ('$202compare_op.8',\n", - " State(pc_initial=196 nstack_initial=5))},\n", - " '$phi216.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi216.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi220.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi220.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi230.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi230.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi232.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi32.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.1': {('$32for_iter.2',\n", - " State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi54.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi56.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.2': {('$54for_iter.3',\n", - " State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi74.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi74.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi76.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi76.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4',\n", - " State(pc_initial=74 nstack_initial=3))}})\n", - "2024-09-12 10:50:51,170 - numba.core.byteflow - DEBUG - changing phismap: defaultdict(,\n", - " {'$phi124.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi124.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi124.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi124.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi136.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi136.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi136.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi136.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi152.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi152.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi152.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi152.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi162.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi162.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi162.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi162.4': {('$144dup_top.8',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi162.5': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi166.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi166.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi166.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi166.4': {('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5))},\n", - " '$phi168.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi168.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi168.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi168.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi180.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi180.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi180.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi180.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi196.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi196.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi196.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi196.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi206.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi206.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi206.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi206.4': {('$188dup_top.8',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi206.5': {('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi210.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi210.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi210.3': {('$match98.12',\n", - " State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.4': {('$120compare_op.23',\n", - " State(pc_initial=76 nstack_initial=4)),\n", - " ('$148compare_op.9',\n", - " State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8',\n", - " State(pc_initial=152 nstack_initial=5)),\n", - " ('$176compare_op.8',\n", - " State(pc_initial=168 nstack_initial=4)),\n", - " ('$192compare_op.9',\n", - " State(pc_initial=180 nstack_initial=4)),\n", - " ('$202compare_op.8',\n", - " State(pc_initial=196 nstack_initial=5))},\n", - " '$phi216.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi216.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi220.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi220.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi230.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi230.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi232.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi32.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.1': {('$32for_iter.2',\n", - " State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi54.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi56.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.2': {('$54for_iter.3',\n", - " State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi74.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi74.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.0': {('$30get_iter.13',\n", - " State(pc_initial=0 nstack_initial=0))},\n", - " '$phi76.1': {('$52get_iter.10',\n", - " State(pc_initial=34 nstack_initial=2))},\n", - " '$phi76.2': {('$72get_iter.9',\n", - " State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4',\n", - " State(pc_initial=74 nstack_initial=3))}})\n", - "2024-09-12 10:50:51,175 - numba.core.byteflow - DEBUG - keep phismap: {'$phi152.4': {('$144dup_top.8', State(pc_initial=136 nstack_initial=4))},\n", - " '$phi166.4': {('$148compare_op.9', State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8', State(pc_initial=152 nstack_initial=5))},\n", - " '$phi196.4': {('$188dup_top.8', State(pc_initial=180 nstack_initial=4))},\n", - " '$phi210.3': {('$match98.12', State(pc_initial=76 nstack_initial=4))},\n", - " '$phi210.4': {('$120compare_op.23', State(pc_initial=76 nstack_initial=4)),\n", - " ('$148compare_op.9', State(pc_initial=136 nstack_initial=4)),\n", - " ('$158compare_op.8', State(pc_initial=152 nstack_initial=5)),\n", - " ('$176compare_op.8', State(pc_initial=168 nstack_initial=4)),\n", - " ('$192compare_op.9', State(pc_initial=180 nstack_initial=4)),\n", - " ('$202compare_op.8', State(pc_initial=196 nstack_initial=5))},\n", - " '$phi32.0': {('$30get_iter.13', State(pc_initial=0 nstack_initial=0))},\n", - " '$phi34.1': {('$32for_iter.2', State(pc_initial=32 nstack_initial=1))},\n", - " '$phi54.1': {('$52get_iter.10', State(pc_initial=34 nstack_initial=2))},\n", - " '$phi56.2': {('$54for_iter.3', State(pc_initial=54 nstack_initial=2))},\n", - " '$phi74.2': {('$72get_iter.9', State(pc_initial=56 nstack_initial=3))},\n", - " '$phi76.3': {('$74for_iter.4', State(pc_initial=74 nstack_initial=3))}}\n", - "2024-09-12 10:50:51,177 - numba.core.byteflow - DEBUG - new_out: defaultdict(,\n", - " {State(pc_initial=0 nstack_initial=0): {'$phi32.0': '$30get_iter.13'},\n", - " State(pc_initial=32 nstack_initial=1): {'$phi34.1': '$32for_iter.2'},\n", - " State(pc_initial=34 nstack_initial=2): {'$phi54.1': '$52get_iter.10'},\n", - " State(pc_initial=54 nstack_initial=2): {'$phi56.2': '$54for_iter.3'},\n", - " State(pc_initial=56 nstack_initial=3): {'$phi74.2': '$72get_iter.9'},\n", - " State(pc_initial=74 nstack_initial=3): {'$phi76.3': '$74for_iter.4'},\n", - " State(pc_initial=76 nstack_initial=4): {'$phi210.3': '$match98.12',\n", - " '$phi210.4': '$120compare_op.23'},\n", - " State(pc_initial=136 nstack_initial=4): {'$phi152.4': '$144dup_top.8',\n", - " '$phi166.4': '$148compare_op.9',\n", - " '$phi210.4': '$148compare_op.9'},\n", - " State(pc_initial=152 nstack_initial=5): {'$phi166.4': '$158compare_op.8',\n", - " '$phi210.4': '$158compare_op.8'},\n", - " State(pc_initial=168 nstack_initial=4): {'$phi210.4': '$176compare_op.8'},\n", - " State(pc_initial=180 nstack_initial=4): {'$phi196.4': '$188dup_top.8',\n", - " '$phi210.4': '$192compare_op.9'},\n", - " State(pc_initial=196 nstack_initial=5): {'$phi210.4': '$202compare_op.8'}})\n", - "2024-09-12 10:50:51,179 - numba.core.byteflow - DEBUG - ----------------------DONE Prune PHIs-----------------------\n", - "2024-09-12 10:50:51,179 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=0 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((0, {}), (2, {'res': '$2load_global.0'}), (4, {'item': '$2load_global.0', 'res': '$4load_attr.1'}), (6, {'item': '$4load_attr.1', 'res': '$6load_attr.2'}), (8, {'item': '$6load_attr.2', 'res': '$8load_method.3'}), (10, {'res': '$10load_global.4'}), (12, {'item': '$10load_global.4', 'res': '$12load_attr.5'}), (14, {'item': '$12load_attr.5', 'res': '$14load_attr.6'}), (16, {'func': '$8load_method.3', 'args': ['$14load_attr.6'], 'res': '$16call_method.7'}), (18, {'value': '$16call_method.7'}), (20, {'res': '$20load_global.8'}), (22, {'res': '$22load_global.9'}), (24, {'res': '$starts24.10'}), (26, {'func': '$22load_global.9', 'args': ['$starts24.10'], 'res': '$26call_function.11'}), (28, {'func': '$20load_global.8', 'args': ['$26call_function.11'], 'res': '$28call_function.12'}), (30, {'value': '$28call_function.12', 'res': '$30get_iter.13'})), outgoing_phis={'$phi32.0': '$30get_iter.13'}, blockstack=(), active_try_block=None, outgoing_edgepushed={32: ('$30get_iter.13',)})\n", - "2024-09-12 10:50:51,180 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=32 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((32, {'iterator': '$phi32.0', 'pair': '$32for_iter.1', 'indval': '$32for_iter.2', 'pred': '$32for_iter.3'}),), outgoing_phis={'$phi34.1': '$32for_iter.2'}, blockstack=(), active_try_block=None, outgoing_edgepushed={234: (), 34: ('$phi32.0', '$32for_iter.2')})\n", - "2024-09-12 10:50:51,181 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=34 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((34, {'value': '$phi34.1'}), (36, {'res': '$36load_global.2'}), (38, {'res': '$starts38.3'}), (40, {'res': '$i40.4'}), (42, {'index': '$i40.4', 'target': '$starts38.3', 'res': '$42binary_subscr.5'}), (44, {'res': '$stops44.6'}), (46, {'res': '$i46.7'}), (48, {'index': '$i46.7', 'target': '$stops44.6', 'res': '$48binary_subscr.8'}), (50, {'func': '$36load_global.2', 'args': ['$42binary_subscr.5', '$48binary_subscr.8'], 'res': '$50call_function.9'}), (52, {'value': '$50call_function.9', 'res': '$52get_iter.10'})), outgoing_phis={'$phi54.1': '$52get_iter.10'}, blockstack=(), active_try_block=None, outgoing_edgepushed={54: ('$phi34.0', '$52get_iter.10')})\n", - "2024-09-12 10:50:51,182 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=54 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((54, {'iterator': '$phi54.1', 'pair': '$54for_iter.2', 'indval': '$54for_iter.3', 'pred': '$54for_iter.4'}),), outgoing_phis={'$phi56.2': '$54for_iter.3'}, blockstack=(), active_try_block=None, outgoing_edgepushed={232: ('$phi54.0',), 56: ('$phi54.0', '$phi54.1', '$54for_iter.3')})\n", - "2024-09-12 10:50:51,183 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=56 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((56, {'value': '$phi56.2'}), (58, {'res': '$const58.3'}), (60, {'value': '$const58.3'}), (62, {'res': '$62load_global.4'}), (64, {'res': '$64load_global.5'}), (66, {'res': '$indices66.6'}), (68, {'func': '$64load_global.5', 'args': ['$indices66.6'], 'res': '$68call_function.7'}), (70, {'func': '$62load_global.4', 'args': ['$68call_function.7'], 'res': '$70call_function.8'}), (72, {'value': '$70call_function.8', 'res': '$72get_iter.9'})), outgoing_phis={'$phi74.2': '$72get_iter.9'}, blockstack=(), active_try_block=None, outgoing_edgepushed={74: ('$phi56.0', '$phi56.1', '$72get_iter.9')})\n", - "2024-09-12 10:50:51,183 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=74 nstack_initial=3):\n", - "AdaptBlockInfo(insts=((74, {'iterator': '$phi74.2', 'pair': '$74for_iter.3', 'indval': '$74for_iter.4', 'pred': '$74for_iter.5'}),), outgoing_phis={'$phi76.3': '$74for_iter.4'}, blockstack=(), active_try_block=None, outgoing_edgepushed={216: ('$phi74.0', '$phi74.1'), 76: ('$phi74.0', '$phi74.1', '$phi74.2', '$74for_iter.4')})\n", - "2024-09-12 10:50:51,184 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=76 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((76, {'value': '$phi76.3'}), (78, {'res': '$indices78.4'}), (80, {'res': '$k80.5'}), (82, {'index': '$k80.5', 'target': '$indices78.4', 'res': '$82binary_subscr.6'}), (84, {'value': '$82binary_subscr.6'}), (86, {'res': '$coords86.7'}), (88, {'res': '$k88.8'}), (90, {'res': '$j90.9'}), (92, {'items': ['$k88.8', '$j90.9'], 'res': '$92build_tuple.10'}), (94, {'index': '$92build_tuple.10', 'target': '$coords86.7', 'res': '$94binary_subscr.11'}), (96, {'value': '$94binary_subscr.11'}), (98, {'res': '$match98.12'}), (100, {'res': '$elem100.13'}), (102, {'res': '$idx102.14'}), (104, {'res': '$const104.15'}), (106, {'index': '$const104.15', 'target': '$idx102.14', 'res': '$106binary_subscr.16'}), (108, {'lhs': '$elem100.13', 'rhs': '$106binary_subscr.16', 'res': '$108binary_subtract.17'}), (110, {'res': '$idx110.18'}), (112, {'res': '$const112.19'}), (114, {'index': '$const112.19', 'target': '$idx110.18', 'res': '$114binary_subscr.20'}), (116, {'lhs': '$108binary_subtract.17', 'rhs': '$114binary_subscr.20', 'res': '$116binary_modulo.21'}), (118, {'res': '$const118.22'}), (120, {'lhs': '$116binary_modulo.21', 'rhs': '$const118.22', 'res': '$120compare_op.23'}), (122, {'pred': '$120compare_op.23'})), outgoing_phis={'$phi210.4': '$120compare_op.23', '$phi210.3': '$match98.12'}, blockstack=(), active_try_block=None, outgoing_edgepushed={124: ('$phi76.0', '$phi76.1', '$phi76.2', '$match98.12'), 210: ('$phi76.0', '$phi76.1', '$phi76.2', '$match98.12', '$120compare_op.23')})\n", - "2024-09-12 10:50:51,184 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=124 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((124, {'res': '$idx124.4'}), (126, {'res': '$const126.5'}), (128, {'index': '$const126.5', 'target': '$idx124.4', 'res': '$128binary_subscr.6'}), (130, {'res': '$const130.7'}), (132, {'lhs': '$128binary_subscr.6', 'rhs': '$const130.7', 'res': '$132compare_op.8'}), (134, {'pred': '$132compare_op.8'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={136: ('$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3'), 168: ('$phi124.0', '$phi124.1', '$phi124.2', '$phi124.3')})\n", - "2024-09-12 10:50:51,185 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=136 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((136, {'res': '$idx136.4'}), (138, {'res': '$const138.5'}), (140, {'index': '$const138.5', 'target': '$idx136.4', 'res': '$140binary_subscr.6'}), (142, {'res': '$elem142.7'}), (144, {'orig': ['$elem142.7'], 'duped': ['$144dup_top.8']}), (148, {'lhs': '$140binary_subscr.6', 'rhs': '$elem142.7', 'res': '$148compare_op.9'}), (150, {'pred': '$148compare_op.9'})), outgoing_phis={'$phi210.4': '$148compare_op.9', '$phi166.4': '$148compare_op.9', '$phi152.4': '$144dup_top.8'}, blockstack=(), active_try_block=None, outgoing_edgepushed={152: ('$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8'), 162: ('$phi136.0', '$phi136.1', '$phi136.2', '$phi136.3', '$144dup_top.8', '$148compare_op.9')})\n", - "2024-09-12 10:50:51,186 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=152 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((152, {'res': '$idx152.5'}), (154, {'res': '$const154.6'}), (156, {'index': '$const154.6', 'target': '$idx152.5', 'res': '$156binary_subscr.7'}), (158, {'lhs': '$phi152.4', 'rhs': '$156binary_subscr.7', 'res': '$158compare_op.8'}), (160, {})), outgoing_phis={'$phi210.4': '$158compare_op.8', '$phi166.4': '$158compare_op.8'}, blockstack=(), active_try_block=None, outgoing_edgepushed={166: ('$phi152.0', '$phi152.1', '$phi152.2', '$phi152.3', '$158compare_op.8')})\n", - "2024-09-12 10:50:51,187 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=162 nstack_initial=6):\n", - "AdaptBlockInfo(insts=(), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={166: ('$phi162.0', '$phi162.1', '$phi162.2', '$phi162.3', '$phi162.5')})\n", - "2024-09-12 10:50:51,188 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=166 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((166, {'pred': '$phi166.4'}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={168: ('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3'), 210: ('$phi166.0', '$phi166.1', '$phi166.2', '$phi166.3', '$phi166.4')})\n", - "2024-09-12 10:50:51,188 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=168 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((168, {'res': '$idx168.4'}), (170, {'res': '$const170.5'}), (172, {'index': '$const170.5', 'target': '$idx168.4', 'res': '$172binary_subscr.6'}), (174, {'res': '$const174.7'}), (176, {'lhs': '$172binary_subscr.6', 'rhs': '$const174.7', 'res': '$176compare_op.8'}), (178, {'pred': '$176compare_op.8'})), outgoing_phis={'$phi210.4': '$176compare_op.8'}, blockstack=(), active_try_block=None, outgoing_edgepushed={180: ('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3'), 210: ('$phi168.0', '$phi168.1', '$phi168.2', '$phi168.3', '$176compare_op.8')})\n", - "2024-09-12 10:50:51,189 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=180 nstack_initial=4):\n", - "AdaptBlockInfo(insts=((180, {'res': '$idx180.4'}), (182, {'res': '$const182.5'}), (184, {'index': '$const182.5', 'target': '$idx180.4', 'res': '$184binary_subscr.6'}), (186, {'res': '$elem186.7'}), (188, {'orig': ['$elem186.7'], 'duped': ['$188dup_top.8']}), (192, {'lhs': '$184binary_subscr.6', 'rhs': '$elem186.7', 'res': '$192compare_op.9'}), (194, {'pred': '$192compare_op.9'})), outgoing_phis={'$phi196.4': '$188dup_top.8', '$phi210.4': '$192compare_op.9'}, blockstack=(), active_try_block=None, outgoing_edgepushed={196: ('$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8'), 206: ('$phi180.0', '$phi180.1', '$phi180.2', '$phi180.3', '$188dup_top.8', '$192compare_op.9')})\n", - "2024-09-12 10:50:51,189 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=196 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((196, {'res': '$idx196.5'}), (198, {'res': '$const198.6'}), (200, {'index': '$const198.6', 'target': '$idx196.5', 'res': '$200binary_subscr.7'}), (202, {'lhs': '$phi196.4', 'rhs': '$200binary_subscr.7', 'res': '$202compare_op.8'}), (204, {})), outgoing_phis={'$phi210.4': '$202compare_op.8'}, blockstack=(), active_try_block=None, outgoing_edgepushed={210: ('$phi196.0', '$phi196.1', '$phi196.2', '$phi196.3', '$202compare_op.8')})\n", - "2024-09-12 10:50:51,190 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=206 nstack_initial=6):\n", - "AdaptBlockInfo(insts=(), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={210: ('$phi206.0', '$phi206.1', '$phi206.2', '$phi206.3', '$phi206.5')})\n", - "2024-09-12 10:50:51,190 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=210 nstack_initial=5):\n", - "AdaptBlockInfo(insts=((210, {'lhs': '$phi210.3', 'rhs': '$phi210.4', 'res': '$210inplace_and.5'}), (212, {'value': '$210inplace_and.5'}), (214, {})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={74: ('$phi210.0', '$phi210.1', '$phi210.2')})\n", - "2024-09-12 10:50:51,191 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=216 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((216, {'res': '$match216.2'}), (218, {'pred': '$match216.2'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={220: ('$phi216.0', '$phi216.1'), 230: ('$phi216.0', '$phi216.1')})\n", - "2024-09-12 10:50:51,191 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=220 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((220, {'res': '$mask220.2'}), (222, {'item': '$mask220.2', 'res': '$222load_method.3'}), (224, {'res': '$j224.4'}), (226, {'func': '$222load_method.3', 'args': ['$j224.4'], 'res': '$226call_method.5'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={230: ('$phi220.0', '$phi220.1')})\n", - "2024-09-12 10:50:51,193 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=230 nstack_initial=2):\n", - "AdaptBlockInfo(insts=((230, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={54: ('$phi230.0', '$phi230.1')})\n", - "2024-09-12 10:50:51,194 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=232 nstack_initial=1):\n", - "AdaptBlockInfo(insts=((232, {}),), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={32: ('$phi232.0',)})\n", - "2024-09-12 10:50:51,194 - numba.core.byteflow - DEBUG - block_infos State(pc_initial=234 nstack_initial=0):\n", - "AdaptBlockInfo(insts=((234, {'res': '$mask234.0'}), (236, {'retval': '$mask234.0', 'castval': '$236return_value.1'})), outgoing_phis={}, blockstack=(), active_try_block=None, outgoing_edgepushed={})\n", - "2024-09-12 10:50:51,203 - numba.core.interpreter - DEBUG - label 0:\n", - " starts = arg(0, name=starts) ['starts']\n", - " stops = arg(1, name=stops) ['stops']\n", - " coords = arg(2, name=coords) ['coords']\n", - " indices = arg(3, name=indices) ['indices']\n", - " $2load_global.0 = global(numba: ) ['$2load_global.0']\n", - " $4load_attr.1 = getattr(value=$2load_global.0, attr=typed) ['$2load_global.0', '$4load_attr.1']\n", - " $6load_attr.2 = getattr(value=$4load_attr.1, attr=List) ['$4load_attr.1', '$6load_attr.2']\n", - " $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list) ['$6load_attr.2', '$8load_method.3']\n", - " $10load_global.4 = global(numba: ) ['$10load_global.4']\n", - " $12load_attr.5 = getattr(value=$10load_global.4, attr=types) ['$10load_global.4', '$12load_attr.5']\n", - " $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp) ['$12load_attr.5', '$14load_attr.6']\n", - " mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None) ['$14load_attr.6', '$8load_method.3', 'mask']\n", - " $20load_global.8 = global(range: ) ['$20load_global.8']\n", - " $22load_global.9 = global(len: ) ['$22load_global.9']\n", - " $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None) ['$22load_global.9', '$26call_function.11', 'starts']\n", - " $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None) ['$20load_global.8', '$26call_function.11', '$28call_function.12']\n", - " $30get_iter.13 = getiter(value=$28call_function.12) ['$28call_function.12', '$30get_iter.13']\n", - " $phi32.0 = $30get_iter.13 ['$30get_iter.13', '$phi32.0']\n", - " jump 32 []\n", - "label 32:\n", - " $32for_iter.1 = iternext(value=$phi32.0) ['$32for_iter.1', '$phi32.0']\n", - " $32for_iter.2 = pair_first(value=$32for_iter.1) ['$32for_iter.1', '$32for_iter.2']\n", - " $32for_iter.3 = pair_second(value=$32for_iter.1) ['$32for_iter.1', '$32for_iter.3']\n", - " $phi34.1 = $32for_iter.2 ['$32for_iter.2', '$phi34.1']\n", - " branch $32for_iter.3, 34, 234 ['$32for_iter.3']\n", - "label 34:\n", - " i = $phi34.1 ['$phi34.1', 'i']\n", - " $36load_global.2 = global(range: ) ['$36load_global.2']\n", - " $42binary_subscr.5 = getitem(value=starts, index=i, fn=) ['$42binary_subscr.5', 'i', 'starts']\n", - " $48binary_subscr.8 = getitem(value=stops, index=i, fn=) ['$48binary_subscr.8', 'i', 'stops']\n", - " $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None) ['$36load_global.2', '$42binary_subscr.5', '$48binary_subscr.8', '$50call_function.9']\n", - " $52get_iter.10 = getiter(value=$50call_function.9) ['$50call_function.9', '$52get_iter.10']\n", - " $phi54.1 = $52get_iter.10 ['$52get_iter.10', '$phi54.1']\n", - " jump 54 []\n", - "label 54:\n", - " $54for_iter.2 = iternext(value=$phi54.1) ['$54for_iter.2', '$phi54.1']\n", - " $54for_iter.3 = pair_first(value=$54for_iter.2) ['$54for_iter.2', '$54for_iter.3']\n", - " $54for_iter.4 = pair_second(value=$54for_iter.2) ['$54for_iter.2', '$54for_iter.4']\n", - " $phi56.2 = $54for_iter.3 ['$54for_iter.3', '$phi56.2']\n", - " branch $54for_iter.4, 56, 232 ['$54for_iter.4']\n", - "label 56:\n", - " j = $phi56.2 ['$phi56.2', 'j']\n", - " match = const(bool, True) ['match']\n", - " $62load_global.4 = global(range: ) ['$62load_global.4']\n", - " $64load_global.5 = global(len: ) ['$64load_global.5']\n", - " $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None) ['$64load_global.5', '$68call_function.7', 'indices']\n", - " $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None) ['$62load_global.4', '$68call_function.7', '$70call_function.8']\n", - " $72get_iter.9 = getiter(value=$70call_function.8) ['$70call_function.8', '$72get_iter.9']\n", - " $phi74.2 = $72get_iter.9 ['$72get_iter.9', '$phi74.2']\n", - " jump 74 []\n", - "label 74:\n", - " $74for_iter.3 = iternext(value=$phi74.2) ['$74for_iter.3', '$phi74.2']\n", - " $74for_iter.4 = pair_first(value=$74for_iter.3) ['$74for_iter.3', '$74for_iter.4']\n", - " $74for_iter.5 = pair_second(value=$74for_iter.3) ['$74for_iter.3', '$74for_iter.5']\n", - " $phi76.3 = $74for_iter.4 ['$74for_iter.4', '$phi76.3']\n", - " branch $74for_iter.5, 76, 216 ['$74for_iter.5']\n", - "label 76:\n", - " k = $phi76.3 ['$phi76.3', 'k']\n", - " idx = getitem(value=indices, index=k, fn=) ['idx', 'indices', 'k']\n", - " $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)]) ['$92build_tuple.10', 'j', 'k']\n", - " elem = getitem(value=coords, index=$92build_tuple.10, fn=) ['$92build_tuple.10', 'coords', 'elem']\n", - " $const104.15 = const(int, 0) ['$const104.15']\n", - " $106binary_subscr.16 = getitem(value=idx, index=$const104.15, fn=) ['$106binary_subscr.16', '$const104.15', 'idx']\n", - " $108binary_subtract.17 = elem - $106binary_subscr.16 ['$106binary_subscr.16', '$108binary_subtract.17', 'elem']\n", - " $const112.19 = const(int, 2) ['$const112.19']\n", - " $114binary_subscr.20 = getitem(value=idx, index=$const112.19, fn=) ['$114binary_subscr.20', '$const112.19', 'idx']\n", - " $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20 ['$108binary_subtract.17', '$114binary_subscr.20', '$116binary_modulo.21']\n", - " $const118.22 = const(int, 0) ['$const118.22']\n", - " $120compare_op.23 = $116binary_modulo.21 == $const118.22 ['$116binary_modulo.21', '$120compare_op.23', '$const118.22']\n", - " bool122 = global(bool: ) ['bool122']\n", - " $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None) ['$120compare_op.23', '$122pred', 'bool122']\n", - " $phi210.4 = $120compare_op.23 ['$120compare_op.23', '$phi210.4']\n", - " $phi210.3 = match ['$phi210.3', 'match']\n", - " branch $122pred, 124, 210 ['$122pred']\n", - "label 124:\n", - " $const126.5 = const(int, 2) ['$const126.5']\n", - " $128binary_subscr.6 = getitem(value=idx, index=$const126.5, fn=) ['$128binary_subscr.6', '$const126.5', 'idx']\n", - " $const130.7 = const(int, 0) ['$const130.7']\n", - " $132compare_op.8 = $128binary_subscr.6 > $const130.7 ['$128binary_subscr.6', '$132compare_op.8', '$const130.7']\n", - " bool134 = global(bool: ) ['bool134']\n", - " $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$132compare_op.8', '$134pred', 'bool134']\n", - " branch $134pred, 136, 168 ['$134pred']\n", - "label 136:\n", - " $const138.5 = const(int, 0) ['$const138.5']\n", - " $140binary_subscr.6 = getitem(value=idx, index=$const138.5, fn=) ['$140binary_subscr.6', '$const138.5', 'idx']\n", - " $148compare_op.9 = $140binary_subscr.6 <= elem ['$140binary_subscr.6', '$148compare_op.9', 'elem']\n", - " bool150 = global(bool: ) ['bool150']\n", - " $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$148compare_op.9', '$150pred', 'bool150']\n", - " $phi210.4 = $148compare_op.9 ['$148compare_op.9', '$phi210.4']\n", - " $phi166.4 = $148compare_op.9 ['$148compare_op.9', '$phi166.4']\n", - " $phi152.4 = elem ['$phi152.4', 'elem']\n", - " branch $150pred, 152, 162 ['$150pred']\n", - "label 152:\n", - " $const154.6 = const(int, 1) ['$const154.6']\n", - " $156binary_subscr.7 = getitem(value=idx, index=$const154.6, fn=) ['$156binary_subscr.7', '$const154.6', 'idx']\n", - " $158compare_op.8 = $phi152.4 < $156binary_subscr.7 ['$156binary_subscr.7', '$158compare_op.8', '$phi152.4']\n", - " $phi210.4 = $158compare_op.8 ['$158compare_op.8', '$phi210.4']\n", - " $phi166.4 = $158compare_op.8 ['$158compare_op.8', '$phi166.4']\n", - " jump 166 []\n", - "label 162:\n", - " jump 166 []\n", - "label 166:\n", - " bool166 = global(bool: ) ['bool166']\n", - " $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$166pred', '$phi166.4', 'bool166']\n", - " branch $166pred, 210, 168 ['$166pred']\n", - "label 168:\n", - " $const170.5 = const(int, 2) ['$const170.5']\n", - " $172binary_subscr.6 = getitem(value=idx, index=$const170.5, fn=) ['$172binary_subscr.6', '$const170.5', 'idx']\n", - " $const174.7 = const(int, 0) ['$const174.7']\n", - " $176compare_op.8 = $172binary_subscr.6 < $const174.7 ['$172binary_subscr.6', '$176compare_op.8', '$const174.7']\n", - " bool178 = global(bool: ) ['bool178']\n", - " $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$176compare_op.8', '$178pred', 'bool178']\n", - " $phi210.4 = $176compare_op.8 ['$176compare_op.8', '$phi210.4']\n", - " branch $178pred, 180, 210 ['$178pred']\n", - "label 180:\n", - " $const182.5 = const(int, 0) ['$const182.5']\n", - " $184binary_subscr.6 = getitem(value=idx, index=$const182.5, fn=) ['$184binary_subscr.6', '$const182.5', 'idx']\n", - " $192compare_op.9 = $184binary_subscr.6 >= elem ['$184binary_subscr.6', '$192compare_op.9', 'elem']\n", - " bool194 = global(bool: ) ['bool194']\n", - " $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None) ['$192compare_op.9', '$194pred', 'bool194']\n", - " $phi196.4 = elem ['$phi196.4', 'elem']\n", - " $phi210.4 = $192compare_op.9 ['$192compare_op.9', '$phi210.4']\n", - " branch $194pred, 196, 206 ['$194pred']\n", - "label 196:\n", - " $const198.6 = const(int, 1) ['$const198.6']\n", - " $200binary_subscr.7 = getitem(value=idx, index=$const198.6, fn=) ['$200binary_subscr.7', '$const198.6', 'idx']\n", - " $202compare_op.8 = $phi196.4 > $200binary_subscr.7 ['$200binary_subscr.7', '$202compare_op.8', '$phi196.4']\n", - " $phi210.4 = $202compare_op.8 ['$202compare_op.8', '$phi210.4']\n", - " jump 210 []\n", - "label 206:\n", - " jump 210 []\n", - "label 210:\n", - " match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined) ['$phi210.3', '$phi210.4', 'match']\n", - " jump 74 []\n", - "label 216:\n", - " bool218 = global(bool: ) ['bool218']\n", - " $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None) ['$218pred', 'bool218', 'match']\n", - " branch $218pred, 220, 230 ['$218pred']\n", - "label 220:\n", - " $222load_method.3 = getattr(value=mask, attr=append) ['$222load_method.3', 'mask']\n", - " $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None) ['$222load_method.3', '$226call_method.5', 'j']\n", - " jump 230 []\n", - "label 230:\n", - " jump 54 []\n", - "label 232:\n", - " jump 32 []\n", - "label 234:\n", - " $236return_value.1 = cast(value=mask) ['$236return_value.1', 'mask']\n", - " return $236return_value.1 ['$236return_value.1']\n", - "\n", - "2024-09-12 10:50:51,252 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 0\n", - "2024-09-12 10:50:51,254 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,254 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:51,255 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:51,256 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:51,257 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:51,257 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:51,258 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:51,259 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:51,260 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:51,260 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:51,261 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:51,262 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:51,262 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,263 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:51,264 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:51,265 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,265 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,266 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:51,267 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:51,267 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,268 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 32\n", - "2024-09-12 10:50:51,269 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,269 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:51,270 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,271 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,271 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:51,272 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:51,273 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 34\n", - "2024-09-12 10:50:51,273 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,274 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:51,275 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:51,275 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:51,276 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:51,277 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,278 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:51,278 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:51,279 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,280 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 54\n", - "2024-09-12 10:50:51,281 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,281 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:51,282 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,283 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,284 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:51,284 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:51,285 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 56\n", - "2024-09-12 10:50:51,286 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,286 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:51,287 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:51,301 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:51,302 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:51,303 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,303 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,304 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:51,305 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:51,306 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,306 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 74\n", - "2024-09-12 10:50:51,307 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,308 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:51,308 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,309 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,310 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:51,311 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:51,311 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 76\n", - "2024-09-12 10:50:51,312 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,313 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:51,313 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:51,314 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:51,315 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:51,316 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:51,316 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:51,317 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:51,318 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:51,319 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:51,319 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:51,320 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:51,321 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:51,321 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:51,322 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,323 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:51,324 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:51,324 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:51,325 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 124\n", - "2024-09-12 10:50:51,326 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,326 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:51,327 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:51,328 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:51,329 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:51,329 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:51,330 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,331 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:51,331 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 136\n", - "2024-09-12 10:50:51,332 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,333 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:51,333 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:51,334 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:51,335 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:51,335 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,336 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,337 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,337 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:51,338 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:51,339 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 152\n", - "2024-09-12 10:50:51,339 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,340 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:51,341 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:51,341 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:51,342 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $158compare_op.8\n", - "2024-09-12 10:50:51,342 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $158compare_op.8\n", - "2024-09-12 10:50:51,343 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,344 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 162\n", - "2024-09-12 10:50:51,344 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,345 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,346 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 166\n", - "2024-09-12 10:50:51,346 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,347 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:51,348 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,349 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:51,349 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 168\n", - "2024-09-12 10:50:51,350 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,351 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:51,351 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:51,352 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:51,353 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:51,353 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:51,354 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,355 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $176compare_op.8\n", - "2024-09-12 10:50:51,355 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:51,356 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 180\n", - "2024-09-12 10:50:51,357 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,357 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:51,358 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:51,359 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:51,359 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:51,360 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,361 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:51,362 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $192compare_op.9\n", - "2024-09-12 10:50:51,362 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:51,363 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 196\n", - "2024-09-12 10:50:51,364 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,364 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:51,365 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:51,366 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:51,366 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $202compare_op.8\n", - "2024-09-12 10:50:51,367 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,368 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 206\n", - "2024-09-12 10:50:51,368 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,369 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,370 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 210\n", - "2024-09-12 10:50:51,370 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,371 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:51,372 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,372 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 216\n", - "2024-09-12 10:50:51,373 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,374 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:51,374 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,375 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:51,376 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 220\n", - "2024-09-12 10:50:51,376 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,377 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:51,378 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,379 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:51,379 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 230\n", - "2024-09-12 10:50:51,380 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,381 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,381 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 232\n", - "2024-09-12 10:50:51,382 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,382 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,383 - numba.core.ssa - DEBUG - ==== SSA block analysis pass on 234\n", - "2024-09-12 10:50:51,384 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,384 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:51,385 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:51,388 - numba.core.ssa - DEBUG - defs defaultdict(,\n", - " {'$106binary_subscr.16': [],\n", - " '$108binary_subtract.17': [],\n", - " '$10load_global.4': [],\n", - " '$114binary_subscr.20': [],\n", - " '$116binary_modulo.21': [],\n", - " '$120compare_op.23': [],\n", - " '$122pred': [],\n", - " '$128binary_subscr.6': [],\n", - " '$12load_attr.5': [],\n", - " '$132compare_op.8': [],\n", - " '$134pred': [],\n", - " '$140binary_subscr.6': [],\n", - " '$148compare_op.9': [],\n", - " '$14load_attr.6': [],\n", - " '$150pred': [],\n", - " '$156binary_subscr.7': [],\n", - " '$158compare_op.8': [],\n", - " '$166pred': [],\n", - " '$172binary_subscr.6': [],\n", - " '$176compare_op.8': [],\n", - " '$178pred': [],\n", - " '$184binary_subscr.6': [],\n", - " '$192compare_op.9': [],\n", - " '$194pred': [],\n", - " '$200binary_subscr.7': [],\n", - " '$202compare_op.8': [],\n", - " '$20load_global.8': [],\n", - " '$218pred': [],\n", - " '$222load_method.3': [],\n", - " '$226call_method.5': [],\n", - " '$22load_global.9': [],\n", - " '$236return_value.1': [],\n", - " '$26call_function.11': [],\n", - " '$28call_function.12': [],\n", - " '$2load_global.0': [],\n", - " '$30get_iter.13': [],\n", - " '$32for_iter.1': [],\n", - " '$32for_iter.2': [],\n", - " '$32for_iter.3': [],\n", - " '$36load_global.2': [],\n", - " '$42binary_subscr.5': [],\n", - " '$48binary_subscr.8': [],\n", - " '$4load_attr.1': [],\n", - " '$50call_function.9': [],\n", - " '$52get_iter.10': [],\n", - " '$54for_iter.2': [],\n", - " '$54for_iter.3': [],\n", - " '$54for_iter.4': [],\n", - " '$62load_global.4': [],\n", - " '$64load_global.5': [],\n", - " '$68call_function.7': [],\n", - " '$6load_attr.2': [],\n", - " '$70call_function.8': [],\n", - " '$72get_iter.9': [],\n", - " '$74for_iter.3': [],\n", - " '$74for_iter.4': [],\n", - " '$74for_iter.5': [],\n", - " '$8load_method.3': [],\n", - " '$92build_tuple.10': [],\n", - " '$const104.15': [],\n", - " '$const112.19': [],\n", - " '$const118.22': [],\n", - " '$const126.5': [],\n", - " '$const130.7': [],\n", - " '$const138.5': [],\n", - " '$const154.6': [],\n", - " '$const170.5': [],\n", - " '$const174.7': [],\n", - " '$const182.5': [],\n", - " '$const198.6': [],\n", - " '$phi152.4': [],\n", - " '$phi166.4': [,\n", - " ],\n", - " '$phi196.4': [],\n", - " '$phi210.3': [],\n", - " '$phi210.4': [,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ],\n", - " '$phi32.0': [],\n", - " '$phi34.1': [],\n", - " '$phi54.1': [],\n", - " '$phi56.2': [],\n", - " '$phi74.2': [],\n", - " '$phi76.3': [],\n", - " 'bool122': [],\n", - " 'bool134': [],\n", - " 'bool150': [],\n", - " 'bool166': [],\n", - " 'bool178': [],\n", - " 'bool194': [],\n", - " 'bool218': [],\n", - " 'coords': [],\n", - " 'elem': [],\n", - " 'i': [],\n", - " 'idx': [],\n", - " 'indices': [],\n", - " 'j': [],\n", - " 'k': [],\n", - " 'mask': [],\n", - " 'match': [,\n", - " ],\n", - " 'starts': [],\n", - " 'stops': []})\n", - "2024-09-12 10:50:51,389 - numba.core.ssa - DEBUG - SSA violators {'$phi210.4', '$phi166.4', 'match'}\n", - "2024-09-12 10:50:51,390 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi210.4\n", - "2024-09-12 10:50:51,391 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:51,391 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,392 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:51,392 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:51,393 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:51,394 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:51,394 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:51,395 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:51,395 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:51,396 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:51,397 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:51,397 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:51,398 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:51,399 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,400 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:51,400 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:51,401 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,402 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,402 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:51,403 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:51,404 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,404 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:51,405 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,405 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:51,406 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,407 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,407 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:51,408 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:51,409 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:51,409 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,410 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:51,411 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:51,411 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:51,412 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:51,413 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,413 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:51,414 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:51,415 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,415 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:51,416 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,417 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:51,417 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,418 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,419 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:51,419 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:51,420 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:51,421 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,421 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:51,422 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:51,423 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:51,423 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:51,424 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,425 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,425 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:51,426 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:51,427 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,427 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:51,428 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,429 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:51,429 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,430 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,431 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:51,431 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:51,432 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:51,433 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,433 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:51,434 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:51,435 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:51,435 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:51,436 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:51,436 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:51,437 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:51,438 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:51,438 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:51,439 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:51,440 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:51,440 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:51,441 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:51,442 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,442 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:51,443 - numba.core.ssa - DEBUG - first assign: $phi210.4\n", - "2024-09-12 10:50:51,444 - numba.core.ssa - DEBUG - replaced with: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:51,444 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:51,445 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:51,445 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:51,446 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,447 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:51,447 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:51,448 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:51,449 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:51,449 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:51,450 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,451 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:51,451 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:51,452 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,452 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:51,453 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:51,454 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:51,454 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:51,455 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,456 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,456 - numba.core.ssa - DEBUG - replaced with: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:51,457 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,457 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:51,458 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:51,459 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:51,459 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,460 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:51,461 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:51,461 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:51,462 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $158compare_op.8\n", - "2024-09-12 10:50:51,462 - numba.core.ssa - DEBUG - replaced with: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:51,463 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $158compare_op.8\n", - "2024-09-12 10:50:51,464 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,464 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:51,465 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,466 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,466 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:51,467 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,467 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:51,468 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,469 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:51,469 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:51,470 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,470 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:51,471 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:51,472 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:51,472 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:51,473 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:51,474 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,474 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $176compare_op.8\n", - "2024-09-12 10:50:51,486 - numba.core.ssa - DEBUG - replaced with: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:51,506 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:51,507 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:51,507 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,508 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:51,509 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:51,509 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:51,510 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:51,510 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,511 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:51,511 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $192compare_op.9\n", - "2024-09-12 10:50:51,512 - numba.core.ssa - DEBUG - replaced with: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:51,512 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:51,514 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:51,514 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,515 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:51,515 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:51,516 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:51,517 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $202compare_op.8\n", - "2024-09-12 10:50:51,517 - numba.core.ssa - DEBUG - replaced with: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:51,518 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,518 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:51,519 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,520 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,520 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:51,521 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,522 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:51,522 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,523 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:51,523 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,524 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:51,525 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,526 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:51,526 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:51,526 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,527 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:51,527 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,528 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:51,529 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:51,530 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,530 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,531 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:51,532 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,532 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,533 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:51,534 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,534 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:51,535 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:51,536 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {76: [],\n", - " 136: [],\n", - " 152: [],\n", - " 168: [],\n", - " 180: [],\n", - " 196: []})\n", - "2024-09-12 10:50:51,536 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:51,537 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,537 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:51,538 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:51,539 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:51,540 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:51,540 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:51,541 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:51,541 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:51,542 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:51,543 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:51,543 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:51,544 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:51,545 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,545 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:51,546 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:51,547 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,547 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,548 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:51,549 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:51,549 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,550 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:51,551 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,551 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:51,552 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,553 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,553 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:51,554 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:51,554 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:51,555 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,556 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:51,556 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:51,557 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:51,557 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:51,558 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,559 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:51,560 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:51,560 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,561 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:51,562 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,562 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:51,563 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,563 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,564 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:51,565 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:51,565 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:51,566 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,567 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:51,567 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:51,568 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:51,568 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:51,569 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,570 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,571 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:51,571 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:51,571 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,572 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:51,572 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,573 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:51,574 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,575 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,575 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:51,576 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:51,577 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:51,577 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,578 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:51,579 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:51,579 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:51,580 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:51,580 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:51,581 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:51,582 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:51,582 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:51,583 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:51,584 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:51,585 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:51,585 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:51,586 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:51,586 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,587 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:51,588 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:51,589 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:51,589 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:51,590 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,590 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:51,591 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:51,592 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:51,592 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:51,593 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:51,594 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,594 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:51,595 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:51,596 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,596 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:51,597 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:51,598 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:51,598 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:51,599 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,600 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:51,600 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,601 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:51,602 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:51,602 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:51,603 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,603 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:51,604 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:51,605 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:51,605 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:51,606 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $158compare_op.8\n", - "2024-09-12 10:50:51,606 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,607 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:51,608 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,608 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,609 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:51,610 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,610 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:51,611 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,612 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:51,612 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:51,613 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,614 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:51,614 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:51,615 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:51,615 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:51,616 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:51,617 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,617 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:51,618 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:51,618 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:51,619 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,619 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:51,620 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:51,620 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:51,621 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:51,621 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,622 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:51,622 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:51,623 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:51,625 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:51,625 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,626 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:51,626 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:51,627 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:51,628 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:51,629 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,629 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:51,630 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,630 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,631 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:51,632 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,632 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:51,633 - numba.core.ssa - DEBUG - find_def var='$phi210.4' stmt=match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:51,633 - numba.core.ssa - DEBUG - find_def_from_top label 210\n", - "2024-09-12 10:50:51,634 - numba.core.ssa - DEBUG - insert phi node $phi210.4.6 = phi(incoming_values=[], incoming_blocks=[]) at 210\n", - "2024-09-12 10:50:51,635 - numba.core.ssa - DEBUG - find_def_from_bottom label 196\n", - "2024-09-12 10:50:51,635 - numba.core.ssa - DEBUG - incoming_def $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:51,636 - numba.core.ssa - DEBUG - find_def_from_bottom label 166\n", - "2024-09-12 10:50:51,637 - numba.core.ssa - DEBUG - find_def_from_top label 166\n", - "2024-09-12 10:50:51,637 - numba.core.ssa - DEBUG - insert phi node $phi210.4.7 = phi(incoming_values=[], incoming_blocks=[]) at 166\n", - "2024-09-12 10:50:51,638 - numba.core.ssa - DEBUG - find_def_from_bottom label 152\n", - "2024-09-12 10:50:51,638 - numba.core.ssa - DEBUG - incoming_def $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:51,639 - numba.core.ssa - DEBUG - find_def_from_bottom label 162\n", - "2024-09-12 10:50:51,639 - numba.core.ssa - DEBUG - find_def_from_top label 162\n", - "2024-09-12 10:50:51,640 - numba.core.ssa - DEBUG - idom 136 from label 162\n", - "2024-09-12 10:50:51,641 - numba.core.ssa - DEBUG - find_def_from_bottom label 136\n", - "2024-09-12 10:50:51,642 - numba.core.ssa - DEBUG - incoming_def $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:51,642 - numba.core.ssa - DEBUG - incoming_def $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:51,643 - numba.core.ssa - DEBUG - find_def_from_bottom label 168\n", - "2024-09-12 10:50:51,643 - numba.core.ssa - DEBUG - incoming_def $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:51,644 - numba.core.ssa - DEBUG - find_def_from_bottom label 76\n", - "2024-09-12 10:50:51,644 - numba.core.ssa - DEBUG - incoming_def $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:51,645 - numba.core.ssa - DEBUG - find_def_from_bottom label 206\n", - "2024-09-12 10:50:51,646 - numba.core.ssa - DEBUG - find_def_from_top label 206\n", - "2024-09-12 10:50:51,646 - numba.core.ssa - DEBUG - idom 180 from label 206\n", - "2024-09-12 10:50:51,647 - numba.core.ssa - DEBUG - find_def_from_bottom label 180\n", - "2024-09-12 10:50:51,648 - numba.core.ssa - DEBUG - incoming_def $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:51,648 - numba.core.ssa - DEBUG - replaced with: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:51,649 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,649 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:51,650 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,651 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:51,651 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,652 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:51,653 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:51,653 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,654 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:51,654 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,655 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:51,656 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:51,656 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,657 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,658 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:51,658 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,659 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,659 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:51,660 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,660 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:51,661 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:51,662 - numba.core.ssa - DEBUG - Fix SSA violator on var $phi166.4\n", - "2024-09-12 10:50:51,662 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:51,663 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,663 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:51,664 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:51,665 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:51,665 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:51,666 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:51,667 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:51,667 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:51,668 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:51,668 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:51,669 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:51,670 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:51,670 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,671 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:51,672 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:51,672 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,673 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,673 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:51,674 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:51,674 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,675 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:51,676 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,676 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:51,677 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,677 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,678 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:51,678 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:51,679 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:51,680 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,680 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:51,681 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:51,681 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:51,682 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:51,683 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,683 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:51,684 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:51,684 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,685 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:51,686 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,686 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:51,686 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,687 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,688 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:51,688 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:51,689 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:51,689 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,690 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:51,690 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:51,691 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:51,692 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:51,692 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,693 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,694 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:51,695 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:51,695 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,696 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:51,696 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,697 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:51,697 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,698 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,698 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:51,699 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:51,699 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:51,700 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,700 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:51,701 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:51,701 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:51,702 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:51,702 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:51,703 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:51,703 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:51,703 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:51,704 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:51,704 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:51,707 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:51,708 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:51,708 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:51,709 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,710 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:51,710 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:51,711 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:51,711 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:51,712 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,713 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:51,713 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:51,714 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:51,715 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:51,715 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:51,716 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,716 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:51,717 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:51,718 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,718 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:51,719 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:51,720 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:51,720 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:51,721 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,721 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:51,722 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,722 - numba.core.ssa - DEBUG - first assign: $phi166.4\n", - "2024-09-12 10:50:51,723 - numba.core.ssa - DEBUG - replaced with: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,724 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:51,724 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:51,725 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:51,726 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,726 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:51,726 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:51,727 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:51,727 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:51,729 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $158compare_op.8\n", - "2024-09-12 10:50:51,729 - numba.core.ssa - DEBUG - replaced with: $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:51,729 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,730 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:51,730 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,731 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,731 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:51,732 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,732 - numba.core.ssa - DEBUG - on stmt: $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:51,733 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:51,733 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,734 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:51,734 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:51,735 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,735 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:51,736 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:51,736 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:51,736 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:51,737 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:51,737 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,738 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:51,738 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:51,741 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:51,742 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,742 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:51,742 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:51,743 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:51,744 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:51,744 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,745 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:51,745 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:51,746 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:51,747 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:51,748 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,748 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:51,749 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:51,749 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:51,750 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:51,750 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,751 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:51,752 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,752 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,753 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:51,754 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,754 - numba.core.ssa - DEBUG - on stmt: $phi210.4.6 = phi(incoming_values=[Var($phi210.4.5, indexing.py:600), Var($phi210.4.7, indexing.py:599), Var($phi210.4.3, indexing.py:600), Var($phi210.4, indexing.py:599), Var($phi210.4.4, indexing.py:600)], incoming_blocks=[196, 166, 168, 76, 206])\n", - "2024-09-12 10:50:51,755 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:51,755 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,756 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:51,757 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,757 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:51,758 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,759 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:51,759 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:51,760 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,760 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:51,761 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,761 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:51,762 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:51,763 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,763 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,764 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:51,764 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,765 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,765 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:51,766 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,766 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:51,767 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:51,768 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {136: [],\n", - " 152: []})\n", - "2024-09-12 10:50:51,769 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:51,769 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,770 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:51,771 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:51,771 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:51,772 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:51,772 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:51,773 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:51,773 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:51,774 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:51,775 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:51,775 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:51,776 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:51,777 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,777 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:51,778 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:51,778 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,779 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,780 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:51,780 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:51,781 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,782 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:51,782 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,783 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:51,783 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,783 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,785 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:51,785 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:51,785 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:51,786 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,786 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:51,787 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:51,787 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:51,788 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:51,788 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,789 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:51,790 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:51,791 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,791 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:51,792 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,792 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:51,793 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,793 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,794 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:51,794 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:51,795 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:51,795 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,795 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:51,796 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:51,798 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:51,798 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:51,799 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,799 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,800 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:51,801 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:51,801 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,802 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:51,802 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,802 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:51,803 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,803 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,804 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:51,804 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:51,805 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:51,807 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,807 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:51,807 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:51,808 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:51,809 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:51,809 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:51,810 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:51,811 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:51,811 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:51,812 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:51,813 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:51,813 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:51,814 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:51,814 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:51,814 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,815 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:51,815 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:51,816 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:51,816 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:51,817 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,817 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:51,818 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:51,818 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:51,819 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:51,819 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:51,820 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,820 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:51,821 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:51,821 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,822 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:51,824 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:51,825 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:51,825 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:51,826 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,826 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:51,827 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,827 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:51,828 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:51,829 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:51,829 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,830 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:51,830 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:51,831 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:51,831 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:51,831 - numba.core.ssa - DEBUG - on stmt: $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:51,832 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,832 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:51,833 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,833 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,834 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:51,834 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,835 - numba.core.ssa - DEBUG - on stmt: $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:51,835 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:51,837 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,838 - numba.core.ssa - DEBUG - find_def var='$phi166.4' stmt=$166pred = call bool166($phi166.4, func=bool166, args=(Var($phi166.4, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,838 - numba.core.ssa - DEBUG - find_def_from_top label 166\n", - "2024-09-12 10:50:51,839 - numba.core.ssa - DEBUG - insert phi node $phi166.4.2 = phi(incoming_values=[], incoming_blocks=[]) at 166\n", - "2024-09-12 10:50:51,840 - numba.core.ssa - DEBUG - find_def_from_bottom label 152\n", - "2024-09-12 10:50:51,840 - numba.core.ssa - DEBUG - incoming_def $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:51,840 - numba.core.ssa - DEBUG - find_def_from_bottom label 162\n", - "2024-09-12 10:50:51,842 - numba.core.ssa - DEBUG - find_def_from_top label 162\n", - "2024-09-12 10:50:51,842 - numba.core.ssa - DEBUG - idom 136 from label 162\n", - "2024-09-12 10:50:51,843 - numba.core.ssa - DEBUG - find_def_from_bottom label 136\n", - "2024-09-12 10:50:51,843 - numba.core.ssa - DEBUG - incoming_def $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,844 - numba.core.ssa - DEBUG - replaced with: $166pred = call bool166($phi166.4.2, func=bool166, args=(Var($phi166.4.2, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,844 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:51,845 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:51,845 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,846 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:51,846 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:51,848 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:51,848 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:51,849 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:51,849 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,849 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:51,850 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:51,850 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:51,851 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,851 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:51,852 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:51,853 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:51,854 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:51,854 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,855 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:51,855 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:51,856 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:51,856 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:51,857 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,858 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:51,858 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:51,859 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:51,859 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:51,860 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,860 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:51,862 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,862 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,862 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:51,863 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,864 - numba.core.ssa - DEBUG - on stmt: $phi210.4.6 = phi(incoming_values=[Var($phi210.4.5, indexing.py:600), Var($phi210.4.7, indexing.py:599), Var($phi210.4.3, indexing.py:600), Var($phi210.4, indexing.py:599), Var($phi210.4.4, indexing.py:600)], incoming_blocks=[196, 166, 168, 76, 206])\n", - "2024-09-12 10:50:51,864 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:51,865 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,865 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:51,866 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,866 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:51,867 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,867 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:51,869 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:51,869 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,870 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:51,870 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,871 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:51,872 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:51,872 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,873 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,873 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:51,874 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,874 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,875 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:51,876 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,876 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:51,877 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:51,878 - numba.core.ssa - DEBUG - Fix SSA violator on var match\n", - "2024-09-12 10:50:51,878 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:51,879 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,879 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:51,880 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:51,881 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:51,881 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:51,881 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:51,882 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:51,882 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:51,883 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:51,883 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:51,885 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:51,885 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:51,886 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,886 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:51,887 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:51,887 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,888 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,889 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:51,889 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:51,890 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,890 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:51,891 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,892 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:51,892 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,893 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,893 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:51,894 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:51,894 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:51,895 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,896 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:51,897 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:51,897 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:51,898 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:51,898 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,899 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:51,900 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:51,900 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,901 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:51,901 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,902 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:51,903 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,903 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:51,904 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:51,904 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:51,905 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:51,906 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,906 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:51,907 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:51,907 - numba.core.ssa - DEBUG - first assign: match\n", - "2024-09-12 10:50:51,908 - numba.core.ssa - DEBUG - replaced with: match = const(bool, True)\n", - "2024-09-12 10:50:51,908 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:51,908 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:51,910 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,910 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,911 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:51,911 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:51,912 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,912 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:51,913 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,914 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:51,914 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,915 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:51,915 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:51,916 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:51,916 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:51,916 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,917 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:51,917 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:51,918 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:51,918 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:51,919 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:51,919 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:51,921 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:51,922 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:51,922 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:51,923 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:51,923 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:51,924 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:51,925 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:51,925 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,926 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:51,926 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:51,927 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:51,928 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:51,928 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,928 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:51,929 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:51,929 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:51,930 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:51,930 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:51,932 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,932 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:51,933 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:51,933 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,934 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:51,934 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:51,934 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:51,936 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:51,936 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,937 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:51,937 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:51,938 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:51,938 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:51,939 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:51,940 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,940 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:51,941 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:51,941 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:51,942 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:51,942 - numba.core.ssa - DEBUG - on stmt: $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:51,943 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,944 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:51,944 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,945 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:51,945 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:51,946 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,946 - numba.core.ssa - DEBUG - on stmt: $phi166.4.2 = phi(incoming_values=[Var($phi166.4.1, indexing.py:600), Var($phi166.4, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:51,947 - numba.core.ssa - DEBUG - on stmt: $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:51,947 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:51,948 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4.2, func=bool166, args=(Var($phi166.4.2, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,948 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:51,949 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:51,949 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,950 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:51,950 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:51,951 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:51,951 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:51,953 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:51,954 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,954 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:51,955 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:51,955 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:51,955 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,956 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:51,956 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:51,957 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:51,957 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:51,958 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,958 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:51,959 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:51,961 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:51,961 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:51,962 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,962 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:51,963 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:51,963 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:51,964 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:51,964 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,965 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:51,966 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,966 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:51,967 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:51,968 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,968 - numba.core.ssa - DEBUG - on stmt: $phi210.4.6 = phi(incoming_values=[Var($phi210.4.5, indexing.py:600), Var($phi210.4.7, indexing.py:599), Var($phi210.4.3, indexing.py:600), Var($phi210.4, indexing.py:599), Var($phi210.4.4, indexing.py:600)], incoming_blocks=[196, 166, 168, 76, 206])\n", - "2024-09-12 10:50:51,969 - numba.core.ssa - DEBUG - on stmt: match = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:51,969 - numba.core.ssa - DEBUG - replaced with: match.1 = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:51,970 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:51,971 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:51,971 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,972 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:51,972 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,973 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:51,974 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:51,974 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,975 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:51,975 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,976 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:51,977 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:51,977 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,978 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:51,978 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:51,979 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,980 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,980 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:51,981 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,982 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:51,982 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:51,983 - numba.core.ssa - DEBUG - Replaced assignments: defaultdict(,\n", - " {56: [],\n", - " 210: []})\n", - "2024-09-12 10:50:51,983 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 0\n", - "2024-09-12 10:50:51,983 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,985 - numba.core.ssa - DEBUG - on stmt: starts = arg(0, name=starts)\n", - "2024-09-12 10:50:51,985 - numba.core.ssa - DEBUG - on stmt: stops = arg(1, name=stops)\n", - "2024-09-12 10:50:51,985 - numba.core.ssa - DEBUG - on stmt: coords = arg(2, name=coords)\n", - "2024-09-12 10:50:51,986 - numba.core.ssa - DEBUG - on stmt: indices = arg(3, name=indices)\n", - "2024-09-12 10:50:51,986 - numba.core.ssa - DEBUG - on stmt: $2load_global.0 = global(numba: )\n", - "2024-09-12 10:50:51,987 - numba.core.ssa - DEBUG - on stmt: $4load_attr.1 = getattr(value=$2load_global.0, attr=typed)\n", - "2024-09-12 10:50:51,987 - numba.core.ssa - DEBUG - on stmt: $6load_attr.2 = getattr(value=$4load_attr.1, attr=List)\n", - "2024-09-12 10:50:51,989 - numba.core.ssa - DEBUG - on stmt: $8load_method.3 = getattr(value=$6load_attr.2, attr=empty_list)\n", - "2024-09-12 10:50:51,989 - numba.core.ssa - DEBUG - on stmt: $10load_global.4 = global(numba: )\n", - "2024-09-12 10:50:51,990 - numba.core.ssa - DEBUG - on stmt: $12load_attr.5 = getattr(value=$10load_global.4, attr=types)\n", - "2024-09-12 10:50:51,990 - numba.core.ssa - DEBUG - on stmt: $14load_attr.6 = getattr(value=$12load_attr.5, attr=intp)\n", - "2024-09-12 10:50:51,991 - numba.core.ssa - DEBUG - on stmt: mask = call $8load_method.3($14load_attr.6, func=$8load_method.3, args=[Var($14load_attr.6, indexing.py:586)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,992 - numba.core.ssa - DEBUG - on stmt: $20load_global.8 = global(range: )\n", - "2024-09-12 10:50:51,992 - numba.core.ssa - DEBUG - on stmt: $22load_global.9 = global(len: )\n", - "2024-09-12 10:50:51,992 - numba.core.ssa - DEBUG - on stmt: $26call_function.11 = call $22load_global.9(starts, func=$22load_global.9, args=[Var(starts, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,993 - numba.core.ssa - DEBUG - on stmt: $28call_function.12 = call $20load_global.8($26call_function.11, func=$20load_global.8, args=[Var($26call_function.11, indexing.py:589)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:51,993 - numba.core.ssa - DEBUG - on stmt: $30get_iter.13 = getiter(value=$28call_function.12)\n", - "2024-09-12 10:50:51,994 - numba.core.ssa - DEBUG - on stmt: $phi32.0 = $30get_iter.13\n", - "2024-09-12 10:50:51,994 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:51,996 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 32\n", - "2024-09-12 10:50:51,996 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:51,997 - numba.core.ssa - DEBUG - on stmt: $32for_iter.1 = iternext(value=$phi32.0)\n", - "2024-09-12 10:50:51,997 - numba.core.ssa - DEBUG - on stmt: $32for_iter.2 = pair_first(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,998 - numba.core.ssa - DEBUG - on stmt: $32for_iter.3 = pair_second(value=$32for_iter.1)\n", - "2024-09-12 10:50:51,998 - numba.core.ssa - DEBUG - on stmt: $phi34.1 = $32for_iter.2\n", - "2024-09-12 10:50:51,999 - numba.core.ssa - DEBUG - on stmt: branch $32for_iter.3, 34, 234\n", - "2024-09-12 10:50:51,999 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 34\n", - "2024-09-12 10:50:52,000 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,001 - numba.core.ssa - DEBUG - on stmt: i = $phi34.1\n", - "2024-09-12 10:50:52,002 - numba.core.ssa - DEBUG - on stmt: $36load_global.2 = global(range: )\n", - "2024-09-12 10:50:52,002 - numba.core.ssa - DEBUG - on stmt: $42binary_subscr.5 = getitem(value=starts, index=i, fn=)\n", - "2024-09-12 10:50:52,002 - numba.core.ssa - DEBUG - on stmt: $48binary_subscr.8 = getitem(value=stops, index=i, fn=)\n", - "2024-09-12 10:50:52,003 - numba.core.ssa - DEBUG - on stmt: $50call_function.9 = call $36load_global.2($42binary_subscr.5, $48binary_subscr.8, func=$36load_global.2, args=[Var($42binary_subscr.5, indexing.py:591), Var($48binary_subscr.8, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,004 - numba.core.ssa - DEBUG - on stmt: $52get_iter.10 = getiter(value=$50call_function.9)\n", - "2024-09-12 10:50:52,005 - numba.core.ssa - DEBUG - on stmt: $phi54.1 = $52get_iter.10\n", - "2024-09-12 10:50:52,005 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:52,006 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 54\n", - "2024-09-12 10:50:52,006 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,007 - numba.core.ssa - DEBUG - on stmt: $54for_iter.2 = iternext(value=$phi54.1)\n", - "2024-09-12 10:50:52,008 - numba.core.ssa - DEBUG - on stmt: $54for_iter.3 = pair_first(value=$54for_iter.2)\n", - "2024-09-12 10:50:52,008 - numba.core.ssa - DEBUG - on stmt: $54for_iter.4 = pair_second(value=$54for_iter.2)\n", - "2024-09-12 10:50:52,009 - numba.core.ssa - DEBUG - on stmt: $phi56.2 = $54for_iter.3\n", - "2024-09-12 10:50:52,009 - numba.core.ssa - DEBUG - on stmt: branch $54for_iter.4, 56, 232\n", - "2024-09-12 10:50:52,010 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 56\n", - "2024-09-12 10:50:52,010 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,011 - numba.core.ssa - DEBUG - on stmt: j = $phi56.2\n", - "2024-09-12 10:50:52,012 - numba.core.ssa - DEBUG - on stmt: match = const(bool, True)\n", - "2024-09-12 10:50:52,012 - numba.core.ssa - DEBUG - on stmt: $62load_global.4 = global(range: )\n", - "2024-09-12 10:50:52,013 - numba.core.ssa - DEBUG - on stmt: $64load_global.5 = global(len: )\n", - "2024-09-12 10:50:52,013 - numba.core.ssa - DEBUG - on stmt: $68call_function.7 = call $64load_global.5(indices, func=$64load_global.5, args=[Var(indices, indexing.py:553)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,014 - numba.core.ssa - DEBUG - on stmt: $70call_function.8 = call $62load_global.4($68call_function.7, func=$62load_global.4, args=[Var($68call_function.7, indexing.py:595)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,015 - numba.core.ssa - DEBUG - on stmt: $72get_iter.9 = getiter(value=$70call_function.8)\n", - "2024-09-12 10:50:52,015 - numba.core.ssa - DEBUG - on stmt: $phi74.2 = $72get_iter.9\n", - "2024-09-12 10:50:52,016 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:52,017 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 74\n", - "2024-09-12 10:50:52,017 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,018 - numba.core.ssa - DEBUG - on stmt: $74for_iter.3 = iternext(value=$phi74.2)\n", - "2024-09-12 10:50:52,018 - numba.core.ssa - DEBUG - on stmt: $74for_iter.4 = pair_first(value=$74for_iter.3)\n", - "2024-09-12 10:50:52,019 - numba.core.ssa - DEBUG - on stmt: $74for_iter.5 = pair_second(value=$74for_iter.3)\n", - "2024-09-12 10:50:52,020 - numba.core.ssa - DEBUG - on stmt: $phi76.3 = $74for_iter.4\n", - "2024-09-12 10:50:52,020 - numba.core.ssa - DEBUG - on stmt: branch $74for_iter.5, 76, 216\n", - "2024-09-12 10:50:52,021 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 76\n", - "2024-09-12 10:50:52,021 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,022 - numba.core.ssa - DEBUG - on stmt: k = $phi76.3\n", - "2024-09-12 10:50:52,023 - numba.core.ssa - DEBUG - on stmt: idx = getitem(value=indices, index=k, fn=)\n", - "2024-09-12 10:50:52,023 - numba.core.ssa - DEBUG - on stmt: $92build_tuple.10 = build_tuple(items=[Var(k, indexing.py:595), Var(j, indexing.py:591)])\n", - "2024-09-12 10:50:52,024 - numba.core.ssa - DEBUG - on stmt: elem = getitem(value=coords, index=$92build_tuple.10, fn=)\n", - "2024-09-12 10:50:52,024 - numba.core.ssa - DEBUG - on stmt: $const104.15 = const(int, 0)\n", - "2024-09-12 10:50:52,025 - numba.core.ssa - DEBUG - on stmt: $106binary_subscr.16 = static_getitem(value=idx, index=0, index_var=$const104.15, fn=)\n", - "2024-09-12 10:50:52,026 - numba.core.ssa - DEBUG - on stmt: $108binary_subtract.17 = elem - $106binary_subscr.16\n", - "2024-09-12 10:50:52,026 - numba.core.ssa - DEBUG - on stmt: $const112.19 = const(int, 2)\n", - "2024-09-12 10:50:52,027 - numba.core.ssa - DEBUG - on stmt: $114binary_subscr.20 = static_getitem(value=idx, index=2, index_var=$const112.19, fn=)\n", - "2024-09-12 10:50:52,028 - numba.core.ssa - DEBUG - on stmt: $116binary_modulo.21 = $108binary_subtract.17 % $114binary_subscr.20\n", - "2024-09-12 10:50:52,028 - numba.core.ssa - DEBUG - on stmt: $const118.22 = const(int, 0)\n", - "2024-09-12 10:50:52,029 - numba.core.ssa - DEBUG - on stmt: $120compare_op.23 = $116binary_modulo.21 == $const118.22\n", - "2024-09-12 10:50:52,029 - numba.core.ssa - DEBUG - on stmt: bool122 = global(bool: )\n", - "2024-09-12 10:50:52,030 - numba.core.ssa - DEBUG - on stmt: $122pred = call bool122($120compare_op.23, func=bool122, args=(Var($120compare_op.23, indexing.py:599),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,030 - numba.core.ssa - DEBUG - on stmt: $phi210.4 = $120compare_op.23\n", - "2024-09-12 10:50:52,031 - numba.core.ssa - DEBUG - on stmt: $phi210.3 = match\n", - "2024-09-12 10:50:52,031 - numba.core.ssa - DEBUG - find_def var='match' stmt=$phi210.3 = match\n", - "2024-09-12 10:50:52,032 - numba.core.ssa - DEBUG - find_def_from_top label 76\n", - "2024-09-12 10:50:52,033 - numba.core.ssa - DEBUG - idom 74 from label 76\n", - "2024-09-12 10:50:52,033 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:52,034 - numba.core.ssa - DEBUG - find_def_from_top label 74\n", - "2024-09-12 10:50:52,034 - numba.core.ssa - DEBUG - insert phi node match.2 = phi(incoming_values=[], incoming_blocks=[]) at 74\n", - "2024-09-12 10:50:52,035 - numba.core.ssa - DEBUG - find_def_from_bottom label 56\n", - "2024-09-12 10:50:52,035 - numba.core.ssa - DEBUG - incoming_def match = const(bool, True)\n", - "2024-09-12 10:50:52,036 - numba.core.ssa - DEBUG - find_def_from_bottom label 210\n", - "2024-09-12 10:50:52,036 - numba.core.ssa - DEBUG - incoming_def match.1 = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:52,036 - numba.core.ssa - DEBUG - replaced with: $phi210.3 = match.2\n", - "2024-09-12 10:50:52,037 - numba.core.ssa - DEBUG - on stmt: branch $122pred, 124, 210\n", - "2024-09-12 10:50:52,037 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 124\n", - "2024-09-12 10:50:52,038 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,040 - numba.core.ssa - DEBUG - on stmt: $const126.5 = const(int, 2)\n", - "2024-09-12 10:50:52,040 - numba.core.ssa - DEBUG - on stmt: $128binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const126.5, fn=)\n", - "2024-09-12 10:50:52,041 - numba.core.ssa - DEBUG - on stmt: $const130.7 = const(int, 0)\n", - "2024-09-12 10:50:52,041 - numba.core.ssa - DEBUG - on stmt: $132compare_op.8 = $128binary_subscr.6 > $const130.7\n", - "2024-09-12 10:50:52,042 - numba.core.ssa - DEBUG - on stmt: bool134 = global(bool: )\n", - "2024-09-12 10:50:52,042 - numba.core.ssa - DEBUG - on stmt: $134pred = call bool134($132compare_op.8, func=bool134, args=(Var($132compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,043 - numba.core.ssa - DEBUG - on stmt: branch $134pred, 136, 168\n", - "2024-09-12 10:50:52,043 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 136\n", - "2024-09-12 10:50:52,044 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,044 - numba.core.ssa - DEBUG - on stmt: $const138.5 = const(int, 0)\n", - "2024-09-12 10:50:52,046 - numba.core.ssa - DEBUG - on stmt: $140binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const138.5, fn=)\n", - "2024-09-12 10:50:52,046 - numba.core.ssa - DEBUG - on stmt: $148compare_op.9 = $140binary_subscr.6 <= elem\n", - "2024-09-12 10:50:52,047 - numba.core.ssa - DEBUG - on stmt: bool150 = global(bool: )\n", - "2024-09-12 10:50:52,047 - numba.core.ssa - DEBUG - on stmt: $150pred = call bool150($148compare_op.9, func=bool150, args=(Var($148compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,048 - numba.core.ssa - DEBUG - on stmt: $phi210.4.1 = $148compare_op.9\n", - "2024-09-12 10:50:52,048 - numba.core.ssa - DEBUG - on stmt: $phi166.4 = $148compare_op.9\n", - "2024-09-12 10:50:52,048 - numba.core.ssa - DEBUG - on stmt: $phi152.4 = elem\n", - "2024-09-12 10:50:52,049 - numba.core.ssa - DEBUG - on stmt: branch $150pred, 152, 162\n", - "2024-09-12 10:50:52,049 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 152\n", - "2024-09-12 10:50:52,050 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,051 - numba.core.ssa - DEBUG - on stmt: $const154.6 = const(int, 1)\n", - "2024-09-12 10:50:52,052 - numba.core.ssa - DEBUG - on stmt: $156binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const154.6, fn=)\n", - "2024-09-12 10:50:52,052 - numba.core.ssa - DEBUG - on stmt: $158compare_op.8 = $phi152.4 < $156binary_subscr.7\n", - "2024-09-12 10:50:52,053 - numba.core.ssa - DEBUG - on stmt: $phi210.4.2 = $158compare_op.8\n", - "2024-09-12 10:50:52,053 - numba.core.ssa - DEBUG - on stmt: $phi166.4.1 = $158compare_op.8\n", - "2024-09-12 10:50:52,054 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:52,054 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 162\n", - "2024-09-12 10:50:52,055 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,055 - numba.core.ssa - DEBUG - on stmt: jump 166\n", - "2024-09-12 10:50:52,056 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 166\n", - "2024-09-12 10:50:52,057 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,058 - numba.core.ssa - DEBUG - on stmt: $phi166.4.2 = phi(incoming_values=[Var($phi166.4.1, indexing.py:600), Var($phi166.4, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:52,058 - numba.core.ssa - DEBUG - on stmt: $phi210.4.7 = phi(incoming_values=[Var($phi210.4.2, indexing.py:600), Var($phi210.4.1, indexing.py:600)], incoming_blocks=[152, 162])\n", - "2024-09-12 10:50:52,059 - numba.core.ssa - DEBUG - on stmt: bool166 = global(bool: )\n", - "2024-09-12 10:50:52,059 - numba.core.ssa - DEBUG - on stmt: $166pred = call bool166($phi166.4.2, func=bool166, args=(Var($phi166.4.2, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,060 - numba.core.ssa - DEBUG - on stmt: branch $166pred, 210, 168\n", - "2024-09-12 10:50:52,060 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 168\n", - "2024-09-12 10:50:52,061 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,062 - numba.core.ssa - DEBUG - on stmt: $const170.5 = const(int, 2)\n", - "2024-09-12 10:50:52,062 - numba.core.ssa - DEBUG - on stmt: $172binary_subscr.6 = static_getitem(value=idx, index=2, index_var=$const170.5, fn=)\n", - "2024-09-12 10:50:52,063 - numba.core.ssa - DEBUG - on stmt: $const174.7 = const(int, 0)\n", - "2024-09-12 10:50:52,064 - numba.core.ssa - DEBUG - on stmt: $176compare_op.8 = $172binary_subscr.6 < $const174.7\n", - "2024-09-12 10:50:52,064 - numba.core.ssa - DEBUG - on stmt: bool178 = global(bool: )\n", - "2024-09-12 10:50:52,065 - numba.core.ssa - DEBUG - on stmt: $178pred = call bool178($176compare_op.8, func=bool178, args=(Var($176compare_op.8, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,065 - numba.core.ssa - DEBUG - on stmt: $phi210.4.3 = $176compare_op.8\n", - "2024-09-12 10:50:52,066 - numba.core.ssa - DEBUG - on stmt: branch $178pred, 180, 210\n", - "2024-09-12 10:50:52,067 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 180\n", - "2024-09-12 10:50:52,067 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,068 - numba.core.ssa - DEBUG - on stmt: $const182.5 = const(int, 0)\n", - "2024-09-12 10:50:52,068 - numba.core.ssa - DEBUG - on stmt: $184binary_subscr.6 = static_getitem(value=idx, index=0, index_var=$const182.5, fn=)\n", - "2024-09-12 10:50:52,069 - numba.core.ssa - DEBUG - on stmt: $192compare_op.9 = $184binary_subscr.6 >= elem\n", - "2024-09-12 10:50:52,070 - numba.core.ssa - DEBUG - on stmt: bool194 = global(bool: )\n", - "2024-09-12 10:50:52,070 - numba.core.ssa - DEBUG - on stmt: $194pred = call bool194($192compare_op.9, func=bool194, args=(Var($192compare_op.9, indexing.py:600),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,071 - numba.core.ssa - DEBUG - on stmt: $phi196.4 = elem\n", - "2024-09-12 10:50:52,071 - numba.core.ssa - DEBUG - on stmt: $phi210.4.4 = $192compare_op.9\n", - "2024-09-12 10:50:52,072 - numba.core.ssa - DEBUG - on stmt: branch $194pred, 196, 206\n", - "2024-09-12 10:50:52,072 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 196\n", - "2024-09-12 10:50:52,073 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,074 - numba.core.ssa - DEBUG - on stmt: $const198.6 = const(int, 1)\n", - "2024-09-12 10:50:52,075 - numba.core.ssa - DEBUG - on stmt: $200binary_subscr.7 = static_getitem(value=idx, index=1, index_var=$const198.6, fn=)\n", - "2024-09-12 10:50:52,075 - numba.core.ssa - DEBUG - on stmt: $202compare_op.8 = $phi196.4 > $200binary_subscr.7\n", - "2024-09-12 10:50:52,076 - numba.core.ssa - DEBUG - on stmt: $phi210.4.5 = $202compare_op.8\n", - "2024-09-12 10:50:52,076 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:52,077 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 206\n", - "2024-09-12 10:50:52,077 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,078 - numba.core.ssa - DEBUG - on stmt: jump 210\n", - "2024-09-12 10:50:52,078 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 210\n", - "2024-09-12 10:50:52,079 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,080 - numba.core.ssa - DEBUG - on stmt: $phi210.4.6 = phi(incoming_values=[Var($phi210.4.5, indexing.py:600), Var($phi210.4.7, indexing.py:599), Var($phi210.4.3, indexing.py:600), Var($phi210.4, indexing.py:599), Var($phi210.4.4, indexing.py:600)], incoming_blocks=[196, 166, 168, 76, 206])\n", - "2024-09-12 10:50:52,080 - numba.core.ssa - DEBUG - on stmt: match.1 = inplace_binop(fn=, immutable_fn=, lhs=$phi210.3, rhs=$phi210.4.6, static_lhs=Undefined, static_rhs=Undefined)\n", - "2024-09-12 10:50:52,081 - numba.core.ssa - DEBUG - on stmt: jump 74\n", - "2024-09-12 10:50:52,081 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 216\n", - "2024-09-12 10:50:52,082 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,082 - numba.core.ssa - DEBUG - on stmt: bool218 = global(bool: )\n", - "2024-09-12 10:50:52,083 - numba.core.ssa - DEBUG - on stmt: $218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,084 - numba.core.ssa - DEBUG - find_def var='match' stmt=$218pred = call bool218(match, func=bool218, args=(Var(match, indexing.py:592),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,084 - numba.core.ssa - DEBUG - find_def_from_top label 216\n", - "2024-09-12 10:50:52,085 - numba.core.ssa - DEBUG - idom 74 from label 216\n", - "2024-09-12 10:50:52,085 - numba.core.ssa - DEBUG - find_def_from_bottom label 74\n", - "2024-09-12 10:50:52,086 - numba.core.ssa - DEBUG - replaced with: $218pred = call bool218(match.2, func=bool218, args=(Var(match.2, indexing.py:595),), kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,086 - numba.core.ssa - DEBUG - on stmt: branch $218pred, 220, 230\n", - "2024-09-12 10:50:52,088 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 220\n", - "2024-09-12 10:50:52,088 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,088 - numba.core.ssa - DEBUG - on stmt: $222load_method.3 = getattr(value=mask, attr=append)\n", - "2024-09-12 10:50:52,089 - numba.core.ssa - DEBUG - on stmt: $226call_method.5 = call $222load_method.3(j, func=$222load_method.3, args=[Var(j, indexing.py:591)], kws=(), vararg=None, varkwarg=None, target=None)\n", - "2024-09-12 10:50:52,090 - numba.core.ssa - DEBUG - on stmt: jump 230\n", - "2024-09-12 10:50:52,090 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 230\n", - "2024-09-12 10:50:52,091 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,092 - numba.core.ssa - DEBUG - on stmt: jump 54\n", - "2024-09-12 10:50:52,092 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 232\n", - "2024-09-12 10:50:52,093 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,094 - numba.core.ssa - DEBUG - on stmt: jump 32\n", - "2024-09-12 10:50:52,094 - numba.core.ssa - DEBUG - ==== SSA block rewrite pass on 234\n", - "2024-09-12 10:50:52,095 - numba.core.ssa - DEBUG - Running \n", - "2024-09-12 10:50:52,095 - numba.core.ssa - DEBUG - on stmt: $236return_value.1 = cast(value=mask)\n", - "2024-09-12 10:50:52,096 - numba.core.ssa - DEBUG - on stmt: return $236return_value.1\n", - "2024-09-12 10:50:52,920 - utils.plot - INFO - Sum of data 3D heatmap: 12153.048423245882\n", - "2024-09-12 10:50:52,923 - utils.plot - INFO - Data 3D heatmap shape: (15, 161)\n", - "2024-09-12 10:50:52,956 - matplotlib.colorbar - DEBUG - locator: \n", - "2024-09-12 10:50:53,196 - utils.plot - INFO - Bounding box: [0, 14, 14, 147]\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%autoreload 2\n", - "from utils.plot import plot_pept_im_rt_heatmap\n", - "\n", - "plot_pept_im_rt_heatmap(\n", - " pept_mz_rank=19198,\n", - " act_3d=act_3d,\n", - " maxquant_result_dict=maxquant_result_ref,\n", - " maxquant_result_exp=maxquant_result_ref,\n", - " plot_range=\"non_zero\",\n", - " #rt_range=(12.86, 13.27),\n", - " #rt_range=(8)\n", - " mobility_values_df=mobility_values_df,\n", - " ms1scans=ms1scans,\n", - " log_intensity=False\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 131, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-07-29 12:50:00,959 - utils.plot - INFO - Dictionary entry Modified sequence Charge 1/K0 RT_search_left RT_search_right \\\n", - "8977 _TFEGHDASVLK_ 2 0.943375 5.320433 6.946167 \n", - "\n", - " RT_search_center Retention time Number of data points Number of scans \n", - "8977 6.1333 15.078 518 20 \n", - "2024-07-29 12:50:00,970 - utils.plot - INFO - Experiment result: Modified sequence Charge Calibrated retention time start \\\n", - "159416 _TFEGHDASVLK_ 2 6.0065 \n", - "\n", - " Calibrated retention time finish 1/K0 1/K0 length \\\n", - "159416 6.1269 0.947821 0.041633 \n", - "\n", - " Number of data points Retention length \n", - "159416 325 0.12041 , bounding box available: [6.0065, 6.1269, 0.12040000000000006, 0.9270046965000001, 0.9686381835, 0.041633487]\n", - "2024-07-29 12:50:00,976 - postprocessing.ims_3d - DEBUG - No reference RT range given, using dictionary entries: 6.133299581836432, (5.320432596738178, 6.946166566934687).\n", - "2024-07-29 12:50:00,979 - postprocessing.ims_3d - DEBUG - No reference IM range given, using dictionary entries: 0.9435497870414629, (0.9035497870414628, 0.9835497870414629).\n", - "2024-07-29 12:50:00,980 - utils.plot - INFO - Reference entry: [6.133299581836432, 0.9435497870414629]\n", - "2024-07-29 12:50:02,733 - utils.plot - INFO - Sum of data 3D heatmap: 1078201.7603834711\n", - "2024-07-29 12:50:02,734 - utils.plot - INFO - Data 3D heatmap shape: (83, 227)\n", - "2024-07-29 12:50:02,764 - matplotlib.colorbar - DEBUG - locator: \n", - "2024-07-29 12:50:03,039 - utils.plot - INFO - Bounding box: [34, 41, 66, 184]\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_pept_im_rt_heatmap(\n", - " pept_mz_rank=15205,\n", - " act_3d=act_3d,\n", - " maxquant_result_dict=maxquant_result_ref,\n", - " maxquant_result_exp=maxquant_result_exp,\n", - " mobility_values_df=mobility_values_df,\n", - " plot_range=\"custom\",\n", - " # rt_range=(12.86, 13.27),\n", - " ms1scans=ms1scans,\n", - " log_intensity=False,\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "sbs", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/paper_02_PS_FDR_figures.ipynb b/notebooks/paper_02_PS_FDR_figures.ipynb deleted file mode 100644 index 37e15cd..0000000 --- a/notebooks/paper_02_PS_FDR_figures.ipynb +++ /dev/null @@ -1,7738 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from importlib import reload\n", - "from IPython.core.interactiveshell import InteractiveShell\n", - "%load_ext autoreload\n", - "InteractiveShell.ast_node_interactivity = \"all\"\n", - "import logging\n", - "logging.basicConfig(\n", - " level=logging.INFO, format=\"%(asctime)s - %(name)s - %(levelname)s - %(message)s\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-30 11:26:11,306 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", - "2024-10-30 11:26:11,308 - numexpr.utils - INFO - NumExpr defaulting to 8 threads.\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", - " from pandas.core import (\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "import pandas as pd\n", - "import os\n", - "import sys\n", - "import matplotlib.pyplot as plt\n", - "\n", - "module_path = os.path.abspath(os.path.join(\"..\"))\n", - "if module_path not in sys.path:\n", - " sys.path.append(module_path)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Load data" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "swaps_config_path = \"/cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/config_20241003_074426_198157.yaml\"\n", - "ps_dir = \"exp_20241003_083433_946837\"\n", - "from utils.config import get_cfg_defaults\n", - "from utils.singleton_swaps_optimization import swaps_optimization_cfg\n", - "\n", - "cfg = get_cfg_defaults(swaps_optimization_cfg)\n", - "cfg.merge_from_file(swaps_config_path)\n", - "cfg.PEAK_SELECTION.merge_from_file(\n", - " os.path.join(\n", - " cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"updated_peak_selection_config.yaml\"\n", - " )\n", - ")\n", - "maxquant_result_ref = pd.read_pickle(cfg.DICT_PICKLE_PATH)\n", - "\n", - "mobility_values_df = pd.read_csv(os.path.join(cfg.RESULT_PATH, \"mobility_values.csv\"))\n", - "ms1scans = pd.read_csv(os.path.join(cfg.RESULT_PATH, \"ms1scans.csv\"))\n", - "pept_act_sum_ps_full_tdc = pd.read_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH,\n", - " \"peak_selection\",\n", - " ps_dir,\n", - " \"pept_act_sum_ps_full_tdc_fdr_thres.csv\",\n", - " )\n", - ")\n", - "test_pred_df = pd.read_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\", \"test_pred_df.csv\"\n", - " )\n", - ")\n", - "# test_pred_df = pd.merge(test_pred_df, maxquant_result_ref, on=[\"mz_rank\", \"Decoy\"])\n", - "test_pred_df = pd.merge(test_pred_df, maxquant_result_ref, on=[\"mz_rank\", \"Decoy\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Illustration of PS and Scoring model" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Loading training data and models" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-30 11:28:11,937 - peak_detection_2d.dataset.dataset - INFO - Transformation: [, , , ]\n", - "2024-10-30 11:28:11,938 - root - INFO - Use hint channel: True\n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "import torch\n", - "from peak_detection_2d.dataset.dataset import (\n", - " build_transformation,\n", - " MultiHDF5_MaskDataset,\n", - ")\n", - "\n", - "random_state = cfg.RANDOM_SEED\n", - "cfg_peak_selection = cfg.PEAK_SELECTION\n", - "hdf5_files = cfg_peak_selection.TRAINING_DATA\n", - "#cfg_peak_selection.DATASET.RESIZE_SHAPE = (64, 64)\n", - "cfg_peak_selection.DATASET.RESIZE_SHAPE = (258, 258)\n", - "transformation, cfg_peak_selection.DATASET = build_transformation(\n", - " cfg_peak_selection.DATASET\n", - ")\n", - "use_hint_channel = \"hint\" in cfg_peak_selection.DATASET.INPUT_CHANNELS\n", - "logging.info(\"Use hint channel: %s\", use_hint_channel)\n", - "dataset = MultiHDF5_MaskDataset(\n", - " hdf5_files[:5],\n", - " use_hint_channel=use_hint_channel,\n", - " transforms=transformation,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-03 10:54:25,692 - root - INFO - best_seg_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/15min_5to35_6R_120min_lib_im_ref_20241002_205908_418520/peak_selection/exp_20241002_223219_829060/model_backups/bst_seg_model_0.7582.pt\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-03 10:54:26,548 - peak_detection_2d.model.seg_model - INFO - Dropout applied to classifier with rate 0.5\n", - "2024-10-03 10:54:32,461 - root - INFO - best_cls_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/15min_5to35_6R_120min_lib_im_ref_20241002_205908_418520/peak_selection/exp_20241002_223219_829060/model_backups/bst_cls_model_0.9086.pt\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from peak_detection_2d.model.build_model import build_model\n", - "\n", - "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", - "best_seg_model_path = cfg.PEAK_SELECTION.MODEL.RESUME_PATH\n", - "best_cls_model_path = cfg.PEAK_SELECTION.CLSMODEL.RESUME_PATH\n", - "# Load models\n", - "bst_seg_model = build_model(cfg.PEAK_SELECTION.MODEL)\n", - "checkpoint = torch.load(best_seg_model_path, map_location=device)\n", - "logging.info(\"best_seg_model_path: %s\", best_seg_model_path)\n", - "bst_seg_model.load_state_dict(checkpoint[\"model_state_dict\"])\n", - "\n", - "bst_cls_model = build_model(cfg.PEAK_SELECTION.CLSMODEL)\n", - "checkpoint = torch.load(best_cls_model_path, map_location=device)\n", - "logging.info(\"best_cls_model_path: %s\", best_cls_model_path)\n", - "bst_cls_model.load_state_dict(checkpoint[\"model_state_dict\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plot illustration" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-03 10:58:37,463 - root - INFO - Is target: 1\n", - "2024-10-03 10:58:37,465 - root - INFO - mask sum: 1765.912652457106\n", - "2024-10-03 10:58:37,466 - root - INFO - hint channel sum: -2921.0\n", - "2024-10-03 10:58:37,489 - peak_detection_2d.utils - INFO - hint channel sum: -292100000.0\n", - "2024-10-03 10:58:37,491 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -7000000., -15800000., -14400000., -32200000., -21700000., -48600000.,\n", - " -20800000., -46400000., -13400000., -30000000., -6100000., -13600000.,\n", - " 400000., 4000000., 2600000., 24000000., 4800000., 44100000.,\n", - " 6900000., 64200000., 5600000., 52000000., 3500000., 32000000.,\n", - " 1300000., 11900000., -8600000., -7700000., -21400000., -19200000.,\n", - " -34300000., -30700000., -40000000., -35800000., -27200000., -24300000.,\n", - " -14400000., -12900000., -1500000., -1400000.], dtype=torch.float64)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from peak_detection_2d.utils import single_inference\n", - "\n", - "seg_output, cls_output = single_inference(\n", - " datapoint=dataset[2], seg_model=bst_seg_model, cls_model=bst_cls_model\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-03 11:00:26,574 - root - INFO - Is target: 1\n", - "2024-10-03 11:00:26,576 - root - INFO - mask sum: 1765.912652457106\n", - "2024-10-03 11:00:26,577 - root - INFO - hint channel sum: -2921.0\n", - "2024-10-03 11:00:26,594 - peak_detection_2d.utils - INFO - seg_out shape: torch.Size([258, 258])\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%autoreload 2\n", - "from peak_detection_2d.utils import plot_data_points_illustration\n", - "image, hint, label = dataset[2]\n", - "logging.info(\"Is target: %s\", label[\"target\"])\n", - "to_plot = {\n", - " # \"data\": image[0].cpu(),\n", - " # \"hint_idx\": hint.cpu(),\n", - " \"mask\": label[\"mask\"][0].cpu(),\n", - " #\"hint_channel\": (image[2].cpu()) * 100000,\n", - " \"seg_out\": seg_output[0][0].cpu(),\n", - "}\n", - "logging.info(\"mask sum: %s\", label[\"mask\"][0].sum().item())\n", - "\n", - "logging.info(\"hint channel sum: %s\", image[2].sum().item())\n", - "plot_data_points_illustration(to_plot, zoom_in=False, label=\"hide\", log_data=False)" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-03 11:14:44,648 - root - INFO - Is target: 1\n", - "2024-10-03 11:14:44,649 - root - INFO - mask sum: 1765.912652457106\n", - "2024-10-03 11:14:44,691 - root - INFO - hint channel sum: -2921.0\n", - "2024-10-03 11:14:44,705 - root - INFO - add label\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " source Decoy mz_rank MS1_frame_idx_left_exp MS1_frame_idx_right_exp \\\n", - "6494 both False 11887 605.0 616.0 \n", - "\n", - " MS1_frame_idx_left_ref MS1_frame_idx_center_ref \\\n", - "6494 587 625 \n", - "\n", - " MS1_frame_idx_right_ref IM_search_idx_left IM_search_idx_right \\\n", - "6494 663 0.0 327.0 \n", - "\n", - " IM_search_idx_center \n", - "6494 90 \n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%autoreload 2\n", - "%matplotlib inline\n", - "from torch import layout\n", - "from peak_detection_2d.utils import plot_data_points_illustration\n", - "\n", - "# load dataset\n", - "i = 2\n", - "image, hint, label = dataset[i]\n", - "seg_output, cls_output = single_inference(\n", - " datapoint=dataset[i], seg_model=bst_seg_model, cls_model=bst_cls_model\n", - ")\n", - "logging.info(\"Is target: %s\", label[\"target\"])\n", - "to_plot = {\n", - " #\"data\": image[0].cpu(),\n", - " #\"hint_idx\": hint.cpu(),\n", - " \"mask\": label[\"mask\"][0].cpu(),\n", - " #\"hint_channel\": (image[2].cpu())*100000,\n", - " #\"seg_out\": seg_output[0][0].cpu(),\n", - "}\n", - "logging.info(\"mask sum: %s\", label[\"mask\"][0].sum().item())\n", - "\n", - "logging.info(\"hint channel sum: %s\", image[2].sum().item())\n", - "plot_data_points_illustration(to_plot, zoom_in=False, label=\"mask\", log_data=True)\n", - "\n", - "row = maxquant_result_ref[maxquant_result_ref[\"mz_rank\"] == label[\"pept_mz_rank\"]]\n", - "if (True) and (not row[\"Decoy\"].values[0]):\n", - " logging.info(\"add label\")\n", - "else:\n", - " logging.info(\"no label since it is decoys\")\n", - "print(\n", - " row[\n", - " [\n", - " \"source\",\n", - " \"Decoy\",\n", - " \"mz_rank\",\n", - " \"MS1_frame_idx_left_exp\",\n", - " \"MS1_frame_idx_right_exp\",\n", - " \"MS1_frame_idx_left_ref\",\n", - " \"MS1_frame_idx_center_ref\",\n", - " \"MS1_frame_idx_right_ref\",\n", - " \"IM_search_idx_left\",\n", - " \"IM_search_idx_right\",\n", - " \"IM_search_idx_center\",\n", - " \n", - " ]\n", - " ]\n", - ")\n", - "figure_path = os.path.join(cfg.RESULT_PATH, \"paper_figures/example_illustrations\")\n", - "os.makedirs(figure_path, exist_ok=True)\n", - "plt.savefig(os.path.join(figure_path, \"example_mask_11887.png\"), dpi=300, format = \"png\", bbox_inches='tight')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Characterizing RT and 1/K0 accuracy" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.025385155871059828" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from utils.metrics import RT_metrics\n", - "\n", - "rt_metrics = RT_metrics(\n", - " maxquant_result_ref.loc[\n", - " (maxquant_result_ref[\"source\"] == \"both\") & (maxquant_result_ref[\"Decoy\"] == 0),\n", - " \"mobility_values_center_exp\",\n", - " ],\n", - " maxquant_result_ref.loc[\n", - " (maxquant_result_ref[\"source\"] == \"both\") & (maxquant_result_ref[\"Decoy\"] == 0),\n", - " \"mobility_values_center_ref\",\n", - " ],\n", - ")\n", - "rt_metrics.CalcDeltaRTwidth()" - ] - }, - { - "cell_type": "code", - "execution_count": 93, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "count 44731.000000\n", - "mean 0.079299\n", - "std 0.036600\n", - "min 0.010497\n", - "25% 0.053957\n", - "50% 0.071868\n", - "75% 0.095912\n", - "max 0.406215\n", - "Name: 1/K0 length, dtype: float64" - ] - }, - "execution_count": 93, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "maxquant_result_ref.loc[\n", - " (maxquant_result_ref[\"source\"] == \"both\") & (maxquant_result_ref[\"Decoy\"] == 0),\n", - " \"1/K0 length\",\n", - "].describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "prediction 1/K0: 0.047358468378823085" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Testset: Generate example images" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "metadata": {}, - "outputs": [], - "source": [ - "%autoreload 2\n", - "from peak_detection_2d.infer_on_pept_act import infer_on_pept_act\n", - "\n", - "test_pred_df_low_conf_decoys = test_pred_df[\n", - " (test_pred_df[\"target_decoy_score\"] < 0.5) & (test_pred_df[\"Decoy\"] == 1) & (test_pred_df[\"per_image_weighted_iou_metric\"] < 0.5)\n", - "]\n", - "test_pred_df_low_conf_decoys = test_pred_df_low_conf_decoys.sample(10)\n", - "infer_on_pept_act(\n", - " cfg=cfg,\n", - " best_seg_model_path=cfg.PEAK_SELECTION.MODEL.RESUME_PATH,\n", - " best_cls_model_path=cfg.PEAK_SELECTION.CLSMODEL.RESUME_PATH,\n", - " maxquant_dict=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"].isin(test_pred_df_low_conf_decoys[\"mz_rank\"])\n", - " ],\n", - " ps_exp_dir=os.path.join(\n", - " \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures\", \"fig2_PS\"\n", - " ),\n", - " plot_samples=True,\n", - " add_label_mask=True,\n", - " dataset_name=\"test_low_conf_decoy\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-18 17:16:24,580 - peak_detection_2d.dataset.dataset - INFO - Transformation: [, , , ]\n", - "2024-10-18 17:16:26,563 - peak_detection_2d.infer_on_pept_act - INFO - best_seg_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_seg_model_0.7183.pt\n", - "2024-10-18 17:16:27,334 - peak_detection_2d.model.seg_model - INFO - Dropout applied to classifier with rate 0.5\n", - "2024-10-18 17:16:27,782 - peak_detection_2d.infer_on_pept_act - INFO - best_cls_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_cls_model_0.8768.pt\n", - "2024-10-18 17:16:27,854 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 0 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-18 17:16:34,861 - peak_detection_2d.utils - INFO - Sample indices: [2 1 0]\n", - "2024-10-18 17:16:35,018 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:16:35,038 - peak_detection_2d.utils - INFO - hint channel sum: -3.0\n", - "2024-10-18 17:16:35,039 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 180., 51., 541., 153., 497., 141., 137., 39., -164., -179.,\n", - " -386., -420., -253., -275., -31., -34.], dtype=torch.float64)\n", - "2024-10-18 17:16:35,043 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:35,045 - peak_detection_2d.utils - INFO - Masked area 1844.0759402813665\n", - "2024-10-18 17:16:35,046 - peak_detection_2d.utils - INFO - Masked intensity sum 173970.86\n", - "2024-10-18 17:16:35,048 - peak_detection_2d.utils - INFO - Pred masked intensity sum 168717.06\n", - "2024-10-18 17:16:35,049 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:35,931 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_799.png\n", - "2024-10-18 17:16:36,931 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_799.svg\n", - "2024-10-18 17:16:37,094 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:16:37,109 - peak_detection_2d.utils - INFO - hint channel sum: -4831.0\n", - "2024-10-18 17:16:37,110 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([-133., -13., -424., -41., -416., -40., -124., -12., -62., -21.,\n", - " -321., -110., -427., -146., -167., -57., -3., -143., -10., -443.,\n", - " -10., -420., -3., -121., -200., -105., -422., -221., -218., -114.,\n", - " 139., 30., 416., 89., 383., 82., 105., 23., -5., -235.,\n", - " -12., -535., -7., -328., -1., -28.], dtype=torch.float64)\n", - "2024-10-18 17:16:37,114 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:37,116 - peak_detection_2d.utils - INFO - Masked area 1220.775461415457\n", - "2024-10-18 17:16:37,117 - peak_detection_2d.utils - INFO - Masked intensity sum 13247.09\n", - "2024-10-18 17:16:37,118 - peak_detection_2d.utils - INFO - Pred masked intensity sum 12292.87\n", - "2024-10-18 17:16:37,119 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:38,002 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_8570.png\n", - "2024-10-18 17:16:38,981 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_8570.svg\n", - "2024-10-18 17:16:39,123 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:16:39,139 - peak_detection_2d.utils - INFO - hint channel sum: -1568.0\n", - "2024-10-18 17:16:39,140 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([-264., -25., -641., -61., -433., -41., -56., -5., 172., 23.,\n", - " 544., 73., 517., 69., 144., 19., -111., -25., -464., -105.,\n", - " -543., -122., -190., -43.], dtype=torch.float64)\n", - "2024-10-18 17:16:39,143 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:39,145 - peak_detection_2d.utils - INFO - Masked area 2920.821648084952\n", - "2024-10-18 17:16:39,146 - peak_detection_2d.utils - INFO - Masked intensity sum 216956.40\n", - "2024-10-18 17:16:39,148 - peak_detection_2d.utils - INFO - Pred masked intensity sum 207236.49\n", - "2024-10-18 17:16:39,149 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:40,016 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_3008.png\n", - "2024-10-18 17:16:40,998 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_3008.svg\n", - "2024-10-18 17:16:41,000 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 4 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-18 17:16:52,641 - peak_detection_2d.utils - INFO - Sample indices: [1 0]\n", - "2024-10-18 17:16:52,825 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:16:52,856 - peak_detection_2d.utils - INFO - hint channel sum: -14.0\n", - "2024-10-18 17:16:52,858 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 20., 126., 65., 412., 65., 412., 20., 126., -105., -139.,\n", - " -249., -330., -166., -220., -22., -29.], dtype=torch.float64)\n", - "2024-10-18 17:16:52,865 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:52,868 - peak_detection_2d.utils - INFO - Masked area 1593.651122625216\n", - "2024-10-18 17:16:52,870 - peak_detection_2d.utils - INFO - Masked intensity sum 35773.17\n", - "2024-10-18 17:16:52,872 - peak_detection_2d.utils - INFO - Pred masked intensity sum 31555.70\n", - "2024-10-18 17:16:52,873 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:53,775 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_53933.png\n", - "2024-10-18 17:16:54,726 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_53933.svg\n", - "2024-10-18 17:16:54,887 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:16:54,908 - peak_detection_2d.utils - INFO - hint channel sum: 32.0\n", - "2024-10-18 17:16:54,910 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 39., 94., 127., 307., 127., 307., 39., 94., -19., -29.,\n", - " -135., -206., -199., -304., -83., -127.], dtype=torch.float64)\n", - "2024-10-18 17:16:54,914 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:54,916 - peak_detection_2d.utils - INFO - Masked area 801.8670058139533\n", - "2024-10-18 17:16:54,917 - peak_detection_2d.utils - INFO - Masked intensity sum 12476.61\n", - "2024-10-18 17:16:54,919 - peak_detection_2d.utils - INFO - Pred masked intensity sum 11367.56\n", - "2024-10-18 17:16:54,920 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:16:55,788 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_52496.png\n", - "2024-10-18 17:16:56,748 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_52496.svg\n", - "2024-10-18 17:16:56,752 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 9 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-18 17:17:05,944 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-18 17:17:06,116 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:17:06,135 - peak_detection_2d.utils - INFO - hint channel sum: 1026.0\n", - "2024-10-18 17:17:06,136 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 32., 96., 99., 298., 96., 289., 29., 87.], dtype=torch.float64)\n", - "2024-10-18 17:17:06,141 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:06,142 - peak_detection_2d.utils - INFO - Masked area 774.5330948121643\n", - "2024-10-18 17:17:06,144 - peak_detection_2d.utils - INFO - Masked intensity sum 7939.20\n", - "2024-10-18 17:17:06,146 - peak_detection_2d.utils - INFO - Pred masked intensity sum 7087.49\n", - "2024-10-18 17:17:06,147 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:06,997 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_114188.png\n", - "2024-10-18 17:17:07,937 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_114188.svg\n", - "2024-10-18 17:17:07,939 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 10 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-18 17:17:16,858 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-18 17:17:17,028 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:17:17,046 - peak_detection_2d.utils - INFO - hint channel sum: -1.0\n", - "2024-10-18 17:17:17,047 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 32., 96., 99., 298., 96., 289., 29., 87., -23., -130.,\n", - " -64., -357., -55., -306., -14., -78.], dtype=torch.float64)\n", - "2024-10-18 17:17:17,050 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:17,052 - peak_detection_2d.utils - INFO - Masked area 1902.6305761422034\n", - "2024-10-18 17:17:17,054 - peak_detection_2d.utils - INFO - Masked intensity sum 185473.22\n", - "2024-10-18 17:17:17,055 - peak_detection_2d.utils - INFO - Pred masked intensity sum 148806.62\n", - "2024-10-18 17:17:17,056 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:17,874 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_128953.png\n", - "2024-10-18 17:17:18,814 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_128953.svg\n", - "2024-10-18 17:17:18,815 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 8 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-18 17:17:28,431 - peak_detection_2d.utils - INFO - Sample indices: [1 0]\n", - "2024-10-18 17:17:28,600 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:17:28,616 - peak_detection_2d.utils - INFO - hint channel sum: 18.0\n", - "2024-10-18 17:17:28,617 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([-229., -4., -491., -9., -263., -5., -1., 30., 89., 98.,\n", - " 293., 98., 293., 30., 89.], dtype=torch.float64)\n", - "2024-10-18 17:17:28,620 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:28,621 - peak_detection_2d.utils - INFO - Masked area 2667.5694692904\n", - "2024-10-18 17:17:28,623 - peak_detection_2d.utils - INFO - Masked intensity sum 40733.08\n", - "2024-10-18 17:17:28,625 - peak_detection_2d.utils - INFO - Pred masked intensity sum 41818.25\n", - "2024-10-18 17:17:28,626 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:29,461 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_106085.png\n", - "2024-10-18 17:17:30,412 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_106085.svg\n", - "2024-10-18 17:17:30,587 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:17:30,601 - peak_detection_2d.utils - INFO - hint channel sum: -1.0\n", - "2024-10-18 17:17:30,602 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -20., -169., -48., -412., -33., -288., -5., -45., 34., 102.,\n", - " 102., 305., 93., 280., 26., 77.], dtype=torch.float64)\n", - "2024-10-18 17:17:30,606 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:30,607 - peak_detection_2d.utils - INFO - Masked area 1058.4152577826997\n", - "2024-10-18 17:17:30,609 - peak_detection_2d.utils - INFO - Masked intensity sum 58877.46\n", - "2024-10-18 17:17:30,610 - peak_detection_2d.utils - INFO - Pred masked intensity sum 59006.40\n", - "2024-10-18 17:17:30,611 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:31,427 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_109921.png\n", - "2024-10-18 17:17:32,370 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_109921.svg\n", - "2024-10-18 17:17:32,371 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 13 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-18 17:17:40,778 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-18 17:17:40,935 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-18 17:17:40,953 - peak_detection_2d.utils - INFO - hint channel sum: 1019.0\n", - "2024-10-18 17:17:40,954 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 34., 102., 102., 305., 93., 280., 26., 77.], dtype=torch.float64)\n", - "2024-10-18 17:17:40,957 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:40,959 - peak_detection_2d.utils - INFO - Masked area 2539.807341037293\n", - "2024-10-18 17:17:40,960 - peak_detection_2d.utils - INFO - Masked intensity sum 16718.92\n", - "2024-10-18 17:17:40,961 - peak_detection_2d.utils - INFO - Pred masked intensity sum 13745.51\n", - "2024-10-18 17:17:40,962 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-18 17:17:41,782 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_172641.png\n", - "2024-10-18 17:17:42,727 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_3_4/inferred_samples_test_low_conf_high_wiou_target/PS_model_prediction_sample_172641.svg\n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from peak_detection_2d.infer_on_pept_act import infer_on_pept_act\n", - "\n", - "test_pred_df_low_conf_high_wiou_targets = test_pred_df[\n", - " (test_pred_df[\"target_decoy_score\"] < 0.2) & (test_pred_df[\"Decoy\"] == 0) & (test_pred_df[\"per_image_weighted_iou_metric\"] > 0.8) & (test_pred_df[\"sum_intensity\"] > 100)\n", - "]\n", - "test_pred_df_low_conf_high_wiou_targets = test_pred_df_low_conf_high_wiou_targets.sample(10)\n", - "infer_on_pept_act(\n", - " cfg=cfg,\n", - " best_seg_model_path=cfg.PEAK_SELECTION.MODEL.RESUME_PATH,\n", - " best_cls_model_path=cfg.PEAK_SELECTION.CLSMODEL.RESUME_PATH,\n", - " maxquant_dict=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"].isin(test_pred_df_low_conf_high_wiou_targets[\"mz_rank\"])\n", - " ],\n", - " ps_exp_dir=os.path.join(\n", - " \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures\", \"fig2_3_4\"\n", - " ),\n", - " plot_samples=True,\n", - " add_label_mask=True,\n", - " dataset_name=\"test_low_conf_high_wiou_target\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [], - "source": [ - "%autoreload 2\n", - "from peak_detection_2d.infer_on_pept_act import infer_on_pept_act\n", - "test_pred_df_high_conf_decoys = test_pred_df[\n", - " (test_pred_df[\"target_decoy_score\"] > 0.8) & (test_pred_df[\"Decoy\"] == 1)\n", - "]\n", - "test_pred_df_high_conf_sample = test_pred_df_high_conf_decoys.sample(10)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 15:38:27,899 - peak_detection_2d.dataset.dataset - INFO - Transformation: [, , , ]\n", - "2024-10-16 15:38:29,701 - peak_detection_2d.infer_on_pept_act - INFO - best_seg_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_seg_model_0.7183.pt\n", - "2024-10-16 15:38:30,461 - peak_detection_2d.model.seg_model - INFO - Dropout applied to classifier with rate 0.5\n", - "2024-10-16 15:38:30,901 - peak_detection_2d.infer_on_pept_act - INFO - best_cls_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_cls_model_0.8768.pt\n", - "2024-10-16 15:38:30,951 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 6 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:38:43,205 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-10-16 15:38:43,361 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:38:43,379 - peak_detection_2d.utils - INFO - hint channel sum: 1360.0\n", - "2024-10-16 15:38:43,380 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([155., 4., 508., 13., 508., 13., 155., 4.], dtype=torch.float64)\n", - "2024-10-16 15:38:43,384 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:38:43,386 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:38:43,387 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:38:43,389 - peak_detection_2d.utils - INFO - Pred masked intensity sum 8260.73\n", - "2024-10-16 15:38:43,390 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:38:44,233 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_75259.png\n", - "2024-10-16 15:38:45,186 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_75259.svg\n", - "2024-10-16 15:38:45,362 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:38:45,377 - peak_detection_2d.utils - INFO - hint channel sum: 8.0\n", - "2024-10-16 15:38:45,378 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -73., -38., -264., -139., -287., -151., 38., 91., -96., -50.,\n", - " 126., 298., 126., 298., 38., 91.], dtype=torch.float64)\n", - "2024-10-16 15:38:45,382 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:38:45,383 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:38:45,385 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:38:45,386 - peak_detection_2d.utils - INFO - Pred masked intensity sum 87046.02\n", - "2024-10-16 15:38:45,387 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:38:46,212 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_82731.png\n", - "2024-10-16 15:38:47,167 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_82731.svg\n", - "2024-10-16 15:38:47,169 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 1 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:38:57,262 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:38:57,435 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:38:57,450 - peak_detection_2d.utils - INFO - hint channel sum: -2407.0\n", - "2024-10-16 15:38:57,451 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -2., -61., -13., -379., -19., -537., -8., -219., -25., -2.,\n", - " -338., -28., -564., -47., -251., -21., 132., 26., 431., 84.,\n", - " 431., 84., 132., 26., -8., -224., -19., -542., -13., -375.,\n", - " -2., -56.], dtype=torch.float64)\n", - "2024-10-16 15:38:57,455 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:38:57,456 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:38:57,458 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:38:57,459 - peak_detection_2d.utils - INFO - Pred masked intensity sum 243880.29\n", - "2024-10-16 15:38:57,460 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:38:58,301 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_19411.png\n", - "2024-10-16 15:38:59,252 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_19411.svg\n", - "2024-10-16 15:38:59,254 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 2 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:39:10,140 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:39:10,306 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:39:10,324 - peak_detection_2d.utils - INFO - hint channel sum: -1182.0\n", - "2024-10-16 15:39:10,325 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 140., 34., 419., 101., 385., 92., 106., 25., -59., -189.,\n", - " -144., -458., -99., -316., -15., -48., -242., -549., -336., -29.],\n", - " dtype=torch.float64)\n", - "2024-10-16 15:39:10,328 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:10,330 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:39:10,332 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:39:10,333 - peak_detection_2d.utils - INFO - Pred masked intensity sum 87246.49\n", - "2024-10-16 15:39:10,334 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:11,172 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_35177.png\n", - "2024-10-16 15:39:12,121 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_35177.svg\n", - "2024-10-16 15:39:12,122 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 5 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:39:24,457 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-10-16 15:39:24,635 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:39:24,650 - peak_detection_2d.utils - INFO - hint channel sum: -2.0\n", - "2024-10-16 15:39:24,651 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 32., 96., 99., 298., 96., 289., 29., 87., -18., -25.,\n", - " -131., -181., -198., -273., -85., -117.], dtype=torch.float64)\n", - "2024-10-16 15:39:24,654 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:24,656 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:39:24,657 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:39:24,659 - peak_detection_2d.utils - INFO - Pred masked intensity sum 4934.86\n", - "2024-10-16 15:39:24,659 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:25,487 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_73181.png\n", - "2024-10-16 15:39:26,439 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_73181.svg\n", - "2024-10-16 15:39:26,623 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:39:26,639 - peak_detection_2d.utils - INFO - hint channel sum: 1219.0\n", - "2024-10-16 15:39:26,640 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([118., 34., 366., 106., 355., 102., 107., 31.], dtype=torch.float64)\n", - "2024-10-16 15:39:26,644 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:26,645 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:39:26,647 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:39:26,648 - peak_detection_2d.utils - INFO - Pred masked intensity sum 23724.66\n", - "2024-10-16 15:39:26,649 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:27,473 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_66292.png\n", - "2024-10-16 15:39:28,422 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_66292.svg\n", - "2024-10-16 15:39:28,423 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 10 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:39:41,180 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-10-16 15:39:41,352 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:39:41,369 - peak_detection_2d.utils - INFO - hint channel sum: 9.0\n", - "2024-10-16 15:39:41,370 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -5., -156., -13., -416., -11., -334., -2., -73., 34., 102.,\n", - " 102., 305., 93., 280., 26., 77.], dtype=torch.float64)\n", - "2024-10-16 15:39:41,374 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:41,375 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:39:41,377 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:39:41,378 - peak_detection_2d.utils - INFO - Pred masked intensity sum 59328.47\n", - "2024-10-16 15:39:41,379 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:42,210 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_135137.png\n", - "2024-10-16 15:39:43,160 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_135137.svg\n", - "2024-10-16 15:39:43,337 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:39:43,351 - peak_detection_2d.utils - INFO - hint channel sum: 1.0\n", - "2024-10-16 15:39:43,352 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([-158., -21., -397., -52., -293., -38., -53., -7., 30., 89.,\n", - " 98., 293., 98., 293., 30., 89.], dtype=torch.float64)\n", - "2024-10-16 15:39:43,355 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:43,357 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:39:43,358 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:39:43,360 - peak_detection_2d.utils - INFO - Pred masked intensity sum 35486.17\n", - "2024-10-16 15:39:43,361 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:44,184 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_135210.png\n", - "2024-10-16 15:39:45,131 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_135210.svg\n", - "2024-10-16 15:39:45,132 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 0 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:39:55,270 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:39:55,425 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:39:55,440 - peak_detection_2d.utils - INFO - hint channel sum: 1575.0\n", - "2024-10-16 15:39:55,441 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([185., 25., 554., 74., 510., 68., 140., 19.], dtype=torch.float64)\n", - "2024-10-16 15:39:55,445 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:55,448 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:39:55,449 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:39:55,450 - peak_detection_2d.utils - INFO - Pred masked intensity sum 36615.17\n", - "2024-10-16 15:39:55,451 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:39:56,281 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_7368.png\n", - "2024-10-16 15:39:57,228 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_7368.svg\n", - "2024-10-16 15:39:57,229 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 9 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:40:11,856 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:40:12,003 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:40:12,021 - peak_detection_2d.utils - INFO - hint channel sum: 1020.0\n", - "2024-10-16 15:40:12,022 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 30., 89., 98., 293., 98., 293., 30., 89.], dtype=torch.float64)\n", - "2024-10-16 15:40:12,025 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:40:12,027 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 15:40:12,028 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 15:40:12,030 - peak_detection_2d.utils - INFO - Pred masked intensity sum 14120.61\n", - "2024-10-16 15:40:12,031 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:40:12,929 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_113560.png\n", - "2024-10-16 15:40:13,919 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_high_conf_non_isolated_decoy/PS_model_prediction_sample_113560.svg\n" - ] - } - ], - "source": [ - "infer_on_pept_act(\n", - " cfg=cfg,\n", - " best_seg_model_path=cfg.PEAK_SELECTION.MODEL.RESUME_PATH,\n", - " best_cls_model_path=cfg.PEAK_SELECTION.CLSMODEL.RESUME_PATH,\n", - " maxquant_dict=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"].isin(test_pred_df_high_conf_sample[\"mz_rank\"])\n", - " ],\n", - " ps_exp_dir=os.path.join(\n", - " \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures\", \"fig2_PS\"\n", - " ),\n", - " plot_samples=True,\n", - " add_label_mask=True,\n", - " dataset_name=\"test_high_conf_decoy\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [], - "source": [ - "test_pred_df_low_wiou_targets = test_pred_df[\n", - " (test_pred_df[\"per_image_weighted_iou_metric\"] < 0.2) & (test_pred_df[\"Decoy\"] == 0)\n", - "]\n", - "test_pred_df_low_wiou_targets = test_pred_df_low_wiou_targets.sample(10)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 15:53:37,443 - peak_detection_2d.dataset.dataset - INFO - Transformation: [, , , ]\n", - "2024-10-16 15:53:39,244 - peak_detection_2d.infer_on_pept_act - INFO - best_seg_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_seg_model_0.7183.pt\n", - "2024-10-16 15:53:40,042 - peak_detection_2d.model.seg_model - INFO - Dropout applied to classifier with rate 0.5\n", - "2024-10-16 15:53:40,457 - peak_detection_2d.infer_on_pept_act - INFO - best_cls_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_cls_model_0.8768.pt\n", - "2024-10-16 15:53:40,510 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 2 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:53:51,969 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:53:52,134 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:53:52,162 - peak_detection_2d.utils - INFO - hint channel sum: 1256.0\n", - "2024-10-16 15:53:52,163 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([117., 30., 383., 98., 383., 98., 117., 30.], dtype=torch.float64)\n", - "2024-10-16 15:53:52,169 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:53:52,171 - peak_detection_2d.utils - INFO - Masked area 1848.1657455884633\n", - "2024-10-16 15:53:52,174 - peak_detection_2d.utils - INFO - Masked intensity sum 50904.65\n", - "2024-10-16 15:53:52,176 - peak_detection_2d.utils - INFO - Pred masked intensity sum 29864.70\n", - "2024-10-16 15:53:52,177 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:53:53,129 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_34435.png\n", - "2024-10-16 15:53:54,098 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_34435.svg\n", - "2024-10-16 15:53:54,099 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 8 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:54:10,922 - peak_detection_2d.utils - INFO - Sample indices: [2 0 1]\n", - "2024-10-16 15:54:11,124 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:54:11,147 - peak_detection_2d.utils - INFO - hint channel sum: -1.0\n", - "2024-10-16 15:54:11,148 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -5., -38., -36., -276., -55., -416., -23., -178., 32., 96.,\n", - " 99., 298., 96., 289., 29., 87.], dtype=torch.float64)\n", - "2024-10-16 15:54:11,152 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:11,154 - peak_detection_2d.utils - INFO - Masked area 552.9874776386406\n", - "2024-10-16 15:54:11,156 - peak_detection_2d.utils - INFO - Masked intensity sum 11997.66\n", - "2024-10-16 15:54:11,157 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 15:54:11,158 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:12,003 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_111264.png\n", - "2024-10-16 15:54:12,948 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_111264.svg\n", - "2024-10-16 15:54:13,107 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:54:13,123 - peak_detection_2d.utils - INFO - hint channel sum: 1019.0\n", - "2024-10-16 15:54:13,124 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 34., 102., 102., 305., 93., 280., 26., 77.], dtype=torch.float64)\n", - "2024-10-16 15:54:13,127 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:13,128 - peak_detection_2d.utils - INFO - Masked area 2566.4034405218\n", - "2024-10-16 15:54:13,130 - peak_detection_2d.utils - INFO - Masked intensity sum 19106.90\n", - "2024-10-16 15:54:13,131 - peak_detection_2d.utils - INFO - Pred masked intensity sum 22192.44\n", - "2024-10-16 15:54:13,132 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:13,949 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_106427.png\n", - "2024-10-16 15:54:14,894 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_106427.svg\n", - "2024-10-16 15:54:15,071 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:54:15,086 - peak_detection_2d.utils - INFO - hint channel sum: -2030.0\n", - "2024-10-16 15:54:15,087 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -44., -109., -121., -301., -103., -257., -26., -65., -1., -220.,\n", - " -3., -481., -2., -279., -18., 32., 96., 99., 298., 96.,\n", - " 289., 29., 87., -30., -184., -68., -415., -42., -257., -4.,\n", - " -26.], dtype=torch.float64)\n", - "2024-10-16 15:54:15,090 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:15,092 - peak_detection_2d.utils - INFO - Masked area 1075.49011053101\n", - "2024-10-16 15:54:15,093 - peak_detection_2d.utils - INFO - Masked intensity sum 11833.67\n", - "2024-10-16 15:54:15,095 - peak_detection_2d.utils - INFO - Pred masked intensity sum 9474.98\n", - "2024-10-16 15:54:15,096 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:15,920 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_100782.png\n", - "2024-10-16 15:54:16,861 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_100782.svg\n", - "2024-10-16 15:54:16,862 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 3 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:54:28,661 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:54:28,833 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:54:28,850 - peak_detection_2d.utils - INFO - hint channel sum: 1134.0\n", - "2024-10-16 15:54:28,851 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 39., 94., 127., 307., 127., 307., 39., 94.], dtype=torch.float64)\n", - "2024-10-16 15:54:28,855 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:28,856 - peak_detection_2d.utils - INFO - Masked area 1764.3556438467153\n", - "2024-10-16 15:54:28,858 - peak_detection_2d.utils - INFO - Masked intensity sum 144346.12\n", - "2024-10-16 15:54:28,859 - peak_detection_2d.utils - INFO - Pred masked intensity sum 34468.23\n", - "2024-10-16 15:54:28,860 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:29,681 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_40963.png\n", - "2024-10-16 15:54:30,648 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_40963.svg\n", - "2024-10-16 15:54:30,649 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 7 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:54:48,629 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:54:48,809 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:54:48,824 - peak_detection_2d.utils - INFO - hint channel sum: 8.0\n", - "2024-10-16 15:54:48,825 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 32., 96., 99., 298., -76., -63., 96., 289., -222., -184.,\n", - " 29., 87., -202., -168., -56., -47.], dtype=torch.float64)\n", - "2024-10-16 15:54:48,829 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:48,831 - peak_detection_2d.utils - INFO - Masked area 1919.9278473464522\n", - "2024-10-16 15:54:48,833 - peak_detection_2d.utils - INFO - Masked intensity sum 48667.36\n", - "2024-10-16 15:54:48,835 - peak_detection_2d.utils - INFO - Pred masked intensity sum 426496.77\n", - "2024-10-16 15:54:48,836 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:54:49,675 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_97775.png\n", - "2024-10-16 15:54:50,615 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_97775.svg\n", - "2024-10-16 15:54:50,616 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 12 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:55:00,613 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:55:00,784 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:55:00,798 - peak_detection_2d.utils - INFO - hint channel sum: -1012.0\n", - "2024-10-16 15:55:00,799 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([-136., -3., -396., -7., -360., -7., -100., -2., 32., 96.,\n", - " 99., 298., 96., 289., 29., 87., -133., -44., -335., -112.,\n", - " -252., -84., -50., -17.], dtype=torch.float64)\n", - "2024-10-16 15:55:00,803 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:55:00,804 - peak_detection_2d.utils - INFO - Masked area 1993.3315444245675\n", - "2024-10-16 15:55:00,806 - peak_detection_2d.utils - INFO - Masked intensity sum 25187.92\n", - "2024-10-16 15:55:00,807 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 15:55:00,808 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:55:01,624 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_155998.png\n", - "2024-10-16 15:55:02,566 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_155998.svg\n", - "2024-10-16 15:55:02,568 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 6 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:55:14,847 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:55:15,015 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:55:15,033 - peak_detection_2d.utils - INFO - hint channel sum: -10.0\n", - "2024-10-16 15:55:15,034 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -39., -134., -115., -395., -104., -356., -28., -95., 117., 30.,\n", - " 383., 98., 383., 98., 117., 30.], dtype=torch.float64)\n", - "2024-10-16 15:55:15,038 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:55:15,040 - peak_detection_2d.utils - INFO - Masked area 6137.600696909348\n", - "2024-10-16 15:55:15,041 - peak_detection_2d.utils - INFO - Masked intensity sum 124986.18\n", - "2024-10-16 15:55:15,043 - peak_detection_2d.utils - INFO - Pred masked intensity sum 10533.85\n", - "2024-10-16 15:55:15,043 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:55:15,872 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_83449.png\n", - "2024-10-16 15:55:16,816 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_83449.svg\n", - "2024-10-16 15:55:16,817 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 11 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:55:31,383 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:55:31,546 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:55:31,561 - peak_detection_2d.utils - INFO - hint channel sum: 1020.0\n", - "2024-10-16 15:55:31,562 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 30., 89., 98., 293., 98., 293., 30., 89.], dtype=torch.float64)\n", - "2024-10-16 15:55:31,565 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:55:31,567 - peak_detection_2d.utils - INFO - Masked area 2625.93997217253\n", - "2024-10-16 15:55:31,568 - peak_detection_2d.utils - INFO - Masked intensity sum 107340.86\n", - "2024-10-16 15:55:31,570 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 15:55:31,571 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:55:32,386 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_148879.png\n", - "2024-10-16 15:55:33,325 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_148879.svg\n", - "2024-10-16 15:55:33,327 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 13 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 15:55:43,186 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 15:55:43,345 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 15:55:43,361 - peak_detection_2d.utils - INFO - hint channel sum: 0.0\n", - "2024-10-16 15:55:43,362 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([-127., -162., -275., -351., -152., -194., -4., -5., 76., 93.,\n", - " 228., 279., 209., 256., 58., 71.], dtype=torch.float64)\n", - "2024-10-16 15:55:43,365 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:55:43,367 - peak_detection_2d.utils - INFO - Masked area 5044.277455587187\n", - "2024-10-16 15:55:43,368 - peak_detection_2d.utils - INFO - Masked intensity sum 396434.01\n", - "2024-10-16 15:55:43,370 - peak_detection_2d.utils - INFO - Pred masked intensity sum 676.89\n", - "2024-10-16 15:55:43,370 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 15:55:44,185 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_163845.png\n", - "2024-10-16 15:55:45,131 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_wiou_targets/PS_model_prediction_sample_163845.svg\n" - ] - } - ], - "source": [ - "infer_on_pept_act(\n", - " cfg=cfg,\n", - " best_seg_model_path=cfg.PEAK_SELECTION.MODEL.RESUME_PATH,\n", - " best_cls_model_path=cfg.PEAK_SELECTION.CLSMODEL.RESUME_PATH,\n", - " maxquant_dict=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"].isin(test_pred_df_low_wiou_targets[\"mz_rank\"])\n", - " ],\n", - " ps_exp_dir=os.path.join(\n", - " \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures\", \"fig2_PS\"\n", - " ),\n", - " add_label_mask=True,\n", - " plot_samples=True,\n", - " dataset_name=\"test_low_wiou_targets\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [], - "source": [ - "test_pred_df_mid_high_wiou_targets = test_pred_df[\n", - " (test_pred_df[\"per_image_weighted_iou_metric\"] > 0.5) & (test_pred_df[\"Decoy\"] == 0)\n", - "]\n", - "test_pred_df_mid_high_wiou_targets_sample = test_pred_df_mid_high_wiou_targets.sample(\n", - " 10\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 16:03:06,756 - peak_detection_2d.dataset.dataset - INFO - Transformation: [, , , ]\n", - "2024-10-16 16:03:08,605 - peak_detection_2d.infer_on_pept_act - INFO - best_seg_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_seg_model_0.7183.pt\n", - "2024-10-16 16:03:09,356 - peak_detection_2d.model.seg_model - INFO - Dropout applied to classifier with rate 0.5\n", - "2024-10-16 16:03:09,775 - peak_detection_2d.infer_on_pept_act - INFO - best_cls_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_cls_model_0.8768.pt\n", - "2024-10-16 16:03:09,825 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 0 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:03:16,524 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:03:16,662 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:03:16,686 - peak_detection_2d.utils - INFO - hint channel sum: 1698.0\n", - "2024-10-16 16:03:16,687 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([156., 70., 468., 210., 430., 193., 118., 53.], dtype=torch.float64)\n", - "2024-10-16 16:03:16,690 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:16,692 - peak_detection_2d.utils - INFO - Masked area 1844.8414263565887\n", - "2024-10-16 16:03:16,693 - peak_detection_2d.utils - INFO - Masked intensity sum 32771.43\n", - "2024-10-16 16:03:16,694 - peak_detection_2d.utils - INFO - Pred masked intensity sum 32266.83\n", - "2024-10-16 16:03:16,695 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:17,509 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_1381.png\n", - "2024-10-16 16:03:18,449 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_1381.svg\n", - "2024-10-16 16:03:18,450 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 3 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:03:30,027 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-10-16 16:03:30,213 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:03:30,228 - peak_detection_2d.utils - INFO - hint channel sum: 1212.0\n", - "2024-10-16 16:03:30,229 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([110., 32., 360., 104., 360., 104., 110., 32.], dtype=torch.float64)\n", - "2024-10-16 16:03:30,232 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:30,234 - peak_detection_2d.utils - INFO - Masked area 1258.6331666417477\n", - "2024-10-16 16:03:30,236 - peak_detection_2d.utils - INFO - Masked intensity sum 38752.61\n", - "2024-10-16 16:03:30,237 - peak_detection_2d.utils - INFO - Pred masked intensity sum 29966.14\n", - "2024-10-16 16:03:30,238 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:31,062 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_44385.png\n", - "2024-10-16 16:03:32,006 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_44385.svg\n", - "2024-10-16 16:03:32,118 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:03:32,132 - peak_detection_2d.utils - INFO - hint channel sum: 1360.0\n", - "2024-10-16 16:03:32,133 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 58., 101., 189., 332., 189., 332., 58., 101.], dtype=torch.float64)\n", - "2024-10-16 16:03:32,136 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:32,137 - peak_detection_2d.utils - INFO - Masked area 1843.6738839882382\n", - "2024-10-16 16:03:32,139 - peak_detection_2d.utils - INFO - Masked intensity sum 16266.25\n", - "2024-10-16 16:03:32,140 - peak_detection_2d.utils - INFO - Pred masked intensity sum 15632.96\n", - "2024-10-16 16:03:32,141 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:32,952 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_47383.png\n", - "2024-10-16 16:03:33,890 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_47383.svg\n", - "2024-10-16 16:03:33,891 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 2 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:03:46,366 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-10-16 16:03:46,533 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:03:46,551 - peak_detection_2d.utils - INFO - hint channel sum: 1164.0\n", - "2024-10-16 16:03:46,552 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([130., 15., 403., 47., 391., 46., 118., 14.], dtype=torch.float64)\n", - "2024-10-16 16:03:46,555 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:46,557 - peak_detection_2d.utils - INFO - Masked area 3883.9009996873856\n", - "2024-10-16 16:03:46,559 - peak_detection_2d.utils - INFO - Masked intensity sum 273140.07\n", - "2024-10-16 16:03:46,560 - peak_detection_2d.utils - INFO - Pred masked intensity sum 266978.67\n", - "2024-10-16 16:03:46,561 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:47,379 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_30805.png\n", - "2024-10-16 16:03:48,334 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_30805.svg\n", - "2024-10-16 16:03:48,478 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:03:48,492 - peak_detection_2d.utils - INFO - hint channel sum: -1118.0\n", - "2024-10-16 16:03:48,493 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -58., -48., -227., -188., -265., -220., -96., -80., 32., 124.,\n", - " 98., 383., 95., 371., 29., 112., -258., -29., -534., -59.,\n", - " -270., -30.], dtype=torch.float64)\n", - "2024-10-16 16:03:48,496 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:48,498 - peak_detection_2d.utils - INFO - Masked area 1239.2806121375202\n", - "2024-10-16 16:03:48,499 - peak_detection_2d.utils - INFO - Masked intensity sum 16379.41\n", - "2024-10-16 16:03:48,500 - peak_detection_2d.utils - INFO - Pred masked intensity sum 17534.49\n", - "2024-10-16 16:03:48,501 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:49,313 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_30271.png\n", - "2024-10-16 16:03:50,252 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_30271.svg\n", - "2024-10-16 16:03:50,253 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 13 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:03:58,897 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:03:59,057 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:03:59,072 - peak_detection_2d.utils - INFO - hint channel sum: 38.0\n", - "2024-10-16 16:03:59,073 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 104., 35., 323., 109., 313., 105., 94., 32., -85., -88.,\n", - " -224., -231., -180., -186., -41., -42.], dtype=torch.float64)\n", - "2024-10-16 16:03:59,076 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:59,077 - peak_detection_2d.utils - INFO - Masked area 3772.032976153891\n", - "2024-10-16 16:03:59,079 - peak_detection_2d.utils - INFO - Masked intensity sum 84224.55\n", - "2024-10-16 16:03:59,080 - peak_detection_2d.utils - INFO - Pred masked intensity sum 88066.04\n", - "2024-10-16 16:03:59,081 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:03:59,898 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_161713.png\n", - "2024-10-16 16:04:00,843 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_161713.svg\n", - "2024-10-16 16:04:00,844 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 7 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:04:11,622 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:04:11,796 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:04:11,812 - peak_detection_2d.utils - INFO - hint channel sum: 7.0\n", - "2024-10-16 16:04:11,813 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 34., 102., 102., 305., 93., 280., 26., 77., -123., -119.,\n", - " -259., -251., -132., -128.], dtype=torch.float64)\n", - "2024-10-16 16:04:11,817 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:04:11,819 - peak_detection_2d.utils - INFO - Masked area 527.83860067581\n", - "2024-10-16 16:04:11,820 - peak_detection_2d.utils - INFO - Masked intensity sum 12295.14\n", - "2024-10-16 16:04:11,821 - peak_detection_2d.utils - INFO - Pred masked intensity sum 21335.99\n", - "2024-10-16 16:04:11,822 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:04:12,638 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_97680.png\n", - "2024-10-16 16:04:13,578 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_97680.svg\n", - "2024-10-16 16:04:13,579 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 9 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:04:22,924 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-10-16 16:04:23,109 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:04:23,124 - peak_detection_2d.utils - INFO - hint channel sum: -1016.0\n", - "2024-10-16 16:04:23,125 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 30., 89., 98., 293., 98., 293., 30., 89., -1., -6.,\n", - " -25., -253., -46., -456., -21., -210., -90., -145., -194., -312.,\n", - " -105., -169., -1., -2.], dtype=torch.float64)\n", - "2024-10-16 16:04:23,129 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:04:23,130 - peak_detection_2d.utils - INFO - Masked area 1887.7932816537468\n", - "2024-10-16 16:04:23,131 - peak_detection_2d.utils - INFO - Masked intensity sum 107779.10\n", - "2024-10-16 16:04:23,133 - peak_detection_2d.utils - INFO - Pred masked intensity sum 104303.58\n", - "2024-10-16 16:04:23,133 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:04:23,953 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_117730.png\n", - "2024-10-16 16:04:24,892 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_117730.svg\n", - "2024-10-16 16:04:25,033 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:04:25,048 - peak_detection_2d.utils - INFO - hint channel sum: -1.0\n", - "2024-10-16 16:04:25,049 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 34., 102., 102., 305., 93., 280., 26., 77., -15., -127.,\n", - " -43., -370., -38., -330., -10., -87.], dtype=torch.float64)\n", - "2024-10-16 16:04:25,052 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:04:25,053 - peak_detection_2d.utils - INFO - Masked area 3014.685829362653\n", - "2024-10-16 16:04:25,055 - peak_detection_2d.utils - INFO - Masked intensity sum 63181.48\n", - "2024-10-16 16:04:25,056 - peak_detection_2d.utils - INFO - Pred masked intensity sum 62501.23\n", - "2024-10-16 16:04:25,057 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:04:25,871 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_123030.png\n", - "2024-10-16 16:04:26,810 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_123030.svg\n", - "2024-10-16 16:04:26,811 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 8 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:04:39,822 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:04:39,981 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:04:39,998 - peak_detection_2d.utils - INFO - hint channel sum: 0.0\n", - "2024-10-16 16:04:39,999 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 86., 47., 265., 146., 257., 142., 78., 43., -78., -30.,\n", - " -278., -108., -305., -119., -105., -41.], dtype=torch.float64)\n", - "2024-10-16 16:04:40,002 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:04:40,004 - peak_detection_2d.utils - INFO - Masked area 1713.949426568971\n", - "2024-10-16 16:04:40,005 - peak_detection_2d.utils - INFO - Masked intensity sum 10272.33\n", - "2024-10-16 16:04:40,006 - peak_detection_2d.utils - INFO - Pred masked intensity sum 10296.10\n", - "2024-10-16 16:04:40,007 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:04:40,826 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_110015.png\n", - "2024-10-16 16:04:41,772 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_mid_high_wiou_targets/PS_model_prediction_sample_110015.svg\n" - ] - } - ], - "source": [ - "infer_on_pept_act(\n", - " cfg=cfg,\n", - " best_seg_model_path=cfg.PEAK_SELECTION.MODEL.RESUME_PATH,\n", - " best_cls_model_path=cfg.PEAK_SELECTION.CLSMODEL.RESUME_PATH,\n", - " maxquant_dict=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"].isin(\n", - " test_pred_df_mid_high_wiou_targets_sample[\"mz_rank\"]\n", - " )\n", - " ],\n", - " ps_exp_dir=os.path.join(\n", - " \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures\", \"fig2_PS\"\n", - " ),\n", - " add_label_mask=True,\n", - " plot_samples=True,\n", - " dataset_name=\"test_mid_high_wiou_targets\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "test_pred_df_low_int_targets = test_pred_df[\n", - " (test_pred_df[\"sum_intensity\"] < 100) & (test_pred_df[\"Decoy\"] == 0)\n", - "]\n", - "test_pred_df_low_int_targets_sample = test_pred_df_low_int_targets.sample(20)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-16 16:06:10,678 - peak_detection_2d.dataset.dataset - INFO - Transformation: [, , , ]\n", - "2024-10-16 16:06:12,502 - peak_detection_2d.infer_on_pept_act - INFO - best_seg_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_seg_model_0.7183.pt\n", - "2024-10-16 16:06:13,247 - peak_detection_2d.model.seg_model - INFO - Dropout applied to classifier with rate 0.5\n", - "2024-10-16 16:06:13,650 - peak_detection_2d.infer_on_pept_act - INFO - best_cls_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/peak_selection/exp_20241003_083433_946837/model_backups/bst_cls_model_0.8768.pt\n", - "2024-10-16 16:06:13,701 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 6 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:06:25,680 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:06:25,840 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:06:25,855 - peak_detection_2d.utils - INFO - hint channel sum: 4.0\n", - "2024-10-16 16:06:25,857 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -87., -4., -345., -15., -400., -18., -141., -6., 30., 89.,\n", - " 98., 293., 98., 293., 30., 89.], dtype=torch.float64)\n", - "2024-10-16 16:06:25,860 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:25,861 - peak_detection_2d.utils - INFO - Masked area 810.8228980322012\n", - "2024-10-16 16:06:25,863 - peak_detection_2d.utils - INFO - Masked intensity sum 37536.22\n", - "2024-10-16 16:06:25,864 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:06:25,865 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:26,793 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_78494.png\n", - "2024-10-16 16:06:27,787 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_78494.svg\n", - "2024-10-16 16:06:27,789 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 12 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:06:37,190 - peak_detection_2d.utils - INFO - Sample indices: [2 1 0]\n", - "2024-10-16 16:06:37,359 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:06:37,376 - peak_detection_2d.utils - INFO - hint channel sum: 1020.0\n", - "2024-10-16 16:06:37,377 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 30., 89., 98., 293., 98., 293., 30., 89.], dtype=torch.float64)\n", - "2024-10-16 16:06:37,380 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:37,382 - peak_detection_2d.utils - INFO - Masked area 1929.2236135957064\n", - "2024-10-16 16:06:37,383 - peak_detection_2d.utils - INFO - Masked intensity sum 15176.25\n", - "2024-10-16 16:06:37,385 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:06:37,386 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:38,253 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_150040.png\n", - "2024-10-16 16:06:39,225 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_150040.svg\n", - "2024-10-16 16:06:39,374 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:06:39,390 - peak_detection_2d.utils - INFO - hint channel sum: 1019.0\n", - "2024-10-16 16:06:39,391 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 34., 102., 102., 305., 93., 280., 26., 77.], dtype=torch.float64)\n", - "2024-10-16 16:06:39,394 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:39,396 - peak_detection_2d.utils - INFO - Masked area 1692.8278123254868\n", - "2024-10-16 16:06:39,397 - peak_detection_2d.utils - INFO - Masked intensity sum 5551.98\n", - "2024-10-16 16:06:39,398 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:06:39,399 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:40,212 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_157825.png\n", - "2024-10-16 16:06:41,187 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_157825.svg\n", - "2024-10-16 16:06:41,327 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:06:41,342 - peak_detection_2d.utils - INFO - hint channel sum: 1020.0\n", - "2024-10-16 16:06:41,343 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 30., 89., 98., 293., 98., 293., 30., 89.], dtype=torch.float64)\n", - "2024-10-16 16:06:41,346 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:41,347 - peak_detection_2d.utils - INFO - Masked area 825.0844762472677\n", - "2024-10-16 16:06:41,349 - peak_detection_2d.utils - INFO - Masked intensity sum 3967.46\n", - "2024-10-16 16:06:41,350 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:06:41,351 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:42,162 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_157687.png\n", - "2024-10-16 16:06:43,120 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_157687.svg\n", - "2024-10-16 16:06:43,121 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 0 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:06:49,645 - peak_detection_2d.utils - INFO - Sample indices: [1 0]\n", - "2024-10-16 16:06:49,778 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:06:50,390 - peak_detection_2d.utils - INFO - hint channel sum: 1756.0\n", - "2024-10-16 16:06:50,392 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 56., 178., 168., 533., 154., 490., 42., 135.], dtype=torch.float64)\n", - "2024-10-16 16:06:50,395 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:50,396 - peak_detection_2d.utils - INFO - Masked area 957.9503812720135\n", - "2024-10-16 16:06:50,398 - peak_detection_2d.utils - INFO - Masked intensity sum 20629.07\n", - "2024-10-16 16:06:50,399 - peak_detection_2d.utils - INFO - Pred masked intensity sum 45.24\n", - "2024-10-16 16:06:50,400 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:51,239 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_5860.png\n", - "2024-10-16 16:06:52,185 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_5860.svg\n", - "2024-10-16 16:06:52,332 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:06:52,348 - peak_detection_2d.utils - INFO - hint channel sum: 2.0\n", - "2024-10-16 16:06:52,349 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 56., 178., 168., 533., 154., 490., 42., 135., -225., -141.,\n", - " -512., -321., -314., -197., -27., -17.], dtype=torch.float64)\n", - "2024-10-16 16:06:52,352 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:52,353 - peak_detection_2d.utils - INFO - Masked area 3004.1914582419186\n", - "2024-10-16 16:06:52,355 - peak_detection_2d.utils - INFO - Masked intensity sum 184248.69\n", - "2024-10-16 16:06:52,356 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:06:52,357 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:06:53,180 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_2468.png\n", - "2024-10-16 16:06:54,126 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_2468.svg\n", - "2024-10-16 16:06:54,127 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 3 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:07:05,441 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-10-16 16:07:05,603 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:07:05,620 - peak_detection_2d.utils - INFO - hint channel sum: -121.0\n", - "2024-10-16 16:07:05,621 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 146., 6., 453., 20., 439., 19., 132., 6., -21., -83.,\n", - " -90., -365., -112., -455., -43., -173.], dtype=torch.float64)\n", - "2024-10-16 16:07:05,624 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:05,626 - peak_detection_2d.utils - INFO - Masked area 1812.3886960824711\n", - "2024-10-16 16:07:05,628 - peak_detection_2d.utils - INFO - Masked intensity sum 27556.86\n", - "2024-10-16 16:07:05,629 - peak_detection_2d.utils - INFO - Pred masked intensity sum 68.77\n", - "2024-10-16 16:07:05,630 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:06,448 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_37314.png\n", - "2024-10-16 16:07:07,391 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_37314.svg\n", - "2024-10-16 16:07:07,551 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:07:07,567 - peak_detection_2d.utils - INFO - hint channel sum: 56.0\n", - "2024-10-16 16:07:07,568 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([-113., -14., -411., -51., 88., 66., -447., -55., 288., 215.,\n", - " -149., -18., 288., 215., 88., 66.], dtype=torch.float64)\n", - "2024-10-16 16:07:07,571 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:07,572 - peak_detection_2d.utils - INFO - Masked area 1356.1767045729966\n", - "2024-10-16 16:07:07,574 - peak_detection_2d.utils - INFO - Masked intensity sum 15766.64\n", - "2024-10-16 16:07:07,575 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:07:07,576 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:08,394 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_38459.png\n", - "2024-10-16 16:07:09,337 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_38459.svg\n", - "2024-10-16 16:07:09,338 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 13 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:07:17,800 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-10-16 16:07:17,958 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:07:17,973 - peak_detection_2d.utils - INFO - hint channel sum: 1078.0\n", - "2024-10-16 16:07:17,974 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 48., 78., 156., 257., 156., 257., 48., 78.], dtype=torch.float64)\n", - "2024-10-16 16:07:17,977 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:17,978 - peak_detection_2d.utils - INFO - Masked area 2661.113636184212\n", - "2024-10-16 16:07:17,980 - peak_detection_2d.utils - INFO - Masked intensity sum 18432.18\n", - "2024-10-16 16:07:17,981 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:07:17,982 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:18,814 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_168931.png\n", - "2024-10-16 16:07:19,758 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_168931.svg\n", - "2024-10-16 16:07:19,910 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:07:19,926 - peak_detection_2d.utils - INFO - hint channel sum: 1110.0\n", - "2024-10-16 16:07:19,927 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([127., 3., 415., 10., 415., 10., 127., 3.], dtype=torch.float64)\n", - "2024-10-16 16:07:19,930 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:19,931 - peak_detection_2d.utils - INFO - Masked area 2726.4515368125517\n", - "2024-10-16 16:07:19,933 - peak_detection_2d.utils - INFO - Masked intensity sum 25249.13\n", - "2024-10-16 16:07:19,934 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:07:19,935 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:20,754 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_164048.png\n", - "2024-10-16 16:07:21,698 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_164048.svg\n", - "2024-10-16 16:07:21,699 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 1 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:07:31,309 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:07:31,457 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:07:31,472 - peak_detection_2d.utils - INFO - hint channel sum: -6635.0\n", - "2024-10-16 16:07:31,473 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -64., -142., -204., -454., -200., -445., -60., -133., 156., 70.,\n", - " 468., 210., 430., 193., 118., 53., -132., -77., -417., -245.,\n", - " -404., -237., -119., -70., -10., -305., -23., -705., -15., -447.,\n", - " -2., -47., -1., -1., -195., -259., -365., -484., -170., -226.,\n", - " -38., -205., -108., -580., -94., -501., -23., -126.],\n", - " dtype=torch.float64)\n", - "2024-10-16 16:07:31,476 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:31,478 - peak_detection_2d.utils - INFO - Masked area 1761.8319053447572\n", - "2024-10-16 16:07:31,479 - peak_detection_2d.utils - INFO - Masked intensity sum 96787.92\n", - "2024-10-16 16:07:31,481 - peak_detection_2d.utils - INFO - Pred masked intensity sum 2.48\n", - "2024-10-16 16:07:31,481 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:32,303 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_14504.png\n", - "2024-10-16 16:07:33,249 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_14504.svg\n", - "2024-10-16 16:07:33,250 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 2 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:07:44,179 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:07:44,336 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:07:44,351 - peak_detection_2d.utils - INFO - hint channel sum: 1394.0\n", - "2024-10-16 16:07:44,352 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 47., 116., 154., 380., 154., 380., 47., 116.], dtype=torch.float64)\n", - "2024-10-16 16:07:44,355 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:44,357 - peak_detection_2d.utils - INFO - Masked area 731.3760697127934\n", - "2024-10-16 16:07:44,358 - peak_detection_2d.utils - INFO - Masked intensity sum 9978.45\n", - "2024-10-16 16:07:44,359 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:07:44,360 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:45,179 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_31299.png\n", - "2024-10-16 16:07:46,123 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_31299.svg\n", - "2024-10-16 16:07:46,124 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 5 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:07:58,009 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:07:58,183 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:07:58,200 - peak_detection_2d.utils - INFO - hint channel sum: -2081.0\n", - "2024-10-16 16:07:58,201 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -74., -123., -178., -295., -122., -202., -18., -29., -46., -13.,\n", - " -260., -76., -356., -104., -142., -42., -17., -76., -68., -302.,\n", - " -78., -349., -28., -123., 104., 18., 340., 58., 340., 58.,\n", - " 104., 18.], dtype=torch.float64)\n", - "2024-10-16 16:07:58,205 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:58,207 - peak_detection_2d.utils - INFO - Masked area 5906.875348837209\n", - "2024-10-16 16:07:58,208 - peak_detection_2d.utils - INFO - Masked intensity sum 115491.18\n", - "2024-10-16 16:07:58,209 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:07:58,210 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:07:59,062 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_73945.png\n", - "2024-10-16 16:08:00,003 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_73945.svg\n", - "2024-10-16 16:08:00,004 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 11 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:08:09,044 - peak_detection_2d.utils - INFO - Sample indices: [0 2 1]\n", - "2024-10-16 16:08:09,228 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:08:09,242 - peak_detection_2d.utils - INFO - hint channel sum: -2044.0\n", - "2024-10-16 16:08:09,243 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([-201., -6., -461., -15., -289., -9., -28., -1., -60., -193.,\n", - " -125., -400., -61., -195., 34., 102., 102., 305., 93., 280.,\n", - " 26., 77., -30., -46., -138., -210., -172., -261., -64., -98.],\n", - " dtype=torch.float64)\n", - "2024-10-16 16:08:09,247 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:09,248 - peak_detection_2d.utils - INFO - Masked area 2746.6654740608224\n", - "2024-10-16 16:08:09,250 - peak_detection_2d.utils - INFO - Masked intensity sum 69378.18\n", - "2024-10-16 16:08:09,251 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:08:09,252 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:10,080 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_145266.png\n", - "2024-10-16 16:08:11,022 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_145266.svg\n", - "2024-10-16 16:08:11,177 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:08:11,193 - peak_detection_2d.utils - INFO - hint channel sum: 1026.0\n", - "2024-10-16 16:08:11,194 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 32., 96., 99., 298., 96., 289., 29., 87.], dtype=torch.float64)\n", - "2024-10-16 16:08:11,196 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:11,198 - peak_detection_2d.utils - INFO - Masked area 1672.4072748956473\n", - "2024-10-16 16:08:11,199 - peak_detection_2d.utils - INFO - Masked intensity sum 17762.92\n", - "2024-10-16 16:08:11,201 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:08:11,202 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:12,017 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_138601.png\n", - "2024-10-16 16:08:12,956 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_138601.svg\n", - "2024-10-16 16:08:13,109 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:08:13,123 - peak_detection_2d.utils - INFO - hint channel sum: -108.0\n", - "2024-10-16 16:08:13,124 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 125., 6., 410., 19., 410., 19., 125., 6., -22., -6.,\n", - " -282., -73., -465., -121., -206., -53.], dtype=torch.float64)\n", - "2024-10-16 16:08:13,127 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:13,129 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 16:08:13,130 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 16:08:13,131 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:08:13,132 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:13,971 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_137672.png\n", - "2024-10-16 16:08:14,907 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_137672.svg\n", - "2024-10-16 16:08:14,908 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 8 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:08:24,518 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:08:24,695 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:08:24,709 - peak_detection_2d.utils - INFO - hint channel sum: 1020.0\n", - "2024-10-16 16:08:24,710 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 30., 89., 98., 293., 98., 293., 30., 89.], dtype=torch.float64)\n", - "2024-10-16 16:08:24,713 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:24,715 - peak_detection_2d.utils - INFO - Masked area 1363.8742955580165\n", - "2024-10-16 16:08:24,716 - peak_detection_2d.utils - INFO - Masked intensity sum 38227.76\n", - "2024-10-16 16:08:24,717 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:08:24,718 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:25,535 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_101079.png\n", - "2024-10-16 16:08:26,477 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_101079.svg\n", - "2024-10-16 16:08:26,479 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 9 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:08:35,665 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-10-16 16:08:35,843 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:08:35,859 - peak_detection_2d.utils - INFO - hint channel sum: 1019.0\n", - "2024-10-16 16:08:35,860 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 34., 102., 102., 305., 93., 280., 26., 77.], dtype=torch.float64)\n", - "2024-10-16 16:08:35,863 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:35,866 - peak_detection_2d.utils - INFO - Masked area 0.0\n", - "2024-10-16 16:08:35,868 - peak_detection_2d.utils - INFO - Masked intensity sum 0.00\n", - "2024-10-16 16:08:35,869 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:08:35,870 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:36,686 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_112564.png\n", - "2024-10-16 16:08:37,626 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_112564.svg\n", - "2024-10-16 16:08:37,627 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 4 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-10-16 16:08:55,909 - peak_detection_2d.utils - INFO - Sample indices: [1 0]\n", - "2024-10-16 16:08:56,051 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:08:56,066 - peak_detection_2d.utils - INFO - hint channel sum: 1124.0\n", - "2024-10-16 16:08:56,067 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 40., 101., 123., 312., 119., 302., 36., 91.], dtype=torch.float64)\n", - "2024-10-16 16:08:56,070 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:56,072 - peak_detection_2d.utils - INFO - Masked area 1313.3953488372092\n", - "2024-10-16 16:08:56,073 - peak_detection_2d.utils - INFO - Masked intensity sum 9552.01\n", - "2024-10-16 16:08:56,075 - peak_detection_2d.utils - INFO - Pred masked intensity sum 35.60\n", - "2024-10-16 16:08:56,076 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:56,904 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_58708.png\n", - "2024-10-16 16:08:57,846 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_58708.svg\n", - "2024-10-16 16:08:57,999 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-10-16 16:08:58,014 - peak_detection_2d.utils - INFO - hint channel sum: 1019.0\n", - "2024-10-16 16:08:58,015 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 34., 102., 102., 305., 93., 280., 26., 77.], dtype=torch.float64)\n", - "2024-10-16 16:08:58,018 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:58,020 - peak_detection_2d.utils - INFO - Masked area 1428.3481974063645\n", - "2024-10-16 16:08:58,021 - peak_detection_2d.utils - INFO - Masked intensity sum 58876.44\n", - "2024-10-16 16:08:58,023 - peak_detection_2d.utils - INFO - Pred masked intensity sum 0.00\n", - "2024-10-16 16:08:58,024 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-10-16 16:08:58,840 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_60646.png\n", - "2024-10-16 16:08:59,782 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/inferred_samples_test_low_intensity_targets/PS_model_prediction_sample_60646.svg\n" - ] - } - ], - "source": [ - "infer_on_pept_act(\n", - " cfg=cfg,\n", - " best_seg_model_path=cfg.PEAK_SELECTION.MODEL.RESUME_PATH,\n", - " best_cls_model_path=cfg.PEAK_SELECTION.CLSMODEL.RESUME_PATH,\n", - " maxquant_dict=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"].isin(\n", - " test_pred_df_low_int_targets_sample[\"mz_rank\"]\n", - " )\n", - " ],\n", - " ps_exp_dir=os.path.join(\n", - " \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures\", \"fig2_PS\"\n", - " ),\n", - " add_label_mask=True,\n", - " plot_samples=True,\n", - " dataset_name=\"test_low_intensity_targets\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Figure 2: Peak selection model performance\n", - "Use only test_pred_df" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Choose colors" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from utils.tools import plot_colortable\n", - "import matplotlib.colors as mcolors\n", - "\n", - "plot_colortable(mcolors.CSS4_COLORS)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "from matplotlib.colors import ListedColormap\n", - "\n", - "custom_cmap = ListedColormap([\"#FF5733\", \"#33FF57\", \"#3357FF\"]) # Custom colors\n", - "custom_labels = [\"Targets\", \"Decoys\"] # Custom label names" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plot" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "test_pred_df_full = pd.merge(\n", - " left=test_pred_df,\n", - " right=maxquant_result_ref[[\"mz_rank\", \"Decoy\"]],\n", - " on=[\"mz_rank\", \"Decoy\"],\n", - " how=\"left\",\n", - ")\n", - "test_pred_df_full[\"Data\"] = \"Target\"\n", - "test_pred_df_full.loc[test_pred_df_full[\"Decoy\"], \"Data\"] = \"Decoy\"" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "ps_exp_dir = \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/\"\n", - "os.makedirs(ps_exp_dir, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Test set targets" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_837179/3333441363.py:2: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " test_pred_df_targets[\"Pass Intensity Filter\"] = (\n", - "/tmp/ipykernel_837179/3333441363.py:5: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " test_pred_df_targets[\"Pass Conf. Score Filter\"] = (\n", - "/tmp/ipykernel_837179/3333441363.py:8: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " test_pred_df_targets[\"Pass Both Filter\"] = (\n" - ] - } - ], - "source": [ - "test_pred_df_targets = test_pred_df_full.loc[~test_pred_df_full[\"Decoy\"]]\n", - "test_pred_df_targets[\"Pass Intensity Filter\"] = (\n", - " test_pred_df_targets[\"log_sum_intensity\"] >= 2\n", - ")\n", - "test_pred_df_targets[\"Pass Conf. Score Filter\"] = (\n", - " test_pred_df_targets[\"target_decoy_score\"] >= 0.2\n", - ")\n", - "test_pred_df_targets[\"Pass Both Filter\"] = (\n", - " test_pred_df_targets[\"Pass Intensity Filter\"]\n", - " & test_pred_df_targets[\"Pass Conf. Score Filter\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 14:31:10,216 - utils.plot - INFO - Data: target_decoy_score, log_sum_intensity, slope = 1.637, intercept = 3.388, Pearson's R = 0.6, Spearman's R = 0.57\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(array([4.9724484 , 4.73482148, 3.59636634, ..., 4.97061243, 4.05985257,\n", - " 4.60659222]),\n", - " array([0.11702096, 0.33817638, 0.51134877, ..., 0.02194875, 1.49574087,\n", - " 0.20808614]),\n", - " (array([ 0, 2, 6, ..., 8931, 8933, 8934]),))" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%autoreload 2\n", - "from utils.plot import plot_scatter\n", - "\n", - "plot_scatter(\n", - " x=test_pred_df_full[\"target_decoy_score\"],\n", - " y=test_pred_df_full[\"log_sum_intensity\"],\n", - " font_size=15,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'SWAPS Inferred Intensity (Log10)')" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Test Set Inferred Intensity')" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 14:37:35,179 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/hist_inferred_intensity_test_targets.png\n", - "2024-10-29 14:37:35,431 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/hist_inferred_intensity_test_targets.svg\n" - ] - } - ], - "source": [ - "import seaborn as sns\n", - "from utils.plot import save_plot\n", - "\n", - "line_width = 2\n", - "plt.rc(\"font\", size=20) # Set the default font size for all text elements\n", - "plt.figure(figsize=(8, 6))\n", - "ax = sns.histplot(\n", - " data=test_pred_df_targets,\n", - " x=\"log_sum_intensity\",\n", - " hue=\"Pass Intensity Filter\",\n", - " palette={False: \"#d8a6a6\", True: \"#a00000\"},\n", - " hue_order=[False, True],\n", - " # color=[\"olivedrab\", \"tomato\"],\n", - " multiple=\"stack\",\n", - " bins=20,\n", - ")\n", - "plt.xlabel(\"SWAPS Inferred Intensity (Log10)\")\n", - "plt.title(\"Test Set Inferred Intensity\")\n", - "# Set the width of all spines (top, right, bottom, left)\n", - "for spine in ax.spines.values():\n", - " spine.set_linewidth(line_width) # Increase this value for thicker lines\n", - "# Optional: you can also make tick marks thicker\n", - "ax.tick_params(width=line_width)\n", - "save_plot(\n", - " save_dir=ps_exp_dir,\n", - " fig_type_name=\"hist\",\n", - " fig_spec_name=\"inferred_intensity_test_targets\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'Weighted IoU')" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Test Set Weighted IoU')" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 14:42:14,255 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/hist_weighted_iou_test_targets.png\n", - "2024-10-29 14:42:14,498 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig2_PS/hist_weighted_iou_test_targets.svg\n" - ] - } - ], - "source": [ - "import seaborn as sns\n", - "\n", - "line_width = 2\n", - "plt.rc(\"font\", size=20) # Set the default font size for all text elements\n", - "plt.figure(figsize=(8, 6))\n", - "ax = sns.histplot(\n", - " data=test_pred_df_targets,\n", - " x=\"per_image_weighted_iou_metric\",\n", - " hue=\"Pass Intensity Filter\",\n", - " palette={False: \"#d8a6a6\", True: \"#a00000\"},\n", - " hue_order=[False, True],\n", - " # color=[\"olivedrab\", \"tomato\"],\n", - " multiple=\"stack\",\n", - " bins=20,\n", - ")\n", - "plt.xlabel(\"Weighted IoU\")\n", - "plt.title(\"Test Set Weighted IoU\")\n", - "# Set the width of all spines (top, right, bottom, left)\n", - "for spine in ax.spines.values():\n", - " spine.set_linewidth(line_width) # Increase this value for thicker lines\n", - "# Optional: you can also make tick marks thicker\n", - "ax.tick_params(width=line_width)\n", - "save_plot(\n", - " save_dir=ps_exp_dir,\n", - " fig_type_name=\"hist\",\n", - " fig_spec_name=\"weighted_iou_test_targets\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.7537675606641124" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.1478927203065134" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "test_pred_df_targets_filter_int = test_pred_df_targets[\n", - " test_pred_df_targets[\"Pass Intensity Filter\"]\n", - "]\n", - "(test_pred_df_targets_filter_int[\"per_image_weighted_iou_metric\"] > 0.8).sum() / len(\n", - " test_pred_df_targets_filter_int\n", - ")\n", - "(test_pred_df_targets_filter_int[\"per_image_weighted_iou_metric\"] < 0.2).sum() / len(\n", - " test_pred_df_targets_filter_int\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Figure 3: FDR Eval and Control" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Specific examples" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [], - "source": [ - "test_pred_df_targets_high_wiou_low_td_score = test_pred_df_targets.loc[\n", - " (test_pred_df_targets[\"per_image_weighted_iou_metric\"] > 0.8)\n", - " & (test_pred_df_targets[\"target_decoy_score\"] < 0.2)\n", - " & (test_pred_df_targets[\"log_sum_intensity\"] > 2)\n", - "].sample(10)" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-18 14:58:21,686 - peak_detection_2d.dataset.dataset - INFO - Transformation: [, , , ]\n", - "2024-09-18 14:58:23,722 - peak_detection_2d.infer_on_pept_act - INFO - best_seg_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/tims_ramp_time/120min_libaray_100ms_20240903_174407_457504/peak_selection/exp_20240903_193426_406274/model_backups/bst_seg_model_0.6696.pt\n", - "2024-09-18 14:58:24,979 - peak_detection_2d.infer_on_pept_act - INFO - best_cls_model_path: /cmnfs/proj/ORIGINS/SWAPS_exp/tims_ramp_time/120min_libaray_100ms_20240903_174407_457504/peak_selection/exp_20240903_193426_406274/model_backups/bst_cls_model_0.8871.pt\n", - "2024-09-18 14:58:25,031 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 8 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-09-18 14:58:35,288 - peak_detection_2d.utils - INFO - Sample indices: [1 2 0]\n", - "2024-09-18 14:58:35,568 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:58:35,592 - peak_detection_2d.utils - INFO - hint channel sum: 0.0\n", - "2024-09-18 14:58:35,594 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 9., 140., 24., 376., 26., 420., 12., 184., -74., -58.,\n", - " -215., -168., -260., -204., -119., -93.], dtype=torch.float64)\n", - "2024-09-18 14:58:35,599 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:58:35,602 - peak_detection_2d.utils - INFO - Masked area 1852.3539811450464\n", - "2024-09-18 14:58:35,605 - peak_detection_2d.utils - INFO - Masked intensity sum 12974.58\n", - "2024-09-18 14:58:35,606 - peak_detection_2d.utils - INFO - Pred masked intensity sum 13259.10\n", - "2024-09-18 14:58:35,607 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:58:36,707 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:58:36,728 - peak_detection_2d.utils - INFO - hint channel sum: 1191.0\n", - "2024-09-18 14:58:36,729 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 9., 140., 24., 376., 26., 420., 12., 184.], dtype=torch.float64)\n", - "2024-09-18 14:58:36,733 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:58:36,735 - peak_detection_2d.utils - INFO - Masked area 3247.722195447581\n", - "2024-09-18 14:58:36,736 - peak_detection_2d.utils - INFO - Masked intensity sum 15160.25\n", - "2024-09-18 14:58:36,738 - peak_detection_2d.utils - INFO - Pred masked intensity sum 15619.23\n", - "2024-09-18 14:58:36,739 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:58:37,704 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:58:37,727 - peak_detection_2d.utils - INFO - hint channel sum: 1191.0\n", - "2024-09-18 14:58:37,728 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 9., 140., 24., 376., 26., 420., 12., 184.], dtype=torch.float64)\n", - "2024-09-18 14:58:37,732 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:58:37,734 - peak_detection_2d.utils - INFO - Masked area 497.2595008508225\n", - "2024-09-18 14:58:37,736 - peak_detection_2d.utils - INFO - Masked intensity sum 3914.48\n", - "2024-09-18 14:58:37,737 - peak_detection_2d.utils - INFO - Pred masked intensity sum 4744.49\n", - "2024-09-18 14:58:37,738 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:58:38,594 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 5 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-09-18 14:58:49,476 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-09-18 14:58:49,603 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:58:49,619 - peak_detection_2d.utils - INFO - hint channel sum: 1473.0\n", - "2024-09-18 14:58:49,620 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([141., 43., 379., 116., 423., 129., 185., 57.], dtype=torch.float64)\n", - "2024-09-18 14:58:49,623 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:58:49,625 - peak_detection_2d.utils - INFO - Masked area 1233.9304934611187\n", - "2024-09-18 14:58:49,626 - peak_detection_2d.utils - INFO - Masked intensity sum 5663.13\n", - "2024-09-18 14:58:49,628 - peak_detection_2d.utils - INFO - Pred masked intensity sum 5607.75\n", - "2024-09-18 14:58:49,629 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:58:50,520 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 2 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-09-18 14:59:02,878 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-09-18 14:59:03,014 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:59:03,040 - peak_detection_2d.utils - INFO - hint channel sum: -1582.0\n", - "2024-09-18 14:59:03,041 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 63., 167., 153., 403., 153., 403., 63., 167., -36., -50.,\n", - " -171., -236., -289., -397., -154., -212., -19., -26., -3., -2.,\n", - " -205., -123., -407., -244., -283., -169., -80., -48.],\n", - " dtype=torch.float64)\n", - "2024-09-18 14:59:03,046 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:03,048 - peak_detection_2d.utils - INFO - Masked area 1021.9952615499717\n", - "2024-09-18 14:59:03,050 - peak_detection_2d.utils - INFO - Masked intensity sum 19218.03\n", - "2024-09-18 14:59:03,051 - peak_detection_2d.utils - INFO - Pred masked intensity sum 21646.77\n", - "2024-09-18 14:59:03,052 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:04,051 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:59:04,065 - peak_detection_2d.utils - INFO - hint channel sum: -1584.0\n", - "2024-09-18 14:59:04,067 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ -35., -121., -108., -376., -142., -494., -69., -239., 42., 124.,\n", - " 127., 372., 161., 474., 77., 226., -155., -71., -384., -174.,\n", - " -396., -180., -167., -76.], dtype=torch.float64)\n", - "2024-09-18 14:59:04,070 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:04,071 - peak_detection_2d.utils - INFO - Masked area 1148.212504861163\n", - "2024-09-18 14:59:04,073 - peak_detection_2d.utils - INFO - Masked intensity sum 20159.10\n", - "2024-09-18 14:59:04,075 - peak_detection_2d.utils - INFO - Pred masked intensity sum 21758.55\n", - "2024-09-18 14:59:04,076 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:04,902 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 6 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-09-18 14:59:14,620 - peak_detection_2d.utils - INFO - Sample indices: [0 1]\n", - "2024-09-18 14:59:14,747 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:59:14,762 - peak_detection_2d.utils - INFO - hint channel sum: 20.0\n", - "2024-09-18 14:59:14,763 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 10., 165., 25., 399., 25., 399., 10., 165., -3., -100.,\n", - " -10., -338., -14., -472., -7., -234.], dtype=torch.float64)\n", - "2024-09-18 14:59:14,766 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:14,768 - peak_detection_2d.utils - INFO - Masked area 1812.9655325576732\n", - "2024-09-18 14:59:14,770 - peak_detection_2d.utils - INFO - Masked intensity sum 40794.29\n", - "2024-09-18 14:59:14,771 - peak_detection_2d.utils - INFO - Pred masked intensity sum 43337.51\n", - "2024-09-18 14:59:14,772 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:15,720 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:59:15,736 - peak_detection_2d.utils - INFO - hint channel sum: 1198.0\n", - "2024-09-18 14:59:15,737 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 7., 117., 22., 351., 28., 447., 13., 213.], dtype=torch.float64)\n", - "2024-09-18 14:59:15,741 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:15,743 - peak_detection_2d.utils - INFO - Masked area 3642.926194378515\n", - "2024-09-18 14:59:15,745 - peak_detection_2d.utils - INFO - Masked intensity sum 43804.65\n", - "2024-09-18 14:59:15,746 - peak_detection_2d.utils - INFO - Pred masked intensity sum 39453.38\n", - "2024-09-18 14:59:15,748 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:16,600 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 0 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-09-18 14:59:24,648 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-09-18 14:59:24,758 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:59:24,782 - peak_detection_2d.utils - INFO - hint channel sum: -2146.0\n", - "2024-09-18 14:59:24,784 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([-123., -123., -345., -345., -414., -414., -191., -191., 182., 132.,\n", - " 440., 319., 440., 319., 182., 132., -107., -287., -228., -611.,\n", - " -185., -494., -64., -170.], dtype=torch.float64)\n", - "2024-09-18 14:59:24,790 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:24,793 - peak_detection_2d.utils - INFO - Masked area 2363.1725420860816\n", - "2024-09-18 14:59:24,794 - peak_detection_2d.utils - INFO - Masked intensity sum 30255.72\n", - "2024-09-18 14:59:24,795 - peak_detection_2d.utils - INFO - Pred masked intensity sum 25444.72\n", - "2024-09-18 14:59:24,797 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:25,664 - peak_detection_2d.infer_on_pept_act - INFO - Infering on pept batch 7 ...\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/peak_detection_2d/dataset/dataset.py:144: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " maxquant_dict[\n", - "2024-09-18 14:59:35,307 - peak_detection_2d.utils - INFO - Sample indices: [0]\n", - "2024-09-18 14:59:35,439 - peak_detection_2d.utils - INFO - Ori_image_raw shape: torch.Size([1, 258, 258])\n", - "2024-09-18 14:59:35,457 - peak_detection_2d.utils - INFO - hint channel sum: -1270.0\n", - "2024-09-18 14:59:35,458 - peak_detection_2d.utils - INFO - hint channel non zero values: tensor([ 10., 165., 25., 399., 25., 399., 10., 165., -76., -177.,\n", - " -152., -357., -109., -255., -32., -76., -213., -33., -434., -68.,\n", - " -321., -50., -99., -16.], dtype=torch.float64)\n", - "2024-09-18 14:59:35,462 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", - "2024-09-18 14:59:35,463 - peak_detection_2d.utils - INFO - Masked area 1151.1255498306662\n", - "2024-09-18 14:59:35,465 - peak_detection_2d.utils - INFO - Masked intensity sum 13820.66\n", - "2024-09-18 14:59:35,466 - peak_detection_2d.utils - INFO - Pred masked intensity sum 15174.83\n", - "2024-09-18 14:59:35,469 - matplotlib.legend - WARNING - No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from peak_detection_2d.infer_on_pept_act import infer_on_pept_act\n", - "\n", - "infer_on_pept_act(\n", - " cfg=cfg,\n", - " best_seg_model_path=cfg.PEAK_SELECTION.MODEL.RESUME_PATH,\n", - " best_cls_model_path=cfg.PEAK_SELECTION.CLSMODEL.RESUME_PATH,\n", - " maxquant_dict=maxquant_result_ref.loc[\n", - " maxquant_result_ref[\"mz_rank\"].isin(\n", - " test_pred_df_targets_high_wiou_low_td_score[\"mz_rank\"]\n", - " )\n", - " ],\n", - " ps_exp_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir),\n", - " plot_samples=True,\n", - " add_label_mask=True,\n", - " dataset_name=\"test_high_wiou_low_td_target\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Test set TDC" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "peak_selection_tdc = pd.read_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH,\n", - " \"peak_selection\",\n", - " ps_dir,\n", - " \"pept_act_sum_ps_full_tdc_fdr_thres.csv\",\n", - " )\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [], - "source": [ - "test_pred_df_tdc = test_pred_df.loc[\n", - " test_pred_df[\"mz_rank\"].isin(peak_selection_tdc[\"mz_rank\"])\n", - "]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Test set decoys" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_837179/4065297847.py:2: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " test_pred_df_decoys[\"Pass Intensity Filter\"] = (\n", - "/tmp/ipykernel_837179/4065297847.py:5: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " test_pred_df_decoys[\"Pass Conf. Score Filter\"] = (\n", - "/tmp/ipykernel_837179/4065297847.py:8: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " test_pred_df_decoys[\"Pass Both Filter\"] = (\n" - ] - } - ], - "source": [ - "test_pred_df_decoys = test_pred_df.loc[test_pred_df[\"Decoy\"] == 1]\n", - "test_pred_df_decoys[\"Pass Intensity Filter\"] = (\n", - " test_pred_df_decoys[\"log_sum_intensity\"] >= 2\n", - ")\n", - "test_pred_df_decoys[\"Pass Conf. Score Filter\"] = (\n", - " test_pred_df_decoys[\"target_decoy_score\"] >= 0.2\n", - ")\n", - "test_pred_df_decoys[\"Pass Both Filter\"] = (\n", - " test_pred_df_decoys[\"Pass Intensity Filter\"]\n", - " & test_pred_df_decoys[\"Pass Conf. Score Filter\"]\n", - ")\n", - "# test_pred_df_decoys[\"Is Isolated Decoys\"] = test_pred_df_decoys[\"mz_rank\"].isin(\n", - "# isolated_decoys\n", - "# )" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Pass Conf. Score Filter\n", - "True 937\n", - "False 441\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 67, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "test_pred_df_decoys.loc[\n", - " test_pred_df_decoys[\"Pass Intensity Filter\"], \"Pass Conf. Score Filter\"\n", - "].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1553" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.6078557630392788" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "944 + 609\n", - "944 / (944 + 609)" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "metadata": {}, - "outputs": [], - "source": [ - "identified_target = test_pred_df.loc[\n", - " (~test_pred_df[\"Decoy\"]) & (test_pred_df[\"log_sum_intensity\"] >= 2),\n", - " \"per_image_weighted_iou_metric\",\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.1478927203065134" - ] - }, - "execution_count": 69, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(identified_target <= 0.2).sum() / identified_target.shape[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "metadata": {}, - "outputs": [], - "source": [ - "ps_exp_dir = \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/\"" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'SWAPS Inferred Intensity (Log10)')" - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Test Set Inferred Intensity of Decoys')" - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 15:49:43,775 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/hist_inferred_intensity_test_decoys.png\n", - "2024-10-29 15:49:44,022 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/hist_inferred_intensity_test_decoys.svg\n" - ] - } - ], - "source": [ - "import seaborn as sns\n", - "from utils.plot import save_plot\n", - "\n", - "line_width = 2\n", - "plt.rc(\"font\", size=20) # Set the default font size for all text elements\n", - "plt.figure(figsize=(8, 6))\n", - "ax = sns.histplot(\n", - " data=test_pred_df_decoys,\n", - " x=\"log_sum_intensity\",\n", - " hue=\"Pass Conf. Score Filter\",\n", - " palette={False: \"#d8a6a6\", True: \"#a00000\"},\n", - " hue_order=[False, True],\n", - " # color=[\"olivedrab\", \"tomato\"],\n", - " multiple=\"stack\",\n", - " bins=20,\n", - ")\n", - "# Set the width of all spines (top, right, bottom, left)\n", - "for spine in ax.spines.values():\n", - " spine.set_linewidth(line_width) # Increase this value for thicker lines\n", - "# Optional: you can also make tick marks thicker\n", - "ax.tick_params(width=line_width)\n", - "plt.vlines(x=2, ymin=0, ymax=3000, color=\"black\", linestyle=\"--\", linewidth=line_width)\n", - "plt.xlabel(\"SWAPS Inferred Intensity (Log10)\")\n", - "plt.title(\"Test Set Inferred Intensity of Decoys\")\n", - "save_plot(\n", - " save_dir=ps_exp_dir,\n", - " fig_type_name=\"hist\",\n", - " fig_spec_name=\"inferred_intensity_test_decoys\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Test set targets" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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sum_intensitymz_rankout_scoretarget_decoy_scoreper_image_weighted_dice_metricper_image_weighted_iou_metricDecoylog_sum_intensitySequenceLength...MS1_frame_idx_right_refIsoMZIsoAbundancemz_binmz_lengthpept_batch_idxDataPass Intensity FilterPass TD Score FilterPass Both Filter
0122875.648438103291.00.9479290.9681390.9959430.991919False5.089469EDSWTLFKPPPVFPVDNSSAK21...1865[787.7307792879601, 788.0631242530267, 788.065...[0.25065097614238496, 0.022905100132044685, 0....787.73118TargetTrueTrueTrue
224924.57031278204.00.9631930.8229610.7749890.632638False4.396645VTTVVATLGQGPER14...1202[714.39682129248, 714.89533874008, 714.8984987...[0.4534083375456066, 0.029832166397493615, 0.3...714.4086TargetTrueTrueTrue
736028.617188166149.00.7114210.5077200.8771720.781217False4.556660VRTDITYPAGFMDVISIDK19...1863[1071.051545939275, 1071.550063386875, 1071.55...[0.2814932367879886, 0.0236656581370854, 0.294...1071.051213TargetTrueTrueTrue
99006.30859497923.00.9602440.9487820.8930430.806755False3.954595LAMTPTERPHGSDICTSWPR20...1111[771.3690819222634, 771.70142688733, 771.70353...[0.2543615471003181, 0.027893017433604107, 0.2...771.37137TargetTrueTrueTrue
116978.698730154193.00.9779430.8596590.9918920.983914False3.843837VLHALQEAAPEVVQPTTVQSSTIPSLLR28...1763[995.5525701534499, 995.8849151185167, 995.887...[0.184255395488496, 0.024246301457991695, 0.26...995.551212TargetTrueTrueTrue
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5 rows × 122 columns

\n", - "
" - ], - "text/plain": [ - " sum_intensity mz_rank out_score target_decoy_score \\\n", - "0 122875.648438 103291.0 0.947929 0.968139 \n", - "2 24924.570312 78204.0 0.963193 0.822961 \n", - "7 36028.617188 166149.0 0.711421 0.507720 \n", - "9 9006.308594 97923.0 0.960244 0.948782 \n", - "11 6978.698730 154193.0 0.977943 0.859659 \n", - "\n", - " per_image_weighted_dice_metric per_image_weighted_iou_metric Decoy \\\n", - "0 0.995943 0.991919 False \n", - "2 0.774989 0.632638 False \n", - "7 0.877172 0.781217 False \n", - "9 0.893043 0.806755 False \n", - "11 0.991892 0.983914 False \n", - "\n", - " log_sum_intensity Sequence Length ... \\\n", - "0 5.089469 EDSWTLFKPPPVFPVDNSSAK 21 ... \n", - "2 4.396645 VTTVVATLGQGPER 14 ... \n", - "7 4.556660 VRTDITYPAGFMDVISIDK 19 ... \n", - "9 3.954595 LAMTPTERPHGSDICTSWPR 20 ... \n", - "11 3.843837 VLHALQEAAPEVVQPTTVQSSTIPSLLR 28 ... \n", - "\n", - " MS1_frame_idx_right_ref IsoMZ \\\n", - "0 1865 [787.7307792879601, 788.0631242530267, 788.065... \n", - "2 1202 [714.39682129248, 714.89533874008, 714.8984987... \n", - "7 1863 [1071.051545939275, 1071.550063386875, 1071.55... \n", - "9 1111 [771.3690819222634, 771.70142688733, 771.70353... \n", - "11 1763 [995.5525701534499, 995.8849151185167, 995.887... \n", - "\n", - " IsoAbundance mz_bin mz_length \\\n", - "0 [0.25065097614238496, 0.022905100132044685, 0.... 787.73 11 \n", - "2 [0.4534083375456066, 0.029832166397493615, 0.3... 714.40 8 \n", - "7 [0.2814932367879886, 0.0236656581370854, 0.294... 1071.05 12 \n", - "9 [0.2543615471003181, 0.027893017433604107, 0.2... 771.37 13 \n", - "11 [0.184255395488496, 0.024246301457991695, 0.26... 995.55 12 \n", - "\n", - " pept_batch_idx Data Pass Intensity Filter Pass TD Score Filter \\\n", - "0 8 Target True True \n", - "2 6 Target True True \n", - "7 13 Target True True \n", - "9 7 Target True True \n", - "11 12 Target True True \n", - "\n", - " Pass Both Filter \n", - "0 True \n", - "2 True \n", - "7 True \n", - "9 True \n", - "11 True \n", - "\n", - "[5 rows x 122 columns]" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "test_pred_df_targets[test_pred_df_targets[\"Pass Intensity Filter\"]].head(5)" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "execution_count": 74, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'Weighted IoU')" - ] - }, - "execution_count": 74, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.001, 'Test Set Weighted IoU of Targets')" - ] - }, - "execution_count": 74, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, '(Pass Intensity Filter)')" - ] - }, - "execution_count": 74, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 15:51:30,607 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/hist_weighted_iou_test_passed_int_filter_targets.png\n", - "2024-10-29 15:51:30,852 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/hist_weighted_iou_test_passed_int_filter_targets.svg\n" - ] - } - ], - "source": [ - "import seaborn as sns\n", - "\n", - "line_width = 2\n", - "plt.rc(\"font\", size=20) # Set the default font size for all text elements\n", - "plt.figure(figsize=(8, 6))\n", - "ax = sns.histplot(\n", - " data=test_pred_df_targets[test_pred_df_targets[\"Pass Intensity Filter\"]],\n", - " x=\"per_image_weighted_iou_metric\",\n", - " hue=\"Pass Conf. Score Filter\",\n", - " palette={False: \"#d8a6a6\", True: \"#a00000\"},\n", - " hue_order=[False, True],\n", - " # color=[\"olivedrab\", \"tomato\"],\n", - " multiple=\"stack\",\n", - " bins=20,\n", - ")\n", - "# Set the width of all spines (top, right, bottom, left)\n", - "for spine in ax.spines.values():\n", - " spine.set_linewidth(line_width) # Increase this value for thicker lines\n", - "# Optional: you can also make tick marks thicker\n", - "ax.tick_params(width=line_width)\n", - "plt.xlabel(\"Weighted IoU\")\n", - "plt.suptitle(\"Test Set Weighted IoU of Targets\", y=1.001)\n", - "plt.title(\"(Pass Intensity Filter)\")\n", - "save_plot(\n", - " save_dir=ps_exp_dir,\n", - " fig_type_name=\"hist\",\n", - " fig_spec_name=\"weighted_iou_test_passed_int_filter_targets\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.8085522638345445" - ] - }, - "execution_count": 46, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.10536612632755729" - ] - }, - "execution_count": 46, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "test_pred_df_targets_filter_both = test_pred_df_targets[\n", - " test_pred_df_targets[\"Pass Both Filter\"]\n", - "]\n", - "(test_pred_df_targets_filter_both[\"per_image_weighted_iou_metric\"] > 0.8).sum() / len(\n", - " test_pred_df_targets_filter_both\n", - ")\n", - "(test_pred_df_targets_filter_both[\"per_image_weighted_iou_metric\"] < 0.2).sum() / len(\n", - " test_pred_df_targets_filter_both\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Figure 3: target decoy score distribution" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "execution_count": 63, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'Confidence Score')" - ] - }, - "execution_count": 63, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.001, '30-minute Exp Library Conf. Score')" - ] - }, - "execution_count": 63, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, '(Test Set)')" - ] - }, - "execution_count": 63, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 15:19:30,073 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/hist_confidence_score_30min_exp_testset.png\n", - "2024-10-29 15:19:30,327 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/hist_confidence_score_30min_exp_testset.svg\n" - ] - } - ], - "source": [ - "import seaborn as sns\n", - "\n", - "line_width = 2\n", - "plt.rc(\"font\", size=20) # Set the default font size for all text elements\n", - "plt.figure(figsize=(8, 6))\n", - "ax = sns.histplot(\n", - " test_pred_df_full,\n", - " x=\"target_decoy_score\",\n", - " hue=\"Data\",\n", - " fill=True,\n", - " hue_order=[\"Decoy\", \"Target\"],\n", - " # palette=custom_cmap,\n", - " multiple=\"dodge\",\n", - " common_norm=True,\n", - " bins=20,\n", - ")\n", - "# Set the width of all spines (top, right, bottom, left)\n", - "for spine in ax.spines.values():\n", - " spine.set_linewidth(line_width) # Increase this value for thicker lines\n", - "# Optional: you can also make tick marks thicker\n", - "ax.tick_params(width=line_width)\n", - "plt.xlabel(\"Confidence Score\")\n", - "plt.suptitle(\"30-minute Exp Library Conf. Score\", y=1.001)\n", - "plt.title(\"(Test Set)\") # Add padding to increase spacing\n", - "save_plot(\n", - " save_dir=ps_exp_dir,\n", - " fig_type_name=\"hist\",\n", - " fig_spec_name=\"confidence_score_30min_exp_testset\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "execution_count": 53, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'Confidence Score')" - ] - }, - "execution_count": 53, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, '120-minute Ref Library Conf. Score')" - ] - }, - "execution_count": 53, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-29 15:07:09,059 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/hist_confidence_score_120min_ref.png\n", - "2024-10-29 15:07:09,305 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/hist_confidence_score_120min_ref.svg\n" - ] - } - ], - "source": [ - "import seaborn as sns\n", - "\n", - "pept_act_sum_ps_df_with_source = pd.merge(\n", - " left=pept_act_sum_ps_df,\n", - " right=maxquant_result_ref[[\"mz_rank\", \"source\"]],\n", - " on=\"mz_rank\",\n", - ")\n", - "line_width = 2\n", - "plt.rc(\"font\", size=20) # Set the default font size for all text elements\n", - "plt.figure(figsize=(8, 6))\n", - "\n", - "ax = sns.histplot(\n", - " data=pept_act_sum_ps_df_with_source.loc[\n", - " pept_act_sum_ps_df_with_source[\"source\"] == \"ref\"\n", - " ],\n", - " x=\"target_decoy_score\",\n", - " hue=\"Data\",\n", - " fill=True,\n", - " hue_order=[\"Decoy\", \"Target\"],\n", - " # palette=custom_cmap,\n", - " multiple=\"dodge\",\n", - " common_norm=True,\n", - " bins=20,\n", - ")\n", - "# Set the width of all spines (top, right, bottom, left)\n", - "for spine in ax.spines.values():\n", - " spine.set_linewidth(line_width) # Increase this value for thicker lines\n", - "# Optional: you can also make tick marks thicker\n", - "ax.tick_params(width=line_width)\n", - "plt.xlabel(\"Confidence Score\")\n", - "plt.title(\"120-minute Ref Library Conf. Score\")\n", - "save_plot(\n", - " save_dir=ps_exp_dir,\n", - " fig_type_name=\"hist\",\n", - " fig_spec_name=\"confidence_score_120min_ref\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Figure S10, intermediate results" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "save_dir = (\n", - " \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Before PS and FDR control" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_df = pd.read_csv(\n", - " os.path.join(cfg.RESULT_PATH, \"results\", \"activation\", \"pept_act_sum.csv\")\n", - ")\n", - "pept_act_sum_df_full = pd.merge(\n", - " left=pept_act_sum_df, right=maxquant_result_ref[[\"mz_rank\", \"Decoy\"]], on=\"mz_rank\"\n", - ")\n", - "pept_act_sum_df_full[\"Data\"] = \"Target\"\n", - "pept_act_sum_df_full.loc[pept_act_sum_df_full[\"Decoy\"], \"Data\"] = \"Decoy\"\n", - "pept_act_sum_df_full[\"log_sum_intensity\"] = np.log10(\n", - " pept_act_sum_df_full[\"pept_act_sum\"] + 1\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "2024-10-30 14:10:19,516 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/PS_model_test_log_sum_intensity_distribution_after_SWA.png\n", - "2024-10-30 14:10:19,816 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/PS_model_test_log_sum_intensity_distribution_after_SWA.svg\n" - ] - } - ], - "source": [ - "from peak_detection_2d.utils import plot_per_image_metric_distr\n", - "\n", - "plot_per_image_metric_distr(\n", - " pept_act_sum_df_full,\n", - " metric_name=\"log_sum_intensity\",\n", - " hue=\"Data\",\n", - " fill=True,\n", - " hue_order=[\"Decoy\", \"Target\"],\n", - " common_norm=True,\n", - " multiple=\"dodge\",\n", - " show_quantiles=None,\n", - " title=\"After SWA, before PS\",\n", - " xlabel=\"SWAPS Inferred Intensity (Log10)\",\n", - " save_dir=save_dir,\n", - " dataset_name=\"after_SWA\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-30 14:11:38,122 - result_analysis.result_analysis - INFO - Drop na values in pept_act_sum, Pept activation sum entries: 186257\n", - "2024-10-30 14:11:38,123 - result_analysis.result_analysis - INFO - Filtering the data by the sum of intensity threshold 2, number of entries before filtering 186257\n", - "2024-10-30 14:11:38,131 - result_analysis.result_analysis - INFO - Number of entries after filtering 186257\n", - "2024-10-30 14:11:38,134 - result_analysis.result_analysis - INFO - Removing decoy entries, number of entries before filtering 186257\n", - "2024-10-30 14:11:38,140 - result_analysis.result_analysis - INFO - Number of entries after filtering 93323\n", - "2024-10-30 14:11:38,391 - result_analysis.result_analysis - INFO - Number of entries after merging 51319 and columns Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'IsoMZ', 'IsoAbundance', 'mz_rank', 'mz_bin', 'mz_length',\n", - " 'pept_batch_idx', 'pept_act_sum', 'Decoy_y', 'Data',\n", - " 'log_sum_intensity'],\n", - " dtype='object', length=116)\n", - "2024-10-30 14:11:38,526 - utils.plot - INFO - Data: Intensity_log, pept_act_sum_log, slope = 0.459, intercept = 2.966, Pearson's R = 0.535, Spearman's R = 0.484\n", - "2024-10-30 14:12:24,314 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/CorrQuantification_pept_act_sum_log_fdr_None_log_int_2.png\n", - "2024-10-30 14:12:28,263 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/CorrQuantification_pept_act_sum_log_fdr_None_log_int_2.svg\n" - ] - } - ], - "source": [ - "from result_analysis import result_analysis\n", - "\n", - "swaps_result = result_analysis.SWAPSResult(\n", - " maxquant_dict=maxquant_result_ref,\n", - " pept_act_sum_df=pept_act_sum_df_full,\n", - " infer_intensity_col=\"pept_act_sum\",\n", - " fdr_thres=None,\n", - " log_sum_intensity_thres=2,\n", - " save_dir=save_dir,\n", - ")\n", - "swaps_result.plot_intensity_corr(\n", - " contour=False, show_diag=False, title=\"After SWA, before PS\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## After PS, before FDR" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_df = pd.read_csv(\n", - " os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"pept_act_sum_ps.csv\")\n", - ")\n", - "pept_act_sum_ps_df[\"log_sum_intensity\"] = np.log10(\n", - " pept_act_sum_ps_df[\"sum_intensity\"] + 1\n", - ")\n", - "pept_act_sum_ps_df = pd.merge(\n", - " left=maxquant_result_ref[[\"mz_rank\", \"Decoy\"]],\n", - " right=pept_act_sum_ps_df,\n", - " on=\"mz_rank\",\n", - ")\n", - "pept_act_sum_ps_df[\"Data\"] = \"Target\"\n", - "pept_act_sum_ps_df.loc[pept_act_sum_ps_df[\"Decoy\"], \"Data\"] = \"Decoy\"" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "2024-10-30 14:15:51,586 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/PS_model_test_log_sum_intensity_distribution_after_PS.png\n", - "2024-10-30 14:15:51,843 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/PS_model_test_log_sum_intensity_distribution_after_PS.svg\n" - ] - } - ], - "source": [ - "plot_per_image_metric_distr(\n", - " pept_act_sum_ps_df,\n", - " metric_name=\"log_sum_intensity\",\n", - " hue=\"Data\",\n", - " fill=True,\n", - " hue_order=[\"Decoy\", \"Target\"],\n", - " common_norm=True,\n", - " multiple=\"dodge\",\n", - " show_quantiles=None,\n", - " title=\"After PS, before FDR\",\n", - " xlabel=\"SWAPS Inferred Intensity (Log10)\",\n", - " save_dir=save_dir,\n", - " dataset_name=\"after_PS\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-30 14:16:38,550 - result_analysis.result_analysis - INFO - Drop na values in sum_intensity, Pept activation sum entries: 186257\n", - "2024-10-30 14:16:38,551 - result_analysis.result_analysis - INFO - Filtering the data by the sum of intensity threshold 2, number of entries before filtering 186257\n", - "2024-10-30 14:16:38,558 - result_analysis.result_analysis - INFO - Number of entries after filtering 99726\n", - "2024-10-30 14:16:38,561 - result_analysis.result_analysis - INFO - Removing decoy entries, number of entries before filtering 99726\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-30 14:16:38,565 - result_analysis.result_analysis - INFO - Number of entries after filtering 74620\n", - "2024-10-30 14:16:38,792 - result_analysis.result_analysis - INFO - Number of entries after merging 46812 and columns Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'mz_rank', 'mz_bin', 'mz_length', 'pept_batch_idx', 'Decoy_y',\n", - " 'sum_intensity', 'out_score', 'target_decoy_score', 'log_sum_intensity',\n", - " 'Data'],\n", - " dtype='object', length=118)\n", - "2024-10-30 14:16:38,903 - utils.plot - INFO - Data: Intensity_log, sum_intensity_log, slope = 0.992, intercept = -0.434, Pearson's R = 0.814, Spearman's R = 0.837\n", - "2024-10-30 14:17:18,111 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/CorrQuantification_sum_intensity_log_fdr_None_log_int_2.png\n", - "2024-10-30 14:17:21,722 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/CorrQuantification_sum_intensity_log_fdr_None_log_int_2.svg\n" - ] - } - ], - "source": [ - "from result_analysis import result_analysis\n", - "\n", - "swaps_result = result_analysis.SWAPSResult(\n", - " maxquant_dict=maxquant_result_ref,\n", - " pept_act_sum_df=pept_act_sum_ps_df,\n", - " infer_intensity_col=\"sum_intensity\",\n", - " fdr_thres=None,\n", - " log_sum_intensity_thres=2,\n", - " save_dir=save_dir,\n", - ")\n", - "swaps_result.plot_intensity_corr(\n", - " contour=False, title=\"After PS, before FDR\", show_diag=False\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## After PS and FDR control" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_843352/1166506118.py:7: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", - "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", - "\n", - "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", - "\n", - "\n", - " to_plot[\"log_sum_intensity\"].fillna(0, inplace=True)\n" - ] - } - ], - "source": [ - "to_plot = pd.merge(\n", - " left=pept_act_sum_ps_df[[\"mz_rank\", \"Data\"]],\n", - " right=pept_act_sum_ps_full_tdc,\n", - " on=[\"mz_rank\"],\n", - " how=\"left\",\n", - ")\n", - "to_plot[\"log_sum_intensity\"].fillna(0, inplace=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "2024-10-30 14:18:02,596 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/PS_model_test_log_sum_intensity_distribution_after_FDR.png\n", - "2024-10-30 14:18:02,831 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/PS_model_test_log_sum_intensity_distribution_after_FDR.svg\n" - ] - } - ], - "source": [ - "plot_per_image_metric_distr(\n", - " to_plot,\n", - " metric_name=\"log_sum_intensity\",\n", - " hue=\"Data\",\n", - " fill=True,\n", - " hue_order=[\"Decoy\", \"Target\"],\n", - " common_norm=True,\n", - " multiple=\"dodge\",\n", - " show_quantiles=None,\n", - " title=\"After PS, after FDR\",\n", - " xlabel=\"SWAPS Inferred Intensity (Log10)\",\n", - " save_dir=save_dir,\n", - " dataset_name=\"after_FDR\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-30 14:18:37,351 - result_analysis.result_analysis - INFO - Drop na values in sum_intensity, Pept activation sum entries: 79795\n", - "2024-10-30 14:18:37,352 - result_analysis.result_analysis - INFO - Filtering the data by the sum of intensity threshold 2, number of entries before filtering 79795\n", - "2024-10-30 14:18:37,358 - result_analysis.result_analysis - INFO - Number of entries after filtering 79795\n", - "2024-10-30 14:18:37,360 - result_analysis.result_analysis - INFO - FDR threshold is larger than the maximum FDR, set to maximum FDR 0.161\n", - "2024-10-30 14:18:37,362 - result_analysis.result_analysis - INFO - Calculating FDR results after filter...\n", - "2024-10-30 14:18:37,365 - peak_detection_2d.utils - INFO - Number of entries before filtering: 79795\n", - "2024-10-30 14:18:37,371 - peak_detection_2d.utils - INFO - Number of entries after filtering by log_sum_intensity with condition [0, 100]: 79795\n", - "2024-10-30 14:18:43,734 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/fdr_id_targets_result_analysis.png\n", - "2024-10-30 14:18:51,233 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/fdr_id_targets_result_analysis.svg\n", - "2024-10-30 14:18:51,234 - result_analysis.result_analysis - INFO - Filtering the data by FDR threshold 0.161, number of entries before filtering 79795\n", - "2024-10-30 14:18:51,242 - result_analysis.result_analysis - INFO - Score threshold 0.0282391110315487, number of entries after filtering 79790\n", - "2024-10-30 14:18:51,242 - result_analysis.result_analysis - INFO - Removing decoy entries, number of entries before filtering 79790\n", - "2024-10-30 14:18:51,247 - result_analysis.result_analysis - INFO - Number of entries after filtering 68726\n", - "2024-10-30 14:18:51,523 - result_analysis.result_analysis - INFO - Number of entries after merging 44966 and columns Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'sum_intensity', 'out_score', 'target_decoy_score', 'Decoy_y',\n", - " 'TD pair id_y', 'log_sum_intensity', 'competition', 'Target', 'fdr',\n", - " 'N_identified_target'],\n", - " dtype='object', length=123)\n", - "2024-10-30 14:18:51,645 - utils.plot - INFO - Data: Intensity_log, sum_intensity_log, slope = 0.994, intercept = -0.436, Pearson's R = 0.827, Spearman's R = 0.845\n", - "2024-10-30 14:19:28,214 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/CorrQuantification_sum_intensity_log_fdr_0.161_log_int_2.png\n", - "2024-10-30 14:19:31,503 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/intermedia_result/CorrQuantification_sum_intensity_log_fdr_0.161_log_int_2.svg\n" - ] - } - ], - "source": [ - "from result_analysis import result_analysis\n", - "\n", - "swaps_result = result_analysis.SWAPSResult(\n", - " maxquant_dict=maxquant_result_ref,\n", - " pept_act_sum_df=pept_act_sum_ps_full_tdc,\n", - " infer_intensity_col=\"sum_intensity\",\n", - " fdr_thres=0.2,\n", - " log_sum_intensity_thres=2,\n", - " save_dir=save_dir,\n", - " # save_dir=eval_dir,\n", - ")\n", - "swaps_result.plot_intensity_corr(\n", - " contour=False, show_diag=False, title=\"After PS, after FDR\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 30min" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Distribution of the gained precursors" - ] - }, - { - "cell_type": "code", - "execution_count": 155, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_tdc_all_no_loser_int_filter_with_source_filter_score_with_proteins_no_decoys = pd.merge(\n", - " left=pept_act_sum_ps_tdc_all_no_loser_int_filter_with_source[\n", - " (\n", - " pept_act_sum_ps_tdc_all_no_loser_int_filter_with_source[\n", - " \"target_decoy_score\"\n", - " ]\n", - " > 0.196861\n", - " )\n", - " & (~pept_act_sum_ps_tdc_all_no_loser_int_filter_with_source[\"Decoy\"])\n", - " ],\n", - " right=maxquant_result_ref[[\"mz_rank\", \"Proteins\"]],\n", - " on=\"mz_rank\",\n", - " how=\"inner\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 168, - "metadata": {}, - "outputs": [], - "source": [ - "exp_proteins_list = maxquant_result_ref.loc[\n", - " (maxquant_result_ref[\"source\"].isin([\"exp\", \"both\"]))\n", - " & (~maxquant_result_ref[\"Decoy\"]),\n", - " \"Proteins\",\n", - "].str.split(\";\")\n", - "ref_proteins_list = pept_act_sum_ps_tdc_all_no_loser_int_filter_with_source_filter_score_with_proteins_no_decoys.loc[\n", - " pept_act_sum_ps_tdc_all_no_loser_int_filter_with_source_filter_score_with_proteins_no_decoys[\n", - " \"source\"\n", - " ].isin(\n", - " [\"ref\"]\n", - " ),\n", - " \"Proteins\",\n", - "].str.split(\n", - " \";\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 157, - "metadata": {}, - "outputs": [], - "source": [ - "from collections import Counter\n", - "\n", - "\n", - "def get_protein_count_from_list(proteins_list):\n", - " protein_list = [item for sublist in proteins_list for item in sublist]\n", - " element_counts = Counter(protein_list)\n", - " df_counts = pd.DataFrame(list(element_counts.items()), columns=[\"Protein\", \"Count\"])\n", - " logging.info(\"Mean of protein count: %s\", df_counts[\"Count\"].mean())\n", - " return df_counts" - ] - }, - { - "cell_type": "code", - "execution_count": 158, - "metadata": {}, - "outputs": [], - "source": [ - "maxquant_result_exp = pd.read_csv(\n", - " \"/cmnfs/proj/ORIGINS/data/tims_ramp_time/combined_30min_gradient/txt/evidence.txt\",\n", - " sep=\"\\t\",\n", - " low_memory=False,\n", - ")\n", - "mq_exp_100ms = maxquant_result_exp[\n", - " maxquant_result_exp[\"Raw file\"]\n", - " == \"Hela2ug_lowflow_30min_1to37to42_NCE29to59_100ms7R_RA2_1_2078\"\n", - "]\n", - "mq_exp_100ms = mq_exp_100ms.drop_duplicates(\n", - " subset=[\"Modified sequence\", \"Charge\"], keep=\"first\"\n", - ")\n", - "mq_proteins_list = mq_exp_100ms[\"Proteins\"].str.split(\";\")\n", - "mq_proteins_list.dropna(inplace=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 159, - "metadata": {}, - "outputs": [], - "source": [ - "swap_proteins_list = pept_act_sum_ps_tdc_all_no_loser_int_filter_with_source_filter_score_with_proteins_no_decoys[\n", - " \"Proteins\"\n", - "].str.split(\n", - " \";\"\n", - ")\n", - "swap_proteins_list.dropna(inplace=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 169, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-19 09:42:40,334 - root - INFO - Mean of protein count: 7.040646077387292\n", - "2024-09-19 09:42:40,345 - root - INFO - Mean of protein count: 3.897360703812317\n", - "2024-09-19 09:42:40,363 - root - INFO - Mean of protein count: 7.4867403314917125\n", - "2024-09-19 09:42:40,385 - root - INFO - Mean of protein count: 8.042613636363637\n" - ] - } - ], - "source": [ - "exp_protein_count = get_protein_count_from_list(exp_proteins_list)\n", - "ref_protein_count = get_protein_count_from_list(ref_proteins_list)\n", - "mq_proteins_count = get_protein_count_from_list(mq_proteins_list)\n", - "swap_proteins_count = get_protein_count_from_list(swap_proteins_list)" - ] - }, - { - "cell_type": "code", - "execution_count": 179, - "metadata": {}, - "outputs": [], - "source": [ - "swaps_only_protein = set(swap_proteins_count[\"Protein\"]) - set(\n", - " mq_proteins_count[\"Protein\"]\n", - ")\n", - "both = set(mq_proteins_count[\"Protein\"]).intersection(\n", - " set(swap_proteins_count[\"Protein\"])\n", - ")\n", - "mq_only_protein = set(mq_proteins_count[\"Protein\"]) - set(\n", - " swap_proteins_count[\"Protein\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 182, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 182, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Protein count comparison')" - ] - }, - "execution_count": 182, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from matplotlib_venn import venn2\n", - "\n", - "venn2(\n", - " subsets=(len(mq_only_protein), len(swaps_only_protein), len(both)),\n", - " set_labels=(\"MaxQuant\", \"SWAPS\"),\n", - ")\n", - "plt.title(\"Protein count comparison\")" - ] - }, - { - "cell_type": "code", - "execution_count": 186, - "metadata": {}, - "outputs": [], - "source": [ - "swap_proteins_count[\"source\"] = \"MQ and SWAPS\"\n", - "swap_proteins_count.loc[\n", - " swap_proteins_count[\"Protein\"].isin(swaps_only_protein), \"source\"\n", - "] = \"SWAPS only\"" - ] - }, - { - "cell_type": "code", - "execution_count": 193, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 193, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import seaborn as sns\n", - "\n", - "sns.histplot(data=swap_proteins_count, x=\"Count\", hue=\"source\", common_norm=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 197, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 197, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "1.8608815426997245" - ] - }, - "execution_count": 197, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Count\n", - "1 850\n", - "2 327\n", - "3 137\n", - "4 65\n", - "5 33\n", - "6 15\n", - "8 8\n", - "7 5\n", - "10 3\n", - "14 2\n", - "9 2\n", - "16 1\n", - "26 1\n", - "25 1\n", - "19 1\n", - "11 1\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 197, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "swap_proteins_count.loc[\n", - " swap_proteins_count[\"Protein\"].isin(swaps_only_protein), \"Count\"\n", - "].hist()\n", - "swap_proteins_count.loc[\n", - " (swap_proteins_count[\"Protein\"].isin(swaps_only_protein))\n", - " & (swap_proteins_count[\"Count\"] > 0),\n", - " \"Count\",\n", - "].mean()\n", - "swap_proteins_count.loc[\n", - " (swap_proteins_count[\"Protein\"].isin(swaps_only_protein))\n", - " & (swap_proteins_count[\"Count\"] > 0),\n", - " \"Count\",\n", - "].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 196, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 196, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "9.756875477463712" - ] - }, - "execution_count": 196, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Count\n", - "2 514\n", - "3 490\n", - "1 459\n", - "4 447\n", - "5 358\n", - " ... \n", - "73 1\n", - "101 1\n", - "145 1\n", - "65 1\n", - "66 1\n", - "Name: count, Length: 81, dtype: int64" - ] - }, - "execution_count": 196, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "swap_proteins_count.loc[\n", - " ~swap_proteins_count[\"Protein\"].isin(swaps_only_protein), \"Count\"\n", - "].hist()\n", - "swap_proteins_count.loc[\n", - " (~swap_proteins_count[\"Protein\"].isin(swaps_only_protein))\n", - " & (swap_proteins_count[\"Count\"] > 0),\n", - " \"Count\",\n", - "].mean()\n", - "swap_proteins_count.loc[\n", - " (~swap_proteins_count[\"Protein\"].isin(swaps_only_protein))\n", - " & (swap_proteins_count[\"Count\"] > 0),\n", - " \"Count\",\n", - "].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "exp_protein_count[\"Count\"].sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Full set result analysis" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps = pd.read_csv(\n", - " os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"pept_act_sum_ps.csv\")\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_full = pd.merge(\n", - " left=pept_act_sum_ps,\n", - " right=maxquant_result_ref[[\"mz_rank\", \"pept_batch_idx\"]],\n", - " on=[\"mz_rank\"],\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n", - "2024-09-11 14:52:38,431 - peak_detection_2d.utils - INFO - FDR after TDC: (Decoy\n", - "False 72748\n", - "True 16649\n", - "Name: count, dtype: int64, 0.22885852532028372)\n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from peak_detection_2d.utils import compete_target_decoy_pair\n", - "\n", - "pept_act_sum_ps_full, pept_act_sum_ps_full_tdc = compete_target_decoy_pair(\n", - " pept_act_sum_ps, maxquant_result_ref, \n", - " #filter_dict={\"log_sum_intensity\": [1, 100]}\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Full set before target decoy competetion" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(Decoy\n", - " False 89397\n", - " True 89397\n", - " Name: count, dtype: int64,\n", - " 1.0)" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from peak_detection_2d.utils import calc_fdr_given_thres\n", - "\n", - "calc_fdr_given_thres(pept_act_sum_ps_full)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/utils/plot.py:346: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n", - " plt.savefig(\n" - ] - } - ], - "source": [ - "from peak_detection_2d.utils import plot_target_decoy_distr\n", - "\n", - "plot_target_decoy_distr(\n", - " pept_act_sum_ps_full,\n", - " threshold=None,\n", - " save_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\"),\n", - " dataset_name=\"fullset\",\n", - " main_plot_type=\"scatter\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.6112928391543656" - ] - }, - "execution_count": 61, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from peak_detection_2d.utils import plot_roc_auc\n", - "\n", - "plot_roc_auc(\n", - " pept_act_sum_ps_full,\n", - " save_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\"),\n", - " dataset_name=\"fullset\",\n", - " # filter_dict={\"log_sum_intensity\": [2, 100]}\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_ref = pd.merge(\n", - " left=maxquant_result_ref.loc[maxquant_result_ref[\"source\"] == \"ref\", \"mz_rank\"],\n", - " right=pept_act_sum_ps_full_tdc,\n", - " how=\"inner\",\n", - ")\n", - "pept_act_sum_ps_both = pd.merge(\n", - " left=maxquant_result_ref.loc[maxquant_result_ref[\"source\"] == \"both\", \"mz_rank\"],\n", - " right=pept_act_sum_ps_full_tdc,\n", - " how=\"inner\",\n", - ")\n", - "# pept_act_sum_ps_exp = pd.merge(\n", - "# left=maxquant_result_ref.loc[maxquant_result_ref[\"source\"] == \"exp\", \"mz_rank\"],\n", - "# right=pept_act_sum_ps_full,\n", - "# how=\"inner\",\n", - "# )\n", - "pept_act_sum_ps_exp = pd.merge(\n", - " left=maxquant_result_ref.loc[maxquant_result_ref[\"source\"] != \"ref\", \"mz_rank\"],\n", - " right=pept_act_sum_ps_full_tdc,\n", - " how=\"inner\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-11 15:12:27,023 - peak_detection_2d.utils - INFO - Number of entries before filtering: 52929\n", - "2024-09-11 15:12:27,026 - peak_detection_2d.utils - INFO - Number of entries after filtering by log_sum_intensity with condition [2, 100]: 45701\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from peak_detection_2d.utils import calc_fdr_and_thres\n", - "\n", - "ref_fdr_thres = calc_fdr_and_thres(\n", - " pept_act_sum_ps_ref,\n", - " score_col=\"target_decoy_score\",\n", - " return_plot=True,\n", - " filter_dict={\"log_sum_intensity\": [2, 100]},\n", - " xlim=(0, 0.4),\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Decoy\n", - "False 34935\n", - "True 10766\n", - "Name: count, dtype: int64\n", - "2758\n" - ] - } - ], - "source": [ - "def report_decoy_type(df, isolated_decoys):\n", - " print(df[\"Decoy\"].value_counts())\n", - " print(df.loc[df[\"Decoy\"], \"mz_rank\"].isin(isolated_decoys).sum())\n", - "\n", - "\n", - "report_decoy_type(df=ref_fdr_thres, isolated_decoys=isolated_decoys)" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-11 15:13:00,221 - peak_detection_2d.utils - INFO - Number of entries before filtering: 36468\n", - "2024-09-11 15:13:00,224 - peak_detection_2d.utils - INFO - Number of entries after filtering by log_sum_intensity with condition [2, 100]: 35458\n" - ] - }, - { - "data": { - "image/png": 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7d7FhwwYsWrQI8+fPx8cff5zjY7WNxjo6OgLQ/T3X1i685jVr1uT4ddq4caPer6t06dJYvXo1Xrx4gcePH+O3335DvXr1sHbtWkyaNEnv8xQU4WvStGnTHL8m2n4m5KeyfG7/VoW4BOPHj4e1tbW40F34mNt7hxgfJVmkxDtz5gwuXboEW1tbDBgwQK/H9OrVCz4+Pvj777+xY8eOPD3f2LFjkZ6ejt27d+Ovv/7CmzdvMHLkyByvUnR2dkbPnj3x66+/ws/PD3FxcTh//nyenldQqlQp1KpVC1FRUXjy5InGcW3V1lu2bAmJRIILFy4Y9Jz6EqbdTDnCVa9ePfFqMGGaMzfNmjUDAK1XXl68eNHo8f73338AgIEDB2oc03X1Z07q1asHW1tb3LlzB8nJyRrHL168qNEmVMzPy/c8L9+/WrVqYcKECTh37hwcHBwKzQ4KOb0GBwcHNGzYEPfu3UNcXJzZYrp48aLWsiLCv9XspWHKly+PwYMH49q1a7h06RJ27tyJ6tWr67yKlJgOJVmkxGLKYqRDhgwBoJiCycuQ/nfffQdAUXk+MzNT78f5+vpCIpFgy5Yt2LJlCwBovXw6NDRU61/EsbGxAJCvAqjjxo0Dz/P48ssv1X54h4eH48cff9ToX6FCBYwaNQo3btzAd999p/UX0JMnT9RGfwxRtmxZAMDz58/zdZ6cWFhYYMqUKYiOjsbUqVORlpam0Sc6Olqt/pnw/Vm0aJHaL9f09HSxkK0xCeUCsie8T58+FafZ8sLKygrDhg1DYmKixjq027dvi+9DVZ6enujQoQMOHDiAP/74Q+t57969K74fgZy/f+Hh4Xj69KlGe3x8PGQyGWxtbdXahZpo5t6iJ7f34MyZM/H+/XuMHz9eo3o/oHg9who+Y3n8+LFGbbyQkBCcO3cOtWrVEks4qBJGBocNG4aUlBRMnDhRY11XdHQ0Hjx4YLJab4TWZJES4uzZs+Li3bS0NLx8+RKXLl1CeHg4rK2tsWzZMnzxxRd5Oqenpyf69euHkJAQ/P7773oPxVepUgXe3t44ffo0LCws0LhxY61FSgcMGAAHBwe0bt0a7u7uYIzhwoULuH79Opo3b46uXbvmKV5Vn3/+OYKDg7F//340a9YMPXr0QEJCAvbs2YOOHTvi4MGDGo9Zu3YtHj9+jG+//RZbt25F+/btUbFiRbx8+RL379/H9evXxb+YDeXt7Q2JRIKAgAD8888/KF26NADgm2++Mfic2sydOxe3b9/G+vXrcejQIXTu3Blubm6IjY3F48ePcenSJSxatEhcb9euXTtMmTIFP/30Exo1aoTBgweLdbJKly5t9MXDffr0Qa1atbBq1SrcvXsXTZs2xfPnz3H48GH06tXLoCR06dKlOHPmDJYvX45r166hbdu2iI6Oxp49e9CzZ08EBwdr/BLesWMHOnfujAkTJuDHH39Eq1at4OzsjMjISNy5cwf//PMPrly5Ii7obtOmDezs7PDDDz/g7du34h8tU6ZMwe3btzFw4EC0aNEC9evXh6urK16/fo2QkBBkZGRoJI9C8p+93pSp1a1bF25ubti1axcsLS1RrVo1cByHMWPGoFq1ahg/fjz+/vtvrFu3DjVr1kSPHj1QtWpVxMXFITw8HOfPn8e4ceOwfv16o8Xk4+ODzz//HEePHsUHH3wg1smysbHBH3/8oXVRfLt27fDBBx/g9u3bsLS0xPjx4zX6BAQEUJ0sUzPptYuEmACU5Rr0IVzWLtw4jmMODg6satWq7MMPP2RLly5lkZGRWh+bU50swa1btxjHcczNzU3velmMZdXZAsBWrFihtc8vv/zC+vfvz6pXr85sbW1Z6dKlmYeHB1u2bJnWy/C10VXCgTHGEhMT2YwZM5irqyuztrZmdevWZStWrGBPnjzRWieLMUUpgJ9++om1adOGOTo6MisrK1alShXWuXNntnr1avbmzRuN59Z1KXy1atV01iATajBl/14bq04WY4zxPM+2bNnCOnfuzEqXLs0sLS2Zq6sra9euHVu0aBF7/vy5Rv+ffvqJ1atXj1lZWTEXFxc2efJklpCQoPO16ENXCYfnz5+zkSNHMldXV2ZjY8MaNGjAli1bxjIyMnIsV5JTKYjIyEjm6+vLypUrx2xsbNgHH3zANm3axPbu3csAsNWrV2s8JikpiS1atIg1a9aM2dvbMxsbG+bu7s569uzJgoKCWEpKilr/o0ePstatWzN7e3vx+xceHs5evHjBAgICWNu2bVnFihWZlZUVc3NzYz4+PuzIkSMaz+vh4cFKlSqVpxImur7XeSnhwBhjYWFhrHPnzszR0ZFxHKf163ro0CHWq1cvVr58eWZpackqVqzIWrRowebMmcPu37+vV1y5UY378uXLrEuXLqxUqVLMwcGBdevWjYWFheX4+B9++CHHMhxUJ8v0OMaMeB08IYSQImfOnDlYvHgxjh07lqeyJKaSkJCAsmXL4vPPP8fy5csLOpwiS6jofurUKXTp0qWgwymRKMkihJAS4uXLlxqX8N+9exdt27aFlZUVoqKiYGNjU0DRZTl06BCGDBmCiIiIfJU+KMlevHiB2rVro0aNGrh3716+rm4khqM1WYQQUkJ4enqiVq1aaNSoEezt7fH48WP89ddf4HkeQUFBhSLBAhRr0rRtgk1yt2PHDjx69Ai7du2CTCbDd999RwlWAaKRLEIIKSEWLFiA4OBgREREIDk5Gc7OzmjdujVmzZqlthkyKbo6deqE8+fPo0qVKpgxYwamT59e0CGVaJRkEUIIIYSYANXJIoQQQggxAUqyCCGEEEJMgJIsQvIpIiICHMdRMT8zEyqCC5t3lxQcxxWq9VNnz54Fx3HirV69egUdUqGyb98+ta9PYfreEdOjJIsQUqJt2rSpQLZvMab58+eD4zit+06ai5eXF+bNm4fPPvtMrf3x48dYtmwZOnfujCpVqsDKygoVK1ZEv379jLqheFhYGAICAvDhhx+iUqVK4DgOlStXzvVxkZGRGD9+PFxdXWFtbQ13d3dMnz4d8fHxOh/z77//YujQoahQoQJsbGxQt25dzJs3T+sWTQ0aNMC8efMwb968fL0+UjRRCQdCSJG0ZMkSfPXVV3BzcyvoUMzq/v37+dq30lQ6deokbl2lau7cudi9ezcaNGiAnj17okyZMnj48CEOHjyIgwcPYs2aNZg6dWq+n3/Hjh1Ys2YNLC0t0aBBA7x69SrXxzx58gRt27ZFbGws+vXrh3r16iEsLAxr1qzBsWPHcOnSJXEvQ8G1a9fQuXNnZGRkYPDgwahSpQrOnDmDhQsX4vTp0zh9+jSsra3F/g0aNBC/LgsWLMj36yRFCyVZhJAiycXFxeh7BhYFRW06zsfHB19++aXG/pznzp1Dt27d8MUXX2DIkCH5/l76+flh7NixaNiwIaysrPSqDTV58mTExsbixx9/xJQpU8T2mTNnYvXq1ZgzZ47aHoRyuRzjxo1DamoqQkJC0LdvXwCKfRaHDh2K/fv3Y/Xq1fjqq6/y9VpIMVJwO/oQUjwIexxq2+vv5cuXbPLkyaxatWrM0tKSlStXjg0YMIDduHFD67kSEhLYtGnTmJubm7if4MqVK3PcT1AfSUlJbOHChaxhw4bi3mc1atRgQ4cOVYvFkP0GN27cKO5/duLECda+fXtmb2/PypUrx/z8/Fh8fDxjjLH//e9/rFevXszZ2ZnZ29uzPn36aOxBmBfa9jFU/V6Eh4ezYcOGsbJlyzJra2vWvHlzdujQIbVzCHvXabupnjcjI4P9/PPPrFWrVqxUqVLM1taWeXh4sJ9++onJ5XK1c+Y1BsYUe0KuWbOGNW3alDk7OzNbW1tWrVo11rdvX3by5Em1vsi2D161atV0vgbGGBs+fDgDwM6ePav167hv3z4GgH366af6fNk15PaeyUm3bt0YALZv3z6DnjsnAJibm5vO4//99x8DwNzd3TW+h0lJScze3p7Z2dmp7c14+vRpBoB17NhR43zCv9Fq1aoxnud1xmTIHoak6KKRLEJMJDw8HO3bt8fLly/RuXNnjBgxAi9evMDevXvx119/Yf/+/ejdu7fYPz09HZ07d8b//vc/NG3aFKNGjUJiYiIWLVqECxcuGBwHYww+Pj64fPky2rRpg48++ggWFhaIjIxEaGgoOnTogObNm+f79R48eBCHDx9G79698cknn+Dy5cvYtGkTIiIisGTJEnTp0gUdOnTAhAkTcPfuXRw6dAhPnz7FnTt3IJEYd3nos2fP0LJlS9SoUQNjxoxBXFwcdu/ejX79+uHUqVPw9vYGoBj9cHZ2RkhICPr16wcPDw/xHM7OzgCAjIwM9OnTB8ePH0fdunUxcuRI2NjYIDQ0FFOmTMG1a9ewdetWg2MQ4ti5cycaNWoEX19f2Nra4uXLl7h48SKOHTuGrl276nyt06dPR3BwMM6dO4exY8fC3d1d7fikSZOwa9cubNiwAV5eXhqPDwoKAgB88sknABTTfufOnUNoaKjJF2lbWloCACwszP+rSFgP1r17d433X6lSpdCuXTucOHECV69eFff9O3PmDADF6Fx2NWrUQJ06dfDo0SM8ffoUNWvWNPErIEVCQWd5hBR1ukayunfvzgCw77//Xq390qVLTCqVsjJlyrDk5GSxfeHChQwAGz58uNpfws+fP2flypUzeCTrzp07DADr37+/xjG5XM7i4uLE+/kZyZJKpWqjJXK5nHXt2pUBYKVLl2bbtm1Te9z48eMZABYcHJzn18RYziNZANj8+fPV+h87dowBYB9++KHW+Ddu3Kj1eebNm8cAsM8++4xlZmaK7ZmZmVpfQ15jSEhIYBzHsebNm6udX/DmzRu1+9AyGiLEGBoaqvU1NGzYkFlbW2uc68mTJ4zjONa2bVuxTRjd03Wu7AwdyYqIiGDW1tbMzs5O7T1oLMhlJGvWrFkMAFuxYoXW459++ikDwNatWye2DR48OMeRt169ejEA7MiRIzpjopGskoWuLiTEBCIjI3HixAlUrVoVs2fPVjvWtm1bjBgxAnFxcThw4IDYvnnzZkgkEixZskRtPUmVKlWMsjWGra2tRptEIkHp0qXzfW4AGDFihNpIiUQiwZgxYwAAjRo1wqhRo9T6+/r6AgBu3bpllOdXVa1aNXzzzTdqbT169EDVqlURFham93l4nsdPP/2ESpUqYfXq1ZBKpeIxqVSKlStXguM4bN++3eAYOI4DYwzW1tZaR/SyL7w2xKRJkyCTyTSuoPz111/BGMPHH38stm3ZsgX3799Hy5Yt8/28ushkMowaNQoymQzz58832nswLxITEwEATk5OWo8L7QkJCfl6DCnZaLqQEBO4efMmAKBDhw7ilIiqzp07Y9u2bbh58yZ8fX2RlJSEJ0+eoEqVKhrTPQDQvn17g2Np0KABPDw8sHPnTjx79gz9+vVD+/bt4enpCSsrK4PPm52np6dGm6urKwBonY4UrgqMjIw0WgwCDw8PtYRIUKVKFVy5ckXv8zx69AhxcXGoXbs2vv/+e619bG1tcf/+fYNjcHR0RJ8+fXDo0CF4eHhg0KBB6NChA1q1amW0qwh9fX3x1VdfYcOGDfj8888BKKZBN23ahNKlS2Po0KFi36pVqxrlOXWRy+UYM2YMLl26hGHDhmHWrFkmfT5CChIlWYSYgPAXr64rpoR24S/epKQkAEDFihW19tfVrg+pVCpeYr5v3z58+eWXABTrTsaOHYslS5bAwcHB4PMLtP11L6y1yelYRkZGvp87O2E9lbbn5Hle7/O8ffsWgKLWU06X36ekpOQrht27d2PZsmXYsWOHWE/JxsYGgwcPxooVK/L1/QcU3+vRo0dj/fr1CA0Nhbe3Nw4ePIiYmBhMnz4dNjY2+Tq/vuRyOUaPHo29e/di6NCh2LZtm15XAZqC8J4U/q1mJ7Srfh8NeQwp2Wi6kBATEH4Yx8TEaD0eHR2t1s/R0REAdNb20afmT05Kly6N1atX48WLF3j8+DF+++031KtXD2vXrsWkSZPEfsJ0VWZmptbzlLRpEOH7M2DAADDGdN7Cw8Pz9Ty2traYP38+Hj16hOfPn2Pbtm1o3749tm3bhsGDBxvjpYjfZ2Ghu/DR39/fKOfPTUZGBkaMGIFdu3Zh5MiR2LFjR4EseBfUrVsXgGK0UpvHjx8DAOrUqZOvx5CSjZIsQkxAqAl08eJFrQmLcGVTs2bNACiSrBo1aiAqKkrrNjEXL140Wmy1atXChAkTcO7cOTg4OCAkJEQ8JqyNefHihcbj/vvvP51/wRdlwpSeXC7XOFavXj04Ozvj6tWrJhlx06ZKlSoYNWoUjh8/jlq1auHixYviiJouOb0GQZMmTdCuXTv8+eefuHbtGk6dOoWOHTuifv36Ro1fm/fv32PIkCHYu3cvfH19sXXrVq1TqeYkXN154sQJjZHF5ORkXLp0CXZ2dmjdurXY3rlzZwDAsWPHNM739OlTPHr0CNWqVUONGjVMGDkpSijJIsQEKleujG7duiEiIgI//PCD2rFr165hx44dKF26NAYMGCC2+/r6gud5BAQEgDEmtr948ULjHHkRHh6Op0+farTHx8dDJpOpLYivV68eHB0dERISgtjYWLE9LS3NKFW5CyNhYfnz5881jllYWGDKlCmIjo7G1KlTtW6bEh0djX///dfg53/9+jXu3r2r0f7u3TukpKTAwsIi17VzOb0GVZMmTcL79+8xaNAgMMbEsg2qnj9/jgcPHiA1NTUPr0I3mUyGAQMGICQkBBMmTMDGjRtzLdkh7AeqbX2isdSsWRPdu3dHREQEfv75Z7Vj8+bNw7t37zBmzBjY29uL7V5eXqhfvz7Onz+PgwcPiu08z4vT8J988kmBTYGSwofWZBFiIuvXr0e7du3wxRdf4MSJE/D09BTrZEkkEmzcuBGlSpUS+8+ePRvBwcHYtWsXHj58iO7duyMxMRF79uxBx44dERwcbFA9qdu3b2PgwIFo0aIF6tevD1dXV7x+/RohISHIyMgQfzkAirpF06ZNw3fffYemTZtiwIAByMzMxMmTJ+Hq6iouZC9O2rRpAzs7O/zwww94+/YtKlWqBACYMmUKnJycMHfuXNy+fRvr16/HoUOH0LlzZ7i5uSE2NhaPHz/GpUuXsGjRIjRo0MCg54+KikLTpk3RuHFjNGnSBFWqVEFSUhIOHz6MmJgYTJ06Ve19oo23tzckEgkCAgLwzz//iCOS2a9uHDJkCGbMmIGoqCiUK1cOAwcO1DiXr6+vUetkffLJJzhy5AjKlSsHNzc3LFy4UKNPp06d1J5LGFnKy3TigwcPsHTpUrW2+Ph4tY3bV6xYgXLlyon3161bh7Zt22Lq1Kk4ffo06tevj2vXriE0NBR16tTBokWL1M4nlUqxceNGdO7cGYMHD8bgwYNRtWpVnD59Gjdu3EC7du0wY8YMvWMmJUABlY4gpNjIqeJ7ZGQk++STT1jVqlWZpaUlK1u2LOvXrx8LCwvTeq74+Hg2ZcoU5uLiwqysrFjdunXZihUr2LVr1xgANm3atDzH9+LFCxYQEMDatm3LKlasyKysrJibmxvz8fHRWs+H53m2ZMkSVqNGDWZpacmqVKnCvvjiC/bu3btcK75nl1MNpZy+bvrIreK7NkINqOyOHj3KWrduzezt7bVWfOd5nm3ZsoV17tyZlS5dmllaWjJXV1fWrl07tmjRIvb8+XODY4iPj2cLFixg3t7ezNXVlVlZWbFKlSoxLy8vtmPHDo3q4dBRa2nr1q3sgw8+YDY2NmoV37ObPn06A8BmzZqVY3zGqpOVU1V94Zb9scHBwQwAmzNnjl4xqMaR003bDgPPnz9nfn5+rFKlSszS0pJVrVqVTZs2LcfaXffu3WODBw9mZcuWZVZWVqx27drs22+/ZampqTnGqOt7R4ovjjGVeQlCSKH066+/wt/fH+vXr1eraURIXnXq1Annz5/Hw4cPUbt27Xyf7+zZs/D29sa8efO0bhBtiJkzZyIoKAjPnj1TG3kq6jiOg5eXF86ePVvQoRAzoTVZhBQiL1++1Gh7/vw5vvvuO1hYWKBPnz4FEBUpLsLCwnDu3Dn06NHDKAmWqgULFoDjOKNsYH3u3DlMnDixWCRY+/btA8dxtE6rhKI1WYQUIoMGDUJGRgaaN28OZ2dnRERE4PDhw0hNTcWSJUuK5ZooYnq//PILoqKixEXnOdX8yit3d3exthcAoyRGf//9d77PUVg0aNBA7etjysX8pPCh6UJCCpF169Zh69atePz4MRITE+Hg4ICmTZvis88+U1ukHBwcrNd2NO7u7moLfwszYTPp3Hh4eKB///4mj6c4cXd3R2RkJGrUqIH58+dj5MiRBR0SISUCJVmEFEF+fn7YvHlzrv2K0vqPTp064dy5c7n2Gzt2rMYefIQQUhhRkkUIIYQQYgK08J0QQgghxARo4XsB4nkeL1++RKlSpejKE0IIIaSIYIwhOTkZrq6uORaJpiSrAL18+RJVqlQp6DAIIYQQYoAXL16gcuXKOo9TklWAhK0yXrx4AUdHxwKOhhBCCCH6SEpKQpUqVXLd8oqSrAIkTBE6OjpSkkUIIYQUMbkt9aGF74QQQgghJkBJFiGEEEKICVCSRQghhBBiApRkEUIIIYSYACVZhBBCCCEmQEkWIYQQQogJUJJFCCGEEGIClGQRQgghhJgAJVmEEEIIISZAFd8JIYSQIurC9B/x348h4v2KPZuj5+HlBRgRUUVJFiGEEFIEbZR00Wh7deRvbJR0wTj+dAFERLKj6UJCCCGkCOF5XmuCpSq348Q8KMkihBBCipDttt316sfzvIkjIbmhJIsQQggpIrbbdkNmBtOr72aLbiaOhuSGkixSOLx7B3Cc4vbuXUFHQ0j+0PuZmMAe157gef0SrBKvkPwbpCSLEEIIKcRuB5/AgbI9wCdlAAAkEq6AIyL6oqsLCSGEkEIquHwP8DzUpgglUkCf5VZ0hWHBo5EsQgghpJB5fe8xgiv00GgXRrFoNKtooJEsQgghpBC5ELAKSZtPANmWXykSKwaeV4xmAZzWNVoSCYexmafMESrJBSVZhBBCSCGStPkE5NmmAyWSrClCiUSRXEmkgETKgZdn9ZNaAKPTKcEqLCjJIoQQQgqJo5U/zPG4MJollXKQy4U2xUepFBiectK0AZI8oTVZhBBCSAG7/fsenK6pu0SDRMqJyZREwkEi4SCVQu1GCVbhQyNZhBBCSAEKrdMLAJCZqSPBUk4VSqSKUSxAeV/CiaWgBiecMFe4JA8oySKEEEIKwMWGvcHLlUmT8qOw3koqAQBOpV010RIWvgNWvVui9+bvzB060RMlWYQQQogZZWZm4uoH/cHLmcYC9+wUC9uzEi1V/V8fN1GExFgoySKEEELM6OoH/bW2C4vahdIMUjGp0qyJ1TfmmImiI8ZESRYhhBBiJpcb99Z5LGtKEFCtgSWVqPbh8GHkUdMGSYyGkixCCCHEDJ6cupRrn5xqYEmkQPPjP5kwQmJslGQRQgghZvB29lKNNqkEkPNZa68kygXvAMCYMtlSbqFTbcu3KFevlhkjJvlFSRYhhBBiQrfb9INcR/0rVeqJFiCuxSpnjS7X/jRZfMR0KMkihBBCTORuu34AoD7tp1KOgZdnLXCXq5RoAABUcob3+e1mjJYYGyVZhBBCiJHJZDI86jxU3G9QIK65ylb3SjXZAoCOD/4yY7TEVCjJIoQQQozoQed+YLyiFIM2qokWY4qbWGRUAjQ6s9mM0RJToiSLEEIIMZKHXfsCAHhePcESyjIADLw8azE7zzNwyq4SCQfPv/+EhQX9ai4u6DtJCCGEGMHDrn3BeEDXCBagWnAUasmWRApIerWjBKuYoe8mIYQQkk9xT54qP8s2gqVceyWVaI5iZd8mx/O7r0wfKDErSe5dzOfevXsYMmQIatSoATs7O5QrVw4dO3bEoUOHNPrev38fPj4+cHBwQJkyZTBmzBi8fv1aox/P81i+fDmqV68OGxsbNGnSBDt37tT6/KY4JyGEkOLvzSfT1O5LJNmuFIQi0VIUGdW8ed44aM5wiZkUqpGsZ8+eITk5GWPHjoWrqytSU1Oxf/9+9O3bF0FBQfD39wcAREZGomPHjnBycsLixYuRkpKCFStW4O7duwgLC4OVlZV4zjlz5mDp0qWYOHEiWrRogZCQEIwcORIcx2H48OFiP1OckxBCSPEX3qc3tE8Rqm/snDWileWDKyGmDY4UKI4xlnuFtAIkl8vRvHlzpKen48GDBwCAyZMnY9OmTXjw4AGqVq0KADh16hS6deumloxFRUWhevXq8Pf3x9q1awEoKuh6eXkhPDwcERERkEqlJjtnbpKSkuDk5ITExEQ4Ojoa6StWRL17Bzg4KD5PSQHs7Qs2HkLyg97PJUZ4n95gPEPmewkYU1Zq54WPUJZwUNTDUiWRcmh4Pti8wZYkJv43qO/v70I1XaiNVCpFlSpVkJCQILbt378fvXv3FpMhAOjatSvq1KmDPXv2iG0hISHIyMjA5MmTxTaO4zBp0iRERkbiypUrJj0nIYSQ4uv5gF5QjFZlG8XiFAkVJ1FOG0oYLCwV04JSC8DCkhKskqJQJlnv3r3Dmzdv8OTJE6xevRpHjx5Fly5dAChGkmJjY+Hp6anxuJYtW+LmzZvi/Zs3b8Le3h7169fX6CccN9U5CSGEFF8vBvYCr7JVDicBOCG54qCWaHESBk7CILXgUS/0T9Q/G1wAEZOCUKjWZAk+//xzBAUFAQAkEgkGDhwoTs1FR0cDAFxcXDQe5+Ligri4OMhkMlhbWyM6OhoVK1YEx3Ea/QDg5cuXJjunNjKZDDKZTLyflJSUw1eBEEJIYRQ5uKfyMw5Zo1gM4DhwqiNbHBOPcZxiFEuS/ZJCUqwVyu/29OnTcfLkSWzevBkffvgh5HI53r9/DwBIS0sDAFhbW2s8zsbGRq1PWlqa3v2MfU5tlixZAicnJ/FWpUoVnX0JIYQUPlHjhyqruauTWihGsDgJoEiq1G9SC6DaIdrkuaQplElWvXr10LVrV/j6+uLw4cNISUlBnz59wBiDra0tAKiNCAnS09MBQOxja2urdz9jn1ObgIAAJCYmircXL17o7EsIIaQQSkmGMIIlkQjTgYpDUgsGiYSJbYopQkWC5bJ3JxUaLYEKZZKV3eDBg3H9+nU8evRInJYTpvhURUdHo0yZMuJIk4uLC2JiYpD9Akrhsa6urmI/Y59TG2trazg6OqrdCCGEFA0xI320tGatvRI+KhIrxY2TADWPHoadcKUbKVGKRJIlTMElJibCzc0N5cuXx40bNzT6hYWFwcPDQ7zv4eGB1NRU3L9/X63ftWvXxOMATHJOQgghxUeGLF38XJgSBKAczVIdvVJd7A7U+OtwwQRMCoVClWTFxsZqtGVkZGDLli2wtbVFgwYNAACDBg3C4cOH1abbTp8+jUePHmHIkCFiW79+/WBpaYl169aJbYwxrF+/Hm5ubmjbtq3YbopzEkIIKR7iP+oPjVErLivRkkiEkausUazqh/4qmGBJoVGoJog//vhjJCUloWPHjnBzc0NMTAy2b9+OBw8eYOXKlXBQDrd+/fXX2Lt3L7y9vTFt2jSkpKQgMDAQjRs3xrhx48TzVa5cGdOnT0dgYCAyMjLQokULBAcH48KFC9i+fbta0VBTnJMQQkjRFr/mG+CfMAAcOJXNnTkJB8YLiVbWFYZSqWIUy23vkQKKmBQmhari+65du/D777/j7t27ePv2LUqVKoXmzZtjypQp6Nu3r1rfe/fuYebMmbh48SKsrKzQq1cvrFy5EhUrVlTrx/M8li1bhqCgIERHR6N27doICAjAqFGjNJ7fFOfMCVV8V0EVsklxQu/nYiHh0A6wgxsBABnpioru8sysiu6AItHKwgAwcN194OY/3bzBEnWFpOJ7oUqyShpKslTQLyVSnND7uViIn9hN+RmHjHTFR17OiVvlqCdYAKC4krDSjmNmjJJoVUiSrEI1XUgIIYQUBomfZCVYgGIdFuOVW+UAABh4le10JBLlNGKDhmaNkxRulGQRQgghGtT3JBSvKOQBSBTtUglT6y+RAuW/WWnGGElhR0kWIYQQoiL51lWNNolEkV8BALRUfFeUbOA02knJRkkWIYQQomrDN4qPWRcTitOEfLYRLsUxRSfnX6lkA1FHSRYhhBCilPp5d/FzjoNyd4+sdVlZiVYWiQSwXLmbts0hGugdQQghhABI++N7ACrJFM8ACaeyITSn2DZHwpRXFjLY/3wY1jY2BRQxKewoySKEEEIAsEeXAGRdSQgoi41KsoqNCh85CWC1fB8lWCRHlGQRQggp8dLm9FS7n1WqQTmipUKi3J/QzsnZPMGRIouSLEIIISVa2vze6g1SDpzKuivVTX7FfQvnbDJ5XKTooySLEEJIiSVb0l+9QSoBJ15DmLUhNGOKhfCKPhzsXSqbM0xSRFGSRQghpESSBc3KuiPhFBUbeJUNoFX6qhZtsF990hzhkWKAkixCCCElCs/zyFwzBEiXax6UcBAmCDlk25xQKoHdctqXkOiPkixCCCElRmZmJvh1w1XKMgCcpRQMioRLpf4o1FZjSThwI74xV5ikmKAkixBCSInBrxsOyDW3xQEASJVFR7PdBwBIONh+0M6ksZHih5IsQgghxV7GbyM0kyspJ7ZxllKwDLmiTaUdUk6xJ+EXe8wcMSkOjJZkpaamYteuXZDJZOjZsyeqVatmrFMTQgghBsl8lwy20x+QMzA++xorRTLFKau6c5ZSQK7so7LZszTgACwtLc0YNSkuDEqyJkyYgGvXruGff/4BALx//x6tW7cW7zs5OeHMmTNo2rSp8SIlhBBC8ojt9M+6w2UlTkJipZpoAQBTq4oFcP7rKMEiBpPk3kVTaGgoBg4cKN7fsWMH/vnnH2zfvh3//PMPKlWqhAULFhgtSEIIISSvMv8Yq3afE5Is1bVWwvSgsB5Lopge5Cwl4Cb/BuvybuYKlxRDBo1kxcTEwN3dXbwfHBwMT09PjBgxAgAwceJEBAYGGiVAQgghxDAZmk0SCaCcNswavVJSSb6sPz9g4thISWDQSJa9vT0SEhIAKC6HPXv2LHr06CEeL1WqFBITE40SICGEEJJX8t1jtbZzUk6RaGkbvVLeJJO3mDNUUowZNJLVrFkz/Prrr/D29sbBgweRnJyMPn36iMefPHmCihUrGi1IQgghRF/yS1t1HxQqu2dt/6xsVxYgLVUTlrYOJo2PlBwGJVmLFi1Cjx494OnpCcYYBg8ejJYtW4rH//zzT7RrR/VECCGEmBefHA+8PC3ez77AHYCYaAEApNKsBw9ZBctytAaLGI9BSZanpycePHiAy5cvw9nZGV5eXuKxhIQETJ48GZ06dTJWjIQQQkiu+MPfAJnRWQ1SSVZJBkCRaDGmGLxSKdFg+fEu8wVJShSDkqzz58+jfv366Nevn8YxZ2dnjBw5Evfv3893cIQQQog++MP+igXtfLakChJxD0LGM0UZB+XgFSfhwLX9zPzBkhLDoIXv3t7eOHlS9y7kZ86cgbe3t8FBEUIIIfrij03S2s5JhPIMEkAqAWcpVbvBSgppvbZmjpaUJAaNZDGmY98nJZlMBqnqPDchhBBiAvyJTxVTgAKJBJDLFRsQSrlsGz5n4SQcMGiDmaIkJZXeSdbz588REREh3n/w4AHOnz+v0S8hIQFBQUG0rQ4hhBCT4f+7AkTsUEwPZsuiOCkHJgcAxYJ3TnXRu9DHRgqJtY3Z4iUlk95J1saNG7FgwQJwHAeO47Bo0SIsWrRIox9jDFKpFEFBQUYNlBBCSMnGX90LvL+ivu5KG4liHRaTQzGixVhWoVGJIumSDNxo6nAJ0T/JGjp0KBo1agTGGIYOHYqpU6eiQ4cOan04joO9vT08PDyoThYhhBCj4ONeAf8uz9bIayZbHKdYacwzMdFSHsjqU3UUJJ5dTRkuISK9k6z69eujfv36ABSjWh07dkT16tVNFhghhBDCX/4iK5nis80LClvkSDhFWQZOWaJBLM+Q7dquRp9CUquZqUMmRGTQwvexY7O2K4iOjkZsbCxq1aoFe3t7owVGCCGkZFNLsHQREy2Vj0BW8iX06fYjrcEiZmdQCQcACAkJQb169VC5cmU0a9YM165dAwC8efMGTZs2RXBwsLFiJIQQUsLwiVH6d5ZIFAmVVKL8XAJYWIg3Se8NlGCRAmFQknXo0CEMHDgQ5cqVw7x589RKOpQrVw5ubm7YuJEWFRJCCDHQ/R9zPi4kVsLIlUSiXJOlfpP0XG/6WAnRwaAka+HChejYsSMuXryITz/9VON4mzZtcPPmzXwHRwghpORhN9fo31lItLLfLCyA9stzfzwhJmRQkvXPP/9g6NChOo9XrFgRsbGxBgdFCCGkZGK3vgX419oPiuvZJdk+curJloUUkq4/QeJQyuTxEpITgxa+29nZ4d27dzqPP336FGXLljU4KEIIISULk8mAB4vVq7cDWQvagayrB1XbJSpjBRJA0ukHs8RLiD4MSrK8vb2xefNmTJ8+XeNYTEwMfv31V/Tu3Tu/sRFCCCkB2L2F2g9kv3IQyLpiUFkLCwBQZSAk1dubPlBC8sig6cJFixYhMjISLVq0QFBQEDiOw/Hjx/HNN9+gcePGYIxh3rx5eT7v9evX8dlnn6Fhw4awt7dH1apVMXToUDx69Eitn5+fn1h5XvVWr149jXPyPI/ly5ejevXqsLGxQZMmTbBz506tz3///n34+PjAwcEBZcqUwZgxY/D6teawdV7OSQghRDsml4Pd/15xJ1upBo5TKb8gfFQdtbKQgrO2gqTjKkqwSKFl0EhW3bp1cfHiRUybNg1z584FYwyBgYEAgE6dOuHnn3+Gu7t7ns+7bNkyXLp0CUOGDEGTJk0QExODtWvXolmzZrh69SoaNWok9rW2tsZvv/2m9ngnJyeNc86ZMwdLly7FxIkT0aJFC4SEhGDkyJHgOA7Dhw8X+0VGRqJjx45wcnLC4sWLkZKSghUrVuDu3bsICwuDlZVVns9JCCFEO8bzwH9LddfBkkjA8bzi6nW1KUHF5xzHAWW7myFSQgzHMZZ9Ajxv4uPj8d9//4HnedSoUQPly5c3+FyXL1+Gp6enWkLz+PFjNG7cGIMHD8a2bdsAKEay9u3bh5SUlBzPFxUVherVq8Pf3x9r164FoNhb0cvLC+Hh4YiIiIBUKgUATJ48GZs2bcKDBw9QtWpVAMCpU6fQrVs3BAUFwd/fP8/nzE1SUhKcnJyQmJgIR0fHPHyliqF37wAHB8XnKSkAFbYlRRm9n3PEniwDMjMVU35iNXc+232mfescgUQCrsVi8wRMih4T/xvU9/e3wcVIBaVLl0aLFi3QqlWrfCVYANC2bVu1BAsAateujYYNG+L+/fsa/eVyOZKSknSeLyQkBBkZGZg8ebLYxnEcJk2ahMjISFy5ckVs379/P3r37i0mWADQtWtX1KlTB3v27DHonIQQQtSx8FzKKgjThBy0l2ZQ3ijBIkWBQdOFW7ZsyfE4x3GwsbERq8FbW1sbFBygGCV69eoVGjZsqNaempoKR0dHpKamonTp0hgxYgSWLVsGByFzBXDz5k3Y29uLey4KWrZsKR5v3749oqKiEBsbC09PT43nb9myJY4cOZLncxJCCFHHwpfnsP+gBAAPqA5ccUD2sQCu+fcmjpIQ4zEoyRIWngNA9tlG1XaO4+Do6IiAgADMnj3boAC3b9+OqKgoLFyYdfWJi4sLZs+ejWbNmoHneRw7dgzr1q3D7du3cfbsWVhYKF5WdHQ0KlasmLWAUuXxAPDy5Uuxn2p79r5xcXGQyWSwtrbW+5zayGQyyGQy8X5Oo3CEEFKcsOerVO7ksEpFdbNnAGLWJZEAjb41VXiEmIRBSdatW7cwduxYlC1bFp9++ilq1aoFQLF+6ueff0ZCQgLWrl2LV69e4aeffkJAQABKlSqFSZMm5el5Hjx4gE8//RRt2rRR25R6yZIlav2GDx+OOnXqYM6cOdi3b5+4+DwtLU3rKJqNjY14XPVjbn2tra31Pqc2S5YswYIFC3S/YEIIKYbYi+sAUxmiEq8c5LJKMajVvFLpK1GsceUazzdLrIQYk0FrslavXo2KFSvi1KlTGDBgABo3bozGjRtj4MCBOHXqFMqXL4/ff/8d/fv3x8mTJ9G6dWusW7cuT88RExODXr16wcnJCfv27ct1MfmMGTMgkUhw6tQpsc3W1lZt5EiQnp4uHlf9qG9fffppExAQgMTERPH24sWLHF8TIYQUZSzmd7DodQAuaR5Urdauel/4XFh71Xg+JVikyDIoyQoODka/fv20HuM4Dn379sWBAwcUTyCRYNCgQfjvv//0Pn9iYiI+/PBDJCQk4NixY3B1dc31Mba2tihbtizi4uLENhcXF8TExGhMaQrTg8J5hak+oT173zJlyoijV/qeUxtra2s4Ojqq3QghpLhhMefBYtYDTAbwmeoHJSpLLXRti6PcGodrSNODpGgzKMnieR4PHz7UefzBgwfgVS67tba2FqfTcpOeno4+ffrg0aNHOHz4MBo0aKDX45KTk/HmzRu1Kxw9PDyQmpqqcWXitWvXxOMA4ObmhvLly+PGjRsa5w0LCxP75eWchBBS0rDMTEVyhX/VpwcBgJNkS6q0FBmVcICFFLBwA1d3jtniJsRUDEqy+vbti3Xr1mHt2rXiNBmgSJB++uknrF+/Hn369BHbr1y5Iq7byolcLsewYcNw5coV7N27F23atNHok56ejuTkZI327777Dowx+Pj4iG39+vWDpaWl2lQlYwzr16+Hm5sb2rZtK7YPGjQIhw8fVpvCO336NB49eoQhQ4YYdE5CCCkJGGNgr38D4v7Q/0EaI1cWgIUFuNoB4GqPM12whJiRQQvf16xZgydPnmDq1KmYNWuW2nTb+/fv0bJlS6xZswaAIimytbXFzJkzcz3v559/joMHD6JPnz6Ii4sTi48KRo8ejZiYGDRt2hQjRowQt9E5fvw4jhw5Ah8fH7VpzMqVK2P69OkIDAxERkYGWrRogeDgYFy4cAHbt29XW+f19ddfY+/evfD29sa0adOQkpKCwMBANG7cGOPGjTPonIQQUiK83aj7GCdR/DkvDGyJa9t5jalDrtosEwVISMEwuOI7Ywx//vknjh8/jmfPngEAqlWrhh49eqB///6QSPI+SNapUyecO3cux+dMSEjAlClTcPXqVbx8+RJyuRy1atXCqFGjMGvWLFhaWqo9hud5LFu2DEFBQYiOjkbt2rUREBCAUaNGaZz/3r17mDlzJi5evAgrKyv06tULK1euRMWKFQ0+Z06o4rsKqpBNipMS9H5mb84B7LHyjkqFdqbyUVe7gJMAFT8Fl4+aioSoKSQV3/OcZKWlpWHOnDnw9vZWmxIkeUdJlooS9EuJlAAl6P3M3vyhnjjpSqZUj2nBVZluuiBJyVNIkqw8DzfZ2toiKCgIr169yleAhBBCijYWl/PuHwAUo1TCR21b5EgtKMEixZZBa7KaN2+Of/75x9ixEEIIKSoSd+Z8nJNkjWIJn3PZ/q4vPQFcDrUFCSnqDEqyfvjhB/Ts2RONGjWCn5+fuI0NIYSQYo7ngZS9YEyueUxc5K6SXAHZEqz64Fy8zREpIQXOoIXvTZo0wZs3b/Dq1StYW1vDzc1No9I5x3G4ffu20QItjmhNlooStIaFlADF+f2cvBdgPBifoUimmMpNoPq5ynY5XAV/MwdLSqxCsibLoCGoMmXKoGzZsqhbt67BARJCCCliUvZrJlSC7NODAqkE4CTgyo03T4yEFCIGJVlnz541chiEEEIKPZUkigPAoDINyJjmmitFZ3DlqLgoKZloMRUhhJDcpR/SbJNIFNOBnFBtlNPowpX1M3VkhBRa+UqyMjIy8ODBAyQmJqrtVSjo2LFjfk5PCCGkMJD9pXmlIACOk4IJC92zj2JJJOBKjTBvnIQUMgYlWTzPIyAgAOvWrUNqaqrOfnK5lqtPCCGEFA2ZFwB5ktYES/ic46SAVKp2tSHHSQGHoQBtM0ZKOIM2iF68eDECAwMxevRobNmyBYwxLF26FOvXr0eTJk3wwQcf4Pjx48aOlRBCiDkwBshPAtDxR7RqgVHljZNYijc4jaAEixAYmGRt2rQJQ4cOxS+//AIfHx8AigKlEydOxLVr18BxHM6cOWPUQAkhhJgJf0p5FaFQ4YfLqtiuJcFSu1mUL7CwCSlsDEqyIiMj0blzZwCAtXJDz/T0dACAlZUVRo8eja1btxopREIIIebAWCiY/CSyiicqP+OUC9pVEy1tN6kFYNe5ACInpHAyaE1W2bJlkZKSAgBwcHCAo6Mjnj59qtYnPj4+/9ERQggxOcbOgCHr2sCsawSzXS0ojGJJJZq1sjgJYNnLZDESUhTpnWRt2bIFHTt2hLu7O5o2bYrr16+Lx7y9vfHDDz+gadOm4HkeP/74Iz744AOTBEwIIcR45OwUOJX/1HCcepkGlu2jKqvetA6LkGz0ni4cN24cLl++DADw9/eHTCaDTCYDACxatAgJCQno2LEjvLy8kJSUhJUrV5omYkIIIUaRyZ8Ex3QkWKokOazDklgAtv0owSJEC71HslS3OOzbty/69u0r3m/QoAGePHmCs2fPQiqVom3btihTpoxxIyWEEGIUmXwyGC5DCgtwnJYpwewjVixr/0EFlc8tPzRLzIQURUar+O7k5IR+/foZ63SEEEJMIJPPBGOXIOGk2gq0q9M1NQgA0u5ZC+IJIVrlKcl6+/Ytnj9/rnf/qlWr5jkgQgghpsOzk9oTLMVmhCp7EWrZ7Fkg7WbCCAkpPjimOg+YA4lEojmsnAuq+J6zpKQkODk5ITExEY6OjgUdTsF69w5wcFB8npIC2NsXbDyE5EchfT+ny49CCg4cp/h5rliHlbUeS21dlsrVg6pXHkLSxVzhEmI4E/8b1Pf3d55GsoYPH45mzZrlOzhCCCHmlZZ5CBJIc5ziY2BZiRYnAYNqMdIWABxMHichxUmekqxevXph5MiRpoqFEEKICaRlHgLAoBy4EimSKqikUpxKYgUw8ODQFhxnZ8ZoCSk+jLbwnRBCSGHFwHESAExxpTjHA0wxZahIqpgywQLAFMkXOAYpR2uvCMkPSrIIIaSYSsm4D+BfSDlLLUeZuDUhx3Hg1Sq4c7CgBIuQfNM7yapWrRocHGg+nhBCioLkjP2A6horJQbFKJaiWXGcV2ZbjPFg4GEtpe1xCDEGvZOs8PBwU8ZBCCHECJLe3wLwCByEKwiFEgxMeZUgl5Voia1CDz776Qgh+UDThYQQUkwkvt8jFmNQX+AurMGCeqKV1UGxCJ7jaBSLECOiJIsQQoqBxPd7IKZQnOZehEyRSYmJlrJR8YExME4OO2l/8wVMSAlASRYhhBRxGRkZAFOMRGkWjVYscFckV0w5TciyjiknDG24PuYNmpASgJIsQggp4lL4fZBAy/Y3IiHR0jVNaAOpVGryOAkpaSjJIoSQIioxPQ6ZOAwprMBJVEewVBe5C1cYZpVsUO3HoQ3sLFzMFjMhJYleSdaWLVsMOrmvr69BjyOEEJKzN+mbAQASSME4JiZTTDltmD3RUlDNsjhYow8sLbXV0CKEGINeSZafn59GmzDvn31/adX1AJRkEUKIccnlcsRnbAMARXkGZb0rVdkTLah24RhKWQ4xT7CElHB6JVnZa2QlJCRg7NixcHJywpQpU1C3bl0AwIMHD/DTTz8hOTkZmzdvNn60hBBSgjHG8Pb9FkiUNbAAiFcRKtZaSbLuM/XRKwYGCSehBIsQM+JY9qEoPYwbNw6RkZE4ceKExpUsPM+je/fuqFKlCjZu3Gi0QIujpKQkODk5ITExEY6OjgUdTsF69w4QdhRISQHs7Qs2HkLywwTv51dpfwBgkMIiK8HiFIvdOeXOz+rFR7MwxgMc4Gw1It9xEFIkmPh3ir6/v3O6HEWn4OBgDBgwQMulwoBEIsHAgQMREhJiyKkJIYSoeJW2A69Sf1eUaBCnBxWy/43MGAMDr35TbpVDCRYh5mfQ1YWMMTx48EDn8X///VfjHz8hhJC8iUn9VUysOGirgaWgWPQOQLnwPfuxMtajTB4rIUSTQSNZ/fv3xy+//IJVq1YhNTVVbE9NTcXKlSsRFBSEfv36GS1IQggpaaJTgxSfcNBevV34jGWtudI2gkUJFiEFx6A1WYmJiejbty8uXLgAS0tLuLgoaqxER0cjIyMD7dq1w6FDh+Ds7GzseIsVWpOlgtZkkeIkH+/nNylRkOEwJMrq7RyXtZhdMZKVtWVOVvKlOcLFgUMZm9H5eRWEFF1FeU2Wk5MTzp07hz///BN+fn6oX78+6tevj3HjxiE4OBjnz583KMG6fv06PvvsMzRs2BD29vaoWrUqhg4dikePHmn0vX//Pnx8fODg4IAyZcpgzJgxeP36tUY/nuexfPlyVK9eHTY2NmjSpAl27typ9flNcU5CCNFHbMojvEgJQjoOg+OgdYsc1VEr4aPaCJZy9KqszRhKsAgpBPJV8b1fv35GnRZctmwZLl26hCFDhqBJkyaIiYnB2rVr0axZM1y9ehWNGjUCAERGRqJjx45wcnLC4sWLkZKSghUrVuDu3bsICwuDlZWVeM45c+Zg6dKlmDhxIlq0aIGQkBCMHDkSHMdh+PDhYj9TnJMQQvSRnBIDGULBAZBw0Ln2ClBcKchxEtUKWCo1sDiUtxlr0lgJIfozaLpQEBUVhfPnzyM2NhaDBg1C5cqVwfM8EhIS4OTklOe9sC5fvgxPT0+1hObx48do3LgxBg8ejG3bFAX4Jk+ejE2bNuHBgweoWrUqAODUqVPo1q0bgoKC4O/vL8ZXvXp1+Pv7Y+3atQAUfwl6eXkhPDwcERERYoymOGduaLpQBU0XkuIkj+/niOQgWHCKTZw5KEexdEwR6sLBCuVtafSKEABFe7qQMYaZM2eievXqGDVqFGbOnClO6SUnJ8Pd3R0//fRTns/btm1btQQLAGrXro2GDRvi/v37Ytv+/fvRu3dvMRkCgK5du6JOnTrYs2eP2BYSEoKMjAxMnjxZbOM4DpMmTUJkZCSuXLli0nMSQkhuHidugFSZYGVh6iNVKhOD4j2Wtei9gu14SrAIKYQMSrICAwOxZs0azJo1CydPnlS7ZNjJyQkDBw7E/v37jRIgYwyvXr1CuXLlAChGkmJjY+Hp6anRt2XLlrh586Z4/+bNm7C3t0f9+vU1+gnHTXVObWQyGZKSktRuhJCS63Hir7DIeYBKJZlS3HimUvtKOhoVbMebI1RCiAEMSrJ+/fVX+Pr6YvHixfDw8NA43qRJE62L1Q2xfft2REVFYdiwYQAUVzACEK9oVOXi4oK4uDjIZDKxb8WKFTXWNwiPffnypcnOqc2SJUvg5OQk3qpUqZLLqyeEFFePE38VfwAzprgBylSKKT5TG71iwuiVIsGqZDcR1tbWBRA5IURfBiVZL168QNu2bXUet7e3N8oozYMHD/Dpp5+iTZs2GDtWsZgzLS0NALT+cLGxsVHrk5aWpnc/Y59Tm4CAACQmJoq3Fy9e6OxLCCnmVGYDeW2HmdCJidODPOMBjsHF7mPzxEgIyReDri6sUKFCjgnC33//rba2yRAxMTHo1asXnJycsG/fPnExua2tLQCII0uq0tPT1frY2trq3c/Y59TG2tqa/vIkhOB+3K+wkKiuw+LAMwYJFG1i/qXyCWMAOCe42tEVzIQUFQaNZA0cOBDr16/H06dPxTZh+uzEiRPYtGkThgwxfKf3xMREfPjhh0hISMCxY8fg6uoqHlMtfJpddHQ0ypQpIyYyLi4uiImJ0dhmQniscF5TnJMQQrS5E/ebmFwxljU9yIODnAE8y5o+5JW393LAzeFjuNlTgkVIUWJQkrVgwQK4uLjAw8MDvr6+4DgOy5YtQ/v27fHhhx+iSZMm+Prrrw0KKD09HX369MGjR49w+PBhNGjQQO24m5sbypcvjxs3bmg8NiwsTG2NmIeHB1JTU9WuTASAa9euicdNdU5CCMnuztvfIVVZe6WgyLgUCRcHnnGQq9ze8xzcHWl6kJCiyOCK71evXsXs2bMRFRUFGxsbnDt3DgkJCZg3bx4uXLgAOzu7PJ9XLpdj2LBhuHLlCvbu3Ys2bdpo7Tdo0CAcPnxYbcry9OnTePTokdoIWr9+/WBpaYl169aJbYwxrF+/Hm5ubmrrykxxTkIIEdx6+zsAYYpQmVghK7kSR7RUbhk8UMPRv6BCJoTkU76KkRrb9OnTsWbNGvTp0wdDhw7VOD56tKIOzIsXL9C0aVM4Oztj2rRpSElJQWBgICpXrozr16+rrXuaPXs2AgMD4e/vjxYtWiA4OBh//fUXtm/fjpEjR4r9THHO3FAxUhVUjJQUJ9nez/+k34Ec/0LCAVIwZVV3llXhXe3Bih/JPONQ23mimQMnpJgoJMVIC1WS1alTJ5w7d07ncdVQ7927h5kzZ+LixYuwsrJCr169sHLlSlSsWFHtMTzPY9myZQgKCkJ0dDRq166NgIAAjBqluTO9Kc6ZE0qyVFCSRYqTbO/nW2m7wHGKhEoCleRKmWgBygXvyh9xPAPs0AFVS9criOgJKfqKUpI1fvx4cByHDRs2QCqVYvz43IvfcRyH33//PW9RlzCUZKmgJIsUJyrv57+froO0lBUkEuWWOci6ilCYNOQ4AEy1RhaH+mU+KpjYCSkOCkmSpVcJhzNnzkAikYDneUilUpw5cybHDUyBnDc4JYSQkkRMnpTrsXgwSJRJFcdxWYVIlW0NKcEipFjQK8mKiIjI8T4hhBDtJNn+3lTkU4pEi8tqAABkAmhCCRYhxYZeVxc2a9YMx44dE+9v2bKFEi1CCNEbpzIVKNRx55S1sThkMg7vGUcJFiHFjF5J1p07d/DmzRvx/rhx43D58mWTBUUIIUXZxZht4uc8hAKjWYmWWqkGAHIGuKJbQYVLCDERvZKsatWq4dSpU5DL5QAUV/nRmitCCNF0/uUmSLW0C4kWr0y2suphKUayKpTN31ZkhJDCR68k65NPPsGWLVtgY2MDR0dHcByHCRMmwNHRUefNycnJ1LETQkihcvblZmS/XJsxTtwAmlcubOeVyRbPOLzngRblc79imxBS9Oi18P2LL77ABx98gNDQULx69QqbN29GixYtUKNGDVPHRwghhV584lv8L/kwpBwgkQBMZaCfCSNYnHLJu0otLMYAD+cRBRAxIcQc9EqyAKB79+7o3r07AGDTpk34+OOP81TdnBBCiqPTkYrRK6miCJYGYWpQorKVDpRtHABra1vzBEoIMTu9kyxVPM/n3okQQoq5N4kxGtODPAMkKo2qU4Wq5AxoV2mcKcMjhBQwvZKs58+fAwCqVq2qdj83Qn9CCCmObiYfV1RxVxvByj6cpVh7pVoQi4FDDXQxfYCEkAKlV5Ll7u4OjuOQlpYGKysr8X5uhKsRCSGkuMr+o1CYHhTwyhtUSjg0suuJMs4VzBYjIaRg6JVk/fHHH+A4DpaWlmr3CSGEaGIqo1lCqQZhy5yOlXwhkeh1YTchpIjTK8ny8/PL8T4hhJREQuLEcYrRKgnTMrLFOPC8YhSrXfkRlGARUoIY9K99/PjxuHbtms7jYWFhGD+e6r4QQoqvgxFbIeeVVwwKZRmQVdFdwDNAzgPtK4yElZWV+QMlhBQYg5KsTZs24cmTJzqPh4eHY/PmzQYHRQghhdmf4dvAAeDBieuvVBMtueqmzzyQwbKWWxBCSg6DSjjk5uXLl7C1pdovhJDi58+n2yBRmRLMZBwslFcOavurVdhGhxBS8uidZIWEhCAkJES8v2HDBpw6dUqjX0JCAk6dOoUWLVoYJ0JCCCkEYt/G4lzCSVhqXPPDadTAkjL1Ts0daPNnQkoivZOsf//9F3v37gUAcByHa9eu4e+//1brw3Ec7O3t0bFjR6xatcq4kRJCSAF5+PQ+7rL/iTWxhMXtTPk/nlNUxxKSLdURLR5AhTIu5gyXEFJIcIyxPI9kSyQSbNu2jbbVyaekpCQ4OTkhMTERjo6OBR1OwXr3DnBwUHyekgLY2xdsPIQoxSa/wrlXp8TkyoJjyiSLZSVdgNgGABbvZOjewF9xAno/E2J+Jv6dou/vb9pWhxBCcnD21SlIVEavFPsQqoxmMSiyLAYI1d7ljOoIEkKMsPA9JSUF8fHx0DYgRtvqEEKKsu2Pt2uswRJ+0jHGARwTG1V/AspppTshBAYmWenp6ViwYAF+//13vH37Vmc/2laHEFIUMcaw7fEOxbiUliRLzgApp0y0ICRYiv/LGYf+VYcBmGi2eAkhhZNBSdbkyZOxefNm9O/fHx06dEDp0qWNHRchhBSIjIwM7Hy6R22KUFjgzimzLgYmjlZlTRsqPnHmylJVd0IIAAOTrAMHDuCjjz5CUFCQseMhhJACwxjDjid7xMQp+8oqli3RUjRmffB27okyZcooFt0SQko8g5IsjuPQrFkzY8dCCCEF6o+HO2CZbQRLzgApkJVxieuthEXuis+G1BplzlAJIUWAQWPa/fr101qIlBBCiqoN97fr/IEoZ1l7EvIqNzmvqINFCRYhRBuDRrLmzp2LoUOHwt/fHx9//DGqVq0KqVSq0a9MmTL5DpAQQkyFMYag+zsAQEsldwUeir9G5SxrhEvxWMXHwdWGmjRGQkjRZVCSVbt2bQDAzZs38fvvv+vsR1cXEkIKqwsPruKeXLHRvXpBUQXVxe5CZUCJymbQcgBj6tAIFiFEN4OSrG+//RYcR8X2CCFFU9C97VmJE5eVSHHKLXIkyuRKSLQEwp+NDJRgEUJyZ1CSNX/+fCOHQQgh5vHzvay1V7r+VuSRNWoFsURD1jG/upRgEUJyZ5RiLomJiTQ1SAgp9H7+Z7uYLIllGlQSLR7qyRSD5oJ3SrAIIfoyOMm6ceMGfHx8YGdnh7Jly+LcuXMAgDdv3qBfv344e/assWIkhJB8i01+CwbF9KAqtaSKZX0UEiu58pbJAL96lGARQvRnUJJ1+fJltG/fHo8fP8bo0aPVNowuV64cEhMTqVApIaTQkMlk2BF+LNd+QoIlVyZbPLKSrHaOLUwdJiGkmDFoTdbXX3+N+vXr4+rVq0hOTsZvv/2mdtzb2xubN282SoCEEJIfW+/8iTdIFUewGNQruasubhcXwCvbmPLQxHoj6WIfQkieGTSSdf36dYwbNw7W1tZaf/C4ubkhJiYm38ERQkh+JCQk4A1SNdqFtVZq96G5/soVFeBffxQlWIQQgxg0kmVpaak2RZhdVFQUHBwcDA6KEEKM4ffnf0ECzasImconnMrVg0Ki1b6UB5pUa2i+QAkhxZJBI1mtW7fGvn37tB579+4dNm7cCC8vr3wFRgghhuJ5HktubdcYrRK2xxHu88i2TQ4D3jNQgkUIMQqDkqwFCxbgxo0b6NWrF44ePQoAuH37Nn777Tc0b94cr1+/xty5c/N83pSUFMybNw8+Pj4oU6YMOI7Dpk2bNPr5+fmB4ziNW7169TT68jyP5cuXo3r16rCxsUGTJk2wc+dOrc9///59+Pj4wMHBAWXKlMGYMWPw+vXrfJ2TEGJeMpkMy+7s0vrDTTXRyj41KFceG1ezr5kjJoQUVwZNF7Zq1QpHjhzBpEmT4OvrCwD4/PPPAQA1a9bEkSNH0KRJkzyf982bN1i4cCGqVq2KDz74IMcyENbW1hoL7p2cnDT6zZkzB0uXLsXEiRPRokULhISEYORIxSLW4cOHi/0iIyPRsWNHODk5YfHixUhJScGKFStw9+5dhIWFwcrKKs/nJISY36r7+8EYU1/drkJItAD1qUJA8RAnu1KmDpEQUkJwjKkOqOfdrVu38PjxY/A8j5o1a6J58+YGLxKVyWSIj49HpUqVcOPGDbRo0QIbN26En5+fWj8/Pz/s27cPKSkpOZ4vKioK1atXh7+/P9auXQtAsSGsl5cXwsPDERERIW5sPXnyZGzatAkPHjxA1apVAQCnTp1Ct27dEBQUBH9//zyfMzdJSUlwcnJCYmIiHB0d9f46FUvv3gHCOr6UFMDevmDjIUVSYloKfn5wEBzHIAEgVW6Zo21dFpCVhwk/BKc3NlIdLHo/E1KwTPxvUN/f3/mu+O7h4YEhQ4Zg2LBh8PT0zNdVONbW1qhUqZLe/eVyOZKSknQeDwkJQUZGBiZPniy2cRyHSZMmITIyEleuXBHb9+/fj969e4sJFgB07doVderUwZ49eww6JyHEfO7HhOPH+wfV2sTColCfIlSdKszggSkNhhsvwSKEECW9pgvPnz9v0Mk7duxo0OP0kZqaCkdHR6SmpqJ06dIYMWIEli1bpnZV482bN2Fvb4/69eurPbZly5bi8fbt2yMqKgqxsbHw9PTUeJ6WLVviyJEjeT4nIcR85HI59r68ovJXIwfVnZ15puUKQ2XB0dkfUHJFCDENvZKsTp06qY1QMcb0GrEy1X6GLi4umD17Npo1awae53Hs2DGsW7cOt2/fxtmzZ2FhoXhZ0dHRqFixokasLi4uAICXL1+K/VTbs/eNi4uDTCaDtbW13ufURiaTQSaTifdzGoUjhOhv0e3dinVV2fYhlDCA57KKi6qSM6AeV8F8QRJCShy9kqzQ0FC1+zKZDLNnz0Zqair8/f1Rt25dAMCDBw/w66+/wt7eHsuXLzd+tEpLlixRuz98+HDUqVMHc+bMwb59+8TF52lpabC2ttZ4vI2NjXhc9WNufa2trfU+p664FyxYkOvrI4TkDcs2UqW4z4EHg0Q5XchxKuUbGNC1VBN41mpcIPESQkoGvdZkeXl5qd2OHTsGKysr3LlzB7NmzUKfPn3Qp08ffPHFF7h16xYsLCxw7Fju+4QZ04wZMyCRSHDq1CmxzdbWVm3kSJCeni4eV/2ob199+mkTEBCAxMRE8fbixQu9XhshRDue5/F12A61NmHASpFQceIehLxyHVYmA+TgKMEihJicQQvft2/fjjFjxoijN6rs7OwwZswYbNu2Ld/B5YWtrS3Kli2LuLg4sc3FxQUxMTHIfgGlMD3o6uoq9lNtz963TJky4uiVvufUxtraGo6Ojmo3Qohh5HI5vrmhqIclLmRH1kJ3iO0cGOPAMw6ZjAPAYXajIQUXOCGkxDAoyXr37p3WhEQQHR2N1FTN/cJMKTk5GW/evEH58uXFNg8PD6SmpuL+/ftqfa9duyYeBxR7LZYvXx43btzQOG9YWJjYLy/nJISY1ty/d4tLsOQqf/MIiRavssGzUHCUMWB2oyGwtLQ0f8CEkBLHoCSra9euWLNmDQ4cOKBxbP/+/VizZg26du2a7+C0SU9PR3Jyskb7d999B8YYfHx8xLZ+/frB0tIS69atE9sYY1i/fj3c3NzQtm1bsX3QoEE4fPiw2hTe6dOn8ejRIwwZMsSgcxJCTEeoN6q296Ay2eKhWbbhPQ+4S8tSgkUIMRuDKr7//PPP6Ny5M4YMGQIXFxfUqlULAPDkyRO8fPkSNWvWxE8//WRQQGvXrkVCQoJ4ld6hQ4cQGRkJAJgyZQri4+PRtGlTjBgxQtxG5/jx4zhy5Ah8fHzQr18/8VyVK1fG9OnTERgYiIyMDLRo0QLBwcG4cOECtm/frlY09Ouvv8bevXvh7e2NadOmISUlBYGBgWjcuDHGjRtn0DkJIcb3xVXFGiyLbBc481D+1aiyN6HqMQAY49HDtMERQogKgyu+p6enIygoCEePHsWzZ88AANWqVUPPnj0xceLEHBeA58Td3V08X3bh4eFwdnbGlClTcPXqVbx8+RJyuRy1atXCqFGjMGvWLI2/Unmex7JlyxAUFITo6GjUrl0bAQEBGDVKszbOvXv3MHPmTFy8eBFWVlbo1asXVq5ciYoVKxp8zpxQxXcVVCGb5CJVJsO8m/vBGCDhFNXchYruAo7TXtlduPpwQfOR5gmW3s+EFKxCUvE939vqEMNRkqWCfimRXMy6ohjB4pR1r6TKjxItiVZ2Zk2wAHo/E1LQCkmSZdB0ISGEmEvg5QN4iXSNUSthepBB8b/smz0LHzMYsKyVGRMsQghR0jvJmjp1ap5OzHEc1qxZk+eACCFEMO3yDsWolY7jwpWDHKeo7q5Krry6cLHnMNMGSQghOuidZK1duzZPJ6YkixCSH9Mu78gaodK11krlEz5bxXfhOF2MQggpKHonWTzP596JEEKM4MaTh+ICdyCrHAOncl9IwIRaWKojWTwAOwDzaJqQEFKAaE0WIaRQ+erSDqRAsd5KtQ5Wdkz8n4JcpT2wNSVXhJCCR0kWIaTQkGW8RzLLKs2gOmLFQzFapbYRtMonPIBO1tXQp1k7c4dNCCFaUZJFCCk0ZlzbB9WBKwao3RcSrewYgMBWwyGRGLSJBSGEmAQlWYSQQkOYHlQdtcpeokFYHSosbuc4YFUbmh4khBQ+lGQRQgqFgIu7tLZrW9gOKJIsr1LuGNCE9gslhBROeo2t//jjj3j06JGpYyGElFATz+1EnJzX3OQ5230eivpXcgZkApRgEUIKNb2SrBkzZuDGjRvifalUih07dpgsKEJIyfAmOQkfnd0JxhgYp3axIABlooWsZEu48QDWtqMpQkJI4abXdGHp0qXx6tUr8T5td0gIMYav/v4LgJYrBrPVxBISLUBR4f2X9pRgEUIKP72SrE6dOmH+/Pm4desWnJycAABbtmzB1atXdT6GKr4TQnKy/9/rALTsRyhcUph9DRayRrEIIaQo4Jgew1KxsbGYPn06QkNDERsbCyD30SyO4yCXy3PsU9Lpu4t3iWDiHdNJ4TL51G7IpDw4cbscpvJ51joGLttWOcKoVlCHQj6SRe9nQgqWif8N6vv7W681WRUqVMCOHTsQHR0NuVwOxhi2bdsGnud13ijBIoRk9/R1DPxO7kaqSvkF5WcAsi16R7Z1WMok65d2w80bNCGEGMigyn0bN25E27Z0VQ8hRH9p799j4a1zAJS1sORZSRWgsqmzyubOqlcTglMkWFRwlBBSVBhUJ2vs2LHi5//++y+ePXsGAKhWrRoaNGhgnMgIIcXG5BN7kMIYJJLso1dMZeNnTusyBMaAltYVMbF1F/MFTAghRmBwMdKQkBDMnDkTERERau3Vq1fHqlWr0Ldv3/zGRggpBsYc2yOut8q+2TMvByRSZEu01Ee1XDlLSrBIicYYg1wuR2ZmZkGHUnTIZEC1almfS6V6PczCwgJSqRScrp3p88igJOvIkSMYNGgQqlWrhsWLF6N+/foAgPv372PDhg0YOHAgDh8+DB8fH6MESQgpmj46tldrcqWgSKh4uWLRu7h4QVyHpXjQd10GmylaQgoXxhgSEhLw+vVrWuecVzwPrF+v+Dw6GsjDMgOpVIoKFSrAyckp38mWXlcXZtemTRvIZDJcuHAB9tlW7L979w7t27eHjY0Nrly5kq/giju6ulAFXY1V7Px4+TzCEl9BImFaryDMwsQ2sTaW8qdSRwdX+LXqaJ6AjYnez8QIoqOjkZCQAEdHRzg6OsLCwsJoIyzFnlwO3L+v+Lx+fb1GshhjyMzMRFJSEpKSkuDs7AwXFxetffX9/W3QSNadO3ewePFijQQLAOzt7eHn54evv/7akFMTQoqBUX/tA2MMErWfa9nXYGW1M6ZItFSnCb+o3xYN3KqaLWZCChO5XI7ExESUL18e5cqVK+hwih7VkT8bG72nCwGgVKlSsLa2xps3b1ChQgVI8/DY7AxKsmxsbBAXF6fzeFxcHGxsbAwOihBSdI04tE/nFKGQYGVPtBjjxASL44CgjgNgZWVlnoAJKYQyMjLAGNM6mEFMz97eHq9fv0ZGRka+kiyDroXu3Lkz1qxZo3U68Nq1a/jxxx/RtWtXg4MihBQ9b1JSMCxkv0aCpbqQXXVhu7bb4Iq1sLHrMEqwCFGi6cGCUaAL35cvX442bdqgffv2aNmyJerWrQsAePjwIcLCwlChQgUsW7bMKAESQgq/o//ew6bHD3QscFdQvYJQuK86ejW3eSfUKlvB5LESQoi5GDSSVb16ddy5cwdTp05FfHw8du/ejd27dyM+Ph7Tpk3D7du34e7ubuRQCSGFUUp6uphgZV9rJXzUNXLF84qpws3dh1KCRQgpdgwunVyhQgWsXr0aDx48QFpaGtLS0vDgwQOsWrUKFSrQD0tCSooJx4/oPMZ4YbSKgyLZyrrxPAeO47DVZ4i5QiWkRDp79iw4jsO+ffsKOhQApoln/vz5ek/xcRyH+fPnG+25c2JwMVJCSMm2MywM+15EQiqFWiV31SlAgAPjmdY/5xgPbOtFCRYhhtA3oQgNDTVxJCQnlGQRQvJkxcVLuBLzCpxEd5FRje1yeEXmJSRgVhywiRIsQgy2detWtftbtmzByZMnNdrr16+P+0K9KGJ2lGQRQvT2y5UwrQmW+uiV+sbPyiNi+x/desOWSrwQki+jR49Wu3/16lWcPHlSox1AvpOs1NRU2NnZ5escJRVtZ08I0cuL129wMjJKxwhWVhKVdZ/LtsAd2OTTjxIsQgoIz/NYtGgRKleuDBsbG3Tp0gX//fefWp9OnTqhUaNG+Pvvv9GxY0fY2dmJxcVlMhnmzZuHWrVqwdraGlWqVMHs2bMhk8nUznHy5Em0b98ezs7OcHBwQN26dbUWKNcnHgDYu3cvmjdvDltbW5QrVw6jR49GVFRUrq9X9v49ZqxahfKVKqFUqVLo27cvIiMj8/IlyzcaySKE5GrAnmCobn+jjfYNuhQP4HlgT/9BJoiMEKKvpUuXQiKRYNasWUhMTMTy5csxatQoXLt2Ta3f27dv8eGHH2L48OEYPXo0KlasCJ7n0bdvX1y8eBH+/v6oX78+7t69i9WrV+PRo0cIDg4GANy7dw+9e/dGkyZNsHDhQlhbW+O///7DpUuXDIpn06ZNGDduHFq0aIElS5bg1atXWLNmDS5duoSbN2/C2dlZ5+v96Pvvse3oUYwcMQJt27XDmTNn0KtXL6N8LfWV5yQrNTUVHTp0wMSJE/HJJ5+YIiZCSCGiSLCQYxV3xXFhNItlO8ZhebsOpg2SEJKr9PR03Lp1Syz2W7p0aUybNg3//PMPGjVqJPaLiYnB+vXr8fHHH4tt27Ztw6lTp3Du3Dm0b99ebG/UqBE++eQTXL58GW3btsXJkyfx/v17HD16NNftgHKLJyMjA19++SUaNWqE8+fPizvJtG/fHr1798bq1auxYMECree+ffs2th09ismDB+PnrVsBqRSffvopRo0ahTt37hj2BTRAnqcL7ezsEB4eTlVoCSkBnsfF69VPvf4Vl+0GuJcvb+JICSG5GTdunNpuCh06KP74efr0qVo/a2trjBs3Tq1t7969qF+/PurVq4c3b96It86dOwPIuopRGFkKCQkBz/P5iufGjRuIjY3F5MmT1bbq69WrF+rVq4e//vpL57mPHD0KAJg6bJha+/Tp03OMydgMWpPl4+OD48ePGzsWQkghM+3UOY1pwKzaV9nas62/EvrsHTDQ9IESQnJVtar6huulS5cGAMTHq/8x5ebmprG11ePHj3Hv3j2UL19e7VanTh0AQGxsLABg2LBhaNeuHT766CNUrFgRw4cPx549e7QmXLnF8+zZMwAQd5VRVa9ePfG4Ns+eP4dEIkHNypXV2rWdy5QMWpM1d+5cDBkyBGPGjMHHH3+M6tWrw9bWVqNfmTJl8h0gIaRgada/Uq99peuKQkquCClcdG10zLL949X2+5zneTRu3BirVq3Seo4qVaqIjz1//jxCQ0Px119/4dixY9i9ezc6d+6MEydOqMWgbzxFmUFJVsOGDQEA//77L3bs2KGzn1wuNywqQkiBy8jMhFyuXmgUEPYgVCZaKu08D4ABB4ZQckVIcVOzZk3cvn0bXbp0yXW5kEQiQZcuXdClSxesWrUKixcvxpw5cxAaGoquXbvq/ZzVqlUDoNgXWZiWFDx8+FA8rvWxVauC53k8iYxE3RYt1B5nTgYlWd9++y2tySKkGFt8+hIux7yBRG1BAQfGFFcYCokWmPrU4HD3qtpORwgp4oYOHYojR47g119/hb+/v9qxtLQ08DwPe3t7xMXFacxieXh4AIBGqYfceHp6okKFCli/fj3Gjx8Pa2trAMDRo0dx//59fPvttzof+6GPD77+5hv8uHs3fh4wQGz/4Ycf8hRDfhmUZJlqz5+UlBQEBgbi2rVrCAsLQ3x8PDZu3Ag/Pz+Nvvfv38eMGTNw8eJFWFlZoVevXli1ahXKZ1tgy/M8VqxYgV9++QXR0dGoU6cOAgICMGLECLOck5Ci5vdrt3Ap+i2kUuWIlTKDEqu3axnKZwwYU782BjZupHGMEFL0jRkzBnv27MEnn3yC0NBQtGvXDnK5HA8ePMCePXtw/PhxeHp6YuHChTh//jx69eqFatWqITY2FuvWrUPlypXVrkrUh6WlJZYtW4Zx48bBy8sLI0aMEEs4uLu7Y8aMGTof6+HhgRE9emDdvn1I9PVF23btcPr0aa11uEzJKHWyEhMT4eDgoHN+VV9v3rzBwoULUbVqVXzwwQc4e/as1n6RkZHo2LEjnJycsHjxYqSkpGDFihW4e/cuwsLC1BbszZkzB0uXLsXEiRPRokULhISEYOTIkeA4DsOHDzfpOQkpig48fp6tVINmogVkjV4JI1mUYBFSfEkkEgQHB2P16tXYsmUL/vzzT9jZ2aFGjRqYNm2auAC+b9++iIiIwB9//IE3b96gXLly8PLywoIFC+Dk5JTn5/Xz84OdnR2WLl2KL7/8Evb29hgwYACWLVuWY40sAPhj7lyUd3bG9uPHERwSgs6dO+Ovv/4S14+ZA8cMXGF248YNfPPNNzh//jzev3+PEydOoHPnznjz5g0mTJiAGTNmoFOnTnk6p0wmQ3x8PCpVqoQbN26gRYsWWkeyJk+ejE2bNuHBgwfi1QmnTp1Ct27dEBQUJA5lRkVFoXr16vD398fatWsBKBbUeXl5ITw8HBEREWJiaIpz5iYpKQlOTk5ITEyEo6Njnr5Wxc67d4CDg+LzlBTA3r5g4ymhhm89hGROKDrKsq3H0l6MlDHg+3Yt0LiKm/kCLezo/UzyKT09HeHh4ahevbpa+QKiJ7kcuHlT8XnTpkAeB4Fy+/rr+/vboBIOly9fRvv27fH48WOMHj1a7dLMcuXKITExEUFBQXk+r7W1NSpVqpRrv/3796N3795ql3927doVderUwZ49e8S2kJAQZGRkYPLkyWIbx3GYNGkSIiMjceXKFZOek5Ci5Jtj55CY499cHNTrYQE8r9g+hxIsQgjRZFCS9fXXX6N+/fr4999/sXjxYo3j3t7eGmX6jSUqKgqxsbHw9PTUONayZUvcFDJXADdv3oS9vT3q16+v0U84bqpzElKUbLp+BzdeJUPtckFwGjWvsvYkVNx4HggZ3s/s8RJCSFFgUJJ1/fp1jBs3DtbW1lqvMnRzc0NMTEy+g9MmOjoaAODi4qJxzMXFBXFxceIVDNHR0ahYsaJGjMJjX758abJzaiOTyZCUlKR2I6Qw2PXvcwCKTCp7UsXz6gVGeV4xEs/zHDb17VJQIRNCSKFnUJJlaWmZY7n8qKgoOAjrEYwsLS0NAMRLOVUJ86ZCn7S0NL37Gfuc2ixZsgROTk7izZyL7wjJibDHoGab0M6B57NuAIcvWzVBuVKm+XdOCCHFgUFJVuvWrbFv3z6tx969e4eNGzfCy8srX4HpIlSi1VZvIz09Xa2Pra2t3v2MfU5tAgICkJiYKN5evHihsy8h5nLsziPx86y9B7PvR6g+kvVtOw90qOVecEETQkgRYFAJhwULFsDLywu9evUSa0Pdvn0bT58+xYoVK/D69WvMnTvXqIEKhGk5YYpPVXR0NMqUKSOONLm4uCA0NFRZQJFT6wcArq6uJjunNtbW1lpHwQgpCA+iXuGzo38DHNO48IYxTiw6mtWm+NixUhm0qk5FRwkhJDcGjWS1atUKR44cwX///QdfX18AwOeffw5/f3/I5XIcOXIETZo0MWqgAjc3N5QvXx43btzQOBYWFiZWlgUUxchSU1Nx//59tX7ConyhrynOSUhh1vW3I/j0yN8ata6EKwjV29Q/BnRvZ+5wCSGkSDIoyQKAzp074+HDh/j777+xe/du7Ny5E2FhYXj06JHJpgoFgwYNwuHDh9Wm206fPo1Hjx5hyJAhYlu/fv1gaWmJdevWiW2MMaxfvx5ubm5o27atSc9JSGHD8zw6bzii3BYHGnWvshItTm16UCjXsK5X3io2E0JISZbviu9NmzZF06ZNjRELAGDt2rVISEgQr9I7dOgQIiMjAQBTpkyBk5MTvv76a+zduxfe3t6YNm2auB1P48aNMW7cOPFclStXxvTp0xEYGIiMjAy0aNECwcHBuHDhArZv365WNNQU5ySksHiblIwhuy6CMc0Nn6FchyVcXSgQpsOFUSy5HKhRrrR5AiaEkGLA4IrvMpkMv/76K44cOYKIiAgAgLu7O3r27ImPPvrI4Aq17u7uePbsmdZj4eHhcHd3BwDcu3cPM2fOVNtncOXKlahYsaLaY3iex7JlyxAUFITo6GjUrl0bAQEBGDVqlMb5TXHOnFDFdxVUIdtk4lPeYeD28wAATlnNXX0Ei4HLobK7MKLFcRxOjOtlpqiLOHo/k3yiiu/5VEgqvhuUZEVGRqJbt254+PAhXFxcUKtWLQDAf//9J26YfOrUKVSuXDmvpy5RKMlSQb+UTOLLPy/i2qtklcRKW5KlbFcuHtA2hcgYcGoCJVh6o/czySdKsvKpkCRZBq3J+vTTT/Hs2TPs2bMHUVFROHfuHM6dO4eoqCjs3r0bz58/x6effmrIqQkhRrLyzC1cjUnRkVRlx4EpS99pK9swpVkNU4dLCCHFjkFJ1unTpzFjxgwMHjxY49iQIUMwbdo0nD59Ot/BEUIM8zgmDgcfxmhJrnLKtjgwXpFsqd6O+/mgX9P6OTyOEELyTyaT4csvv4SrqytsbW3RqlUrnDx5MtfHHThwAMOGDUONGjVgZ2eHunXr4vNZs5CQnGyGqHNm0ML3UqVKoUKFCjqPV6pUCaVKlTI4KEJI/kw4EKZz9EpYIKDtuHB1IccBpz7qaarwCCFEg5+fH/bt24fp06ejdu3a2LRpE3r27InQ0FC0b6/7ymZ/f3+4urpi9OjRqFq1Ku7evYu169bhSHAw/rd1K3SXCDc9g5KscePGYdOmTZg4cSLs7OzUjqWkpGDjxo2YMGGCUQIkhOSNz7rjYokGgfp9DrqWYjIGrPmwORpXqaj1OCGEmEJYWBh27dqFwMBAzJo1CwDg6+uLRo0aYfbs2bh8+bLOx+7btw+dOnVSa2vetCnGjhuH7ceO4aM2bUwZeo70SrIOHDigdr9p06b466+/UK9ePYwdO1Zc+P748WNs2bIFZcqUMVkxUkJIzt5lq4GVPeFSUC06mrV7wcExneCQw9ZQhJDihcnS8P7wJmTevQJkZgAWlrBo3AZWvf3AWZvvZ8G+ffsglUrh7+8vttnY2GDChAn4+uuv8eLFC537/WZPsABgQP/+GDtuHO6Hh5sqZL3olWQNHjwYHJf116/q54sWLdLoHxkZiREjRmDo0KFGDJUQkhvvdcfFz7OSK/WRK9XkS/GRw4oejdHcna4GJqQkYbI0pK2aDv7lU7U9tDLO/gn5o1uwnfmD2RKtmzdvok6dOhpX6rVs2RIAcOvWLZ1JljYxMTEAgHLOzkaL0RB6JVmhoaGmjoMQkg//vXwD373/g0SqKDaqSRi5Ympb5HAc8OeojihdikoMEFLSvD+8SSPBAgAwHvzLcLw/vAnWgyaZJZbo6GhxH2FVQptQoFxfywIDIZVKMbhLF6PEZyi9kixTb5NDCDHcL2fvYOvtV+J9oXBo1sizau+sKu4cgBMTusDK0tJ8wRJCCo3Mu1c0EywB45F594rZkqy0tDRYW1trtAs1qtLS0vQ+144dO/D7H39gtq8valct2M3s872tDiGk4HRbcxIpqmuwGFSqNOhe4M7zwJmPu8LSgn4EEFJiZWbk77gR2draQiaTabSnp6eLx/Vx4cIFTJgwAT26d8eiSeZJEHNi8E/Yixcv4o8//sDTp08RHx+v8cOc4zjcvn073wESQrRrvfqklkKjikxLfT0WoLovIWOKEg2UYBFSwlnkMoqd23EjcnFxQVRUlEZ7dHQ0AMDV1TXXc9y+fRt9+/ZFo0aNsG/PHlg8fmz0OPPKoJ+yq1atwhdffAEbGxvUrVsXZcqUMXZchJAcDP7llM5jjAc4ifpVhYoNoBV4OXBpag9Th0gIKeQsGrdBxtk/IW73oIqTwKKx+UofeHh4IDQ0FElJSWqL369duyYez8mTJ0/g4+ODChUq4MiRI3AQtrUqYAYlWYGBgWjXrh0OHToEJycnY8dECMnB64QkvEhTLHDPXgsLUK7H4gGAiXs6MKa4K4xiEUKIVW8/yB/dAv8yXD3R4iSQuFaHVW8/s8UyePBgrFixAhs2bBDrZMlkMmzcuBGtWrUSryx8/vw5UlNTUa9ePfGxMTEx6N69OyQSCY4fP47y5csr9i4sBAxKslJTUzFq1ChKsAgxI1lGBjqsOQ/VzZzVZV/srr4fofDx0tTupg+WEFLocda2sJ35Q6Gok9WqVSsMGTIEAQEBiI2NRa1atbB582ZERETg999/F/v5+vri3LlzakuUfHx88PTpU8yePRsXL17ExYsXFQtPIyJQsWxZdGva1GyvIzuDkixvb2/cvXvX2LEQQnRouSJrL1BOkn0dlqqcq7kfmqB7awpCSMnDWdvCetAks11FmJMtW7Zg7ty52Lp1K+Lj49GkSRMcPnwYHTt2zPFxwvrv5cuXaxzzatYM3T75xCTx6oNjun4i5+DFixfo3r07JkyYgPHjx9OaLAMlJSXByckJiYmJGgXYSpx37wBhDj0lBbCnuk0C1QRLGMVSJFlMy8J3qPUVNK9ki5+GdTBdkEQdvZ9JPqWnpyM8PBzVq1cXyxiQPJDLgZs3FZ83bQpIpXl6eG5ff31/fxs0klWlShV8/PHHmDVrFr788kvY2NhAmu0FcByHxMREQ05PCFEKvvks1z7ats1R3ej5uH8HlLKlH9KEEGJuBiVZ3377LRYtWgQ3Nzd4enrS2ixCTGTx6f9yOJrz1GCfmvaY07etaQIjhBCSK4OSrPXr16NXr14IDg6GRPseHoQQk9CsgwVALdkSriCkBIsQQgqWQRnS+/fv0atXL0qwCDEDLduKaWnnoBjZUiRY5z6jrbAIIaSgGZQl9e7dGxcuXDB2LISQbPw8tVU5VpRmYEzzxnHA1RldYU37ERJCSIEzKMmaN28e/v33X0yePBl///03Xr9+jbi4OI0bISR//n6WJCZQ6jiAcWA8B17OQZ7JQZ4pwdUZXQsiTEIIIVoYtCarbt26AIBbt24hKChIZz95Iam4SkhRFPEmCbejkgEpB9UcK3uVd6GaO6iSOyGEFCoGX13I0d4chJjU0A1hwjp3AIC26wiFUg0Aw6R2VcwWGyGEkNwZlGTNnz/fyGEQQrLTTKqEKwm195/QrrYpwyGEEJJHBiVZhBDTYoypJ1lM+T/tVUe1D3MRQggpUAYlWQsXLsy1D8dxmDt3riGnJ6TEO/lPBCSMgVdbgCX+L1sb8FGrSuYKjRBCiJ6MPl3IcYoq1JRkEWKYYzfD8e2hx4CU0xzByj5ixRjAAZ94NzRzlIQQQnJjUAkHnuc1bpmZmXjy5AlmzJgBT09PxMbGGjtWQoq9NgtOYN6hx5oHtC3EYgzgGYY2oVEsQkjRJ5PJ8OWXX8LV1RW2trZo1aoVTp48mefzdOvWDZyFBT5bvtwEUeaN0Uq2SyQSVK9eHStWrEDt2rUxZcoUY52akBKhzYIT4IU7ypErCaAYvWLQUn1UcXx2z0YFES4hhBiVn58fVq1ahVGjRmHNmjWQSqXo2bMnLl68qPc5Dhw4gCtXrpgwyrwxyb44HTt2xJEjR0xxakKKnTk7rqDNghOKOxwAjlMreSURbiz7jdGCd0JIsRAWFoZdu3ZhyZIlCAwMhL+/P86cOYNq1aph9uzZep0jPT0dn3/+Ob788ksTR6s/kyRZN27coH0NCdHDysN3ceZxsvaDPHTXa1C213Omf2eEEMMx/j1YXChY1G9gkUGKj3GhYPx7s8axb98+SKVS+Pv7i202NjaYMGECrly5ghcvXuR6juXLl4PnecyaNcuUoeaJQQvft2zZorU9ISEB58+fx4EDB/DRRx/lKzBCijue57HvxkvNsgxKHJSbQUu0rcdS3LZ81sWUIRJCijHGvwdidgIZr9UPJP8PSH8OVmkEOImVWWK5efMm6tSpA0dHR7X2li1bAlDsMFOliu6Cy8+fP8fSpUvxxx9/wNbW1qSx5oVBSZafn5/OY+XKlcNXX32Fb7/91tCYCCkR2i04qbkVTrarCTkA4NVnBTnlTtBX5lCCRQjJh4RLmgkWAIABGW8Ux8t4myWU6OhouLi4aLQLbS9fvszx8Z9//jmaNm2K4cOHmyQ+QxmUZIWHh2u0cRyH0qVLo1SpUvkOipDiLC45FX2WnxfXX2nF1AuPcmrtwKyu1WhKnhCSP2lPcjjIlMfNk2SlpaXB2tpao93GxkY8rktoaCj279+Pa9eumSw+QxmUZFWrVs3YcRBS7Gw8fQ+/n9WxjkBHgiUBwIvDVtqnCUNnd4Sd8gcPIYQYjMnzd9yIbG1tIZPJNNrT09PF49pkZmZi6tSpGDNmDFq0aGHSGA1B2+oQYkRyuRxe83Ou6yKkThIo1rZnH7USxqfEiwcZAwfAiuNwfl53Y4dMCCmpOGn+jhuRi4sLoqKiNNqjo6MBAK6urloft2XLFjx8+BBBQUGIiIhQO5acmoqIly9RoW5d2BXQLJveSVaTJk3ydGKO43D79u08B0RIUaVIsE4oMiNd04DZMShXuGvuS8hBuf6KAcdmtYNTKQcjR0wIKdFsayoWuWutBcMpjpuJh4cHQkNDkZSUpLb4XZgC9PDw0Pq458+fIyMjA+3atdM4tuWvv7Dlr7/w5/796D9woEnizo3eSVaZMmXA6fGLIyYmBg8fPtSrLyHFBWMMXnNPKIah8vDe1zo9KG6hk/WDjxIsQojRObcD0p8rFrmrX14DWJZTHDeTwYMHY8WKFdiwYYNYgkEmk2Hjxo1o1aqVeGXh8+fPkZqainr16gEAhg8frjUBGzBgAHq2a4eJ/fujlfIKxYKgd5J19uzZHI/HxMRg2bJlCAoKglQqxZgxY/IbW46xeHtrX4x35coVtG7dWrx/+fJlzJ49G//73//g6OiIoUOHYvHixXBwUP+lJZPJ8O2332Lr1q2Ij49HkyZN8P3336Nbt24az6HvOUnJwPM8On1zPM8JlkCYHtRItpQV3S8t6JH/IAkhJBtOYgVWaYTiKsK0J4o1WJxUMYLl3M5s5RsAoFWrVhgyZAgCAgIQGxuLWrVqYfPmzYiIiMDvv/8u9vP19cW5c+fAhFqB9eqJCVd21V1d0b9TJ0DLVYvmku81Wa9evcLSpUuxYcMGZGRkYPTo0ZgzZw5q1jT9MOPUqVM1FrrVqlVL/PzWrVvo0qUL6tevj1WrViEyMhIrVqzA48ePcfToUbXH+fn5Yd++fZg+fTpq166NTZs2oWfPnggNDUX79u0NOicpGTp9czxP/YXZQbWNn6FSGVi5hY69hMOJ+ZRgEUJMh5NYKcs0mOcqwpxs2bIFc+fOVRvsOHz4MDp27FjQoRnM4CRLGLlSTa6++eYb1KhRw5jx5ahDhw4YPHiwzuNff/01SpcujbNnz4pzvO7u7pg4cSJOnDiB7t0Vi4iFcv6BgYHiMKWvry8aNWqE2bNn4/Lly3k+JykZfL49qnU9lV6Y+D/NKUKOEixCSMliY2ODwMBABAYG6uyT26yagGVmAjdvGikyw+W50E5MTAymT5+OmjVr4ueff8bw4cPx8OFD/PHHH2ZNsATJycnIzMzUaE9KSsLJkycxevRotUV0vr6+cHBwwJ49e8Q2fcv55+WcpPj7dG0oUjNUEixhE2c9cMqb5ubPgE/jcjRFSAghxYDeI1nR0dFYunQpfv31V2RmZsLX1xdz5sxB9erVTRlfjsaNG4eUlBRIpVJ06NABgYGB8PT0BADcvXsXmZmZ4n2BlZUVPDw8cFMlw9W3nH9ezkmKr9M3IrDjzAM8eSsHJCojWMKVgjnRWWQU+LBRGcwZVnALNAkhhBiX3klWzZo1IZPJ4OHhga+//hrVq1dHfHw84uPjdT6mWbNmRgkyOysrKwwaNAg9e/ZEuXLl8O+//2LFihXo0KEDLl++jKZNm4q1NXSV6b9w4YJ4X99y/nk5pzYymUyt2FpSUlJuL5UUAqO+P4LoJPURKh7QSKgkAHhhr0Ft04fKBKuqAxCVonj4stFN0Kqu9vovhBBCija9kyyh6urNmzcxdOjQHPsyxsBxHORy01SLbdu2Ldq2bSve79u3LwYPHowmTZogICAAx44dE0vw6yrTr1qiX99y/nk5pzZLlizBggULcnt5pJCIS3yHwYvOarSLCZauiu26NnXmgYuLfYwbJCGEkEJL7yRr48aNpowj32rVqoV+/frhwIEDkMvlYgl+XWX6VUv061vOPy/n1CYgIAAzZ84U7yclJeW4qzgpOMfDIrBs373cO+q6SpDP3o9h+8z2IIQQUnLonWSNHTvWlHEYRZUqVfD+/Xu8e/dOnNITpvhURUdHq5Xo17ecf17OqY21tbXWUTBSuGw+8S82nwrXfdWgyiiWrq1xILQpzehVC1XKq6/5I4QQUrzl+erCwuzp06ewsbGBg4MDGjVqBAsLC9y4cUOtz/v373Hr1i21CrEeHh549OiRxhqp7OX883JOUnRtPhWu+ETPsgwSjSsEs64UBFMcH9C+jqnCJYQQUkgVySTr9evXGm23b9/GwYMH0b17d0gkEjg5OaFr167Ytm0bkpOTxX5bt25FSkoKhgwZIrYNHjwYcrkcGzZsENu0lfPPyzlJ0dT5i8O5l2HQUqpBAtVkC2K1dgmADZ+1zn4GQgghJUC+K74XhGHDhsHW1hZt27ZFhQoV8O+//2LDhg2ws7PD0qVLxX6LFi1C27Zt4eXlBX9/f0RGRmLlypXo3r07fHyyFiDrW84/L+ckRU/P2Yf1K8Mg0DJFmP2vljI2QJ3KZYwRHiGEkCKmSI5k9e/fH2/evMGqVaswefJk7N69GwMHDsSNGzdQv359sV+zZs1w6tQp2NraYsaMGdiwYQMmTJiAffv2aZxzy5YtmD59OrZu3YqpU6ciIyNDazn/vJyTFB2ZmXLIsi9W10ECZO2lKkwNZv8cwNDWLjgwv6cxwySEEFKEcIzpWaKaGF1SUhKcnJyQmJioUQi1xHn3DhA22E5JAeztzfr045afwfNX78A4Tmd5Bg2MgVftJ+FQpbQlvh7RHPWr0uhViVbA72dS9KWnpyM8PBzVq1cXywmRPJDLs7bVadoUkErz9PDcvv76/v4uktOFhBhLYnIaVm6/gucx7wBO9+bNGpRThWeX9zJTpIQQQooaSrJIiXT5zgvM25htGyRtJRh0lWVgwJlASrAIIYToViTXZBFiiPvhb9Bj2kF0m3YwK8HiuKybkvaNm7PKMnAM2PplhwJ4BYQQUnzJZDJ8+eWXcHV1ha2tLVq1aoWTJ0/q/fjdu3ejTZs2sLe3h3PZsmg7fjzOXL9uwohzR0kWKRG2/HUP03+4rN6YvUq76iHhxrLfGOq52cOtvJOpQyaEkBLFz88Pq1atwqhRo7BmzRpIpVL07NkTFy9ezPWx8+fPx4gRI1ClShWsWrUK3y9ciCa1ayNKS8knc6LpQlIibD/xJOuOBDo2cFb+T9daLOVU4c8zvI0dHiGElGhhYWHYtWsXAgMDMWvWLACAr68vGjVqhNmzZ+Py5cs6H3v16lUsXLgQK1euxIwZMxSNcjmgssdxQaGRLFLsLd18PfcCo1ApzZCtFIPqVGHwgq6mCpMQQsyOZxlIfH8ZsWk78Sp1G2LTdiLx/WXwLMOscezbtw9SqRT+/v5im42NDSZMmIArV67gxYsXOh/7ww8/oFKlSpg2bRoYY0hJSTFHyHqhJIsUa8NnhyD0xku9+6tVbueZ4qbcGufrEQ1RyiHnTcAJIaSo4FkG3qaHIDXzLuQsCTzeQc6SkJr5D96mh5g10bp58ybq1KmjUQ6hZcuWAIBbt27pfOzp06fRokUL/PjjjyhfvjxKlSoFl8qVsXbPHlOGrBeaLiTFUrosAwNmHdF+kIcia8qhREP2vz7WTGmFBtUrGC0+QggpaMkZ15HJ3mo5wpDJ4pCccR1OVuaZcouOjoaLi4tGu9D28qX2P5bj4+Px5s0bXLp0CWfOnMG8efNQtWpVbPzjD0wJDISlhQU+btrUpLHnhJIsUixpJFjZFrnz+qy/Uh47uaqPSWIkhJCCJJM/y+EoUx43T5KVlpYGa2trjXahEGhaWprWxwlTg2/fvsWuXbswbNgwAMDgAQPQuG5dfP/77/j4u+9MFHXuKMkixUrfKcHI4KFetV1LHiVRzgQq5ga14Dgs+sgTLRto/mVFCCHFAWPyfB03JltbW8hkMo329PR08biuxwGApaUlBg8eLLZLJBIM69YN8zZswPPnz1G1enUTRJ07SrJIsdHz02DtB3SMWkkAxdRhNlu/7YwKZR2MGxwhhBQyHCfN2odV13EzcXFxQVRUlEZ7dHQ0AMDV1VXr48qUKQMbGxs4OztDmm3rnAplFNubxcfHF1iSRQvfSbFw6WakUc5T2g6UYBFCSgRraTVoHeoHAHDK4+bh4eGBR48eISkpSa392rVr4nFtJBIJPDw88Pr1a7x//17t2Etljazy5csbP2A9UZJFioVFv93QeUxnaQaBStuuJX2NHhshhBRGpSxbwIIrA81Ei4MFVwalLFuYLZbBgwdDLpdjw4YNYptMJsPGjRvRqlUrVKlSBQDw/PlzPHjwQO2xw4YNg1wux+bNm8W29PR0bD92DA2qV9c5CmYONF1Iih0OmiPgWYvdoXmU4zCuVy0M797A5LERQkhhIeEsUdamH5IzrkMmfwbG5OA4Kayl1VDKsgUknKXZYmnVqhWGDBmCgIAAxMbGolatWti8eTMiIiLw+++/i/18fX1x7tw5MJU/jj/++GP89ttv+PTTT/Ho0SNUrVoVW7dswbOYGBxaudJsr0EbSrJIkbf/xAPNzZy1rMOSqB2DWGD0h1ntULd6OfMESwghhYiEs1SWaSj46uhbtmzB3LlzsXXrVsTHx6NJkyY4fPgwOnbsmOPjbG1tcebMGcyePRt//PEH3r17B48PPsBfq1ejR5s2ZopeO0qySJG38c/7ys+0lGTInnyptjPFqBclWIQQUvBsbGwQGBiIwMBAnX3Onj2rtb1ChQrYtGlTVoNcDty8adwADUBJFinSlv12VWs7BwBMGLTStQ6Lw5rZ7U0WGyGEkJKNkixS5PA8j/6fBCs+5wBIOJ0FRtWTLai0c9i1zAeODjbmCJkQQkgJRFcXkiKFMSYmWCqNuT6OU70xht5tK1OCRQghxKRoJIsUKd+tvaTZqBy5UhvNUmkHoJ6IMWDyKE9ThUgIIYQAoJEsUsTcuBur3iDUv1LKqomFrLpYykXu4BkkDPhrXX9zhUsIIaQEo5EsUuxolGoAxETs8C8DzB0OIYSQEopGskiRJu4/qKuaO5DVnsFj8U9nzRIXIYQQQiNZpEhpXKcM7j6KU2uTAOB5ZF1KCCjWYwnJlXKqUMpxuHbrDQaM3ys+tkldRyz4socZIieEEFLS0EgWKVIWzeqktV0CQMIACQ/FyBYvrMNStqv05VU+v/MwCQPG78X0b4+YKmRCCCElFCVZpMgJCVKuq9IxRSgmXEJyxVQKZXEcwHEadbOeRb7Dt4FnTBc0IYSQEoeSLFLkcByHkKAB4ISrCHmme02WyvY5as1aznv33zfGD5YQQkiJRUkWKZI4ZQ2srAKj0Ey4dCRYORngtwcjJu4xfsCEEEJKHEqySJG14msvtfuqCZd4M+C87zOAYRMo0SKEEHOSyWT48ssv4erqCltbW7Rq1QonT57U67GnTp2Ct7c3ypUrB2dnZ7Rs3RpbjxT8WltKskiRVbtGOSz5QrnBM8thylCVsk9ub/xMORD7OsUocRJCCMmdn58fVq1ahVGjRmHNmjWQSqXo2bMnLl68mOPjDh48iO7du+P9+/eYP38+Fi1aBFtbW/jOm4fVO3aYKXrtOMb02PiNmERSUhKcnJyQmJgIR0fHgg6nYL17Bzg4KD5PSQHs7fP08H4qZRnUttPRtrWOriSLKSrCi32Vi+dVVSpvg6mT2qB27Qp5io+UMPl8PxOSnp6O8PBwVK9eHTY2xX+f1bCwMLRq1QqBgYGYNWsWAMXXoFGjRqhQoQIuX76s87Hdu3fHvXv38PTpU1hbWwMAMmUy1KtVC/a2trh9/z4gleYpnty+/vr+/qY6WaRY6N+9Fg4efyzeF8s0MKZWM0vnCJbqFYiAep0t4TiAmNg0fD3/DDgAA/rWw4hhHsZ5AYQQUgDS5Rn/b+/uo6Ku8j+Av+eBhxFBFEIeSxQoUxMfwOxsm5pZlGabaGlCtabW77C2qWDm0yrZiraaa26pS5q4mms/+Vm57p5ay5N6xNp0SyVLU0HUEFQehBlk5vP7A5gYGBBm5vtlwPfrnDnA/d7v9977YQ7z4X7v3MGuM9/hv8UFqLaYodfq0D8gDGMj+8Fb56FaPz788EPodDpMmzbNWubt7Y0pU6bgtddeQ35+PiIiIuyeW1paiq5du1oTLADQ6/UI9PdXuts3xduF1CE8//QAm88s1NY9gF++NnVy3axVw7L6ard+qHnUNJP90ffI2nrE5WMhIlKD0XwDy498hn8XnMRlYzmuVlXisrEcewtOYvmRz2A031CtL0eOHEFMTEyjWaH4+HgAwNGjR5s8d9iwYTh+/DgWLFiAU6dO4fTp00h//XV8nZuLtKQkJbt9U0yyqMMYMiDEukeWNeFq9G7DBrNT9hIs6/EmGqqXaH28+yR4x52I2qNdZ77D+evXGv2pswAouH4Nu858p1pfLl68iJCQkEbldWUXLlxo8twFCxZgwoQJWLp0KaKjoxEVFYVly5fjfzMy8OSIEYr1uSWYZFG7JiL46KPjSH52O745dN5mYbv1UT/pskm8YD/BEqnZKb6FfTj634suGg0RkXr+W1zQ5P+SltrjaqmsrLS53Venbj1UZWVlk+d6eXkhJiYGiYmJ2LZtG7Zs2YLBgwZh8sKFOPSdeomiPVyTRYoSERw4cBaHc86ha9dOGPVwFMLCurX4/IMHz2DXzuO4cqUSvr4euFZ2AxWV1XZv52kBWExmiKfW7jHbjlk72LjRViRYAHC+oBQDYkNbcQYRUdurtpibPy6WZo+7ksFggMlkalRuNBqtx5uSkpKCQ4cO4ZtvvoFWW/PXe8K4cehz5514+U9/Qk5ysjKdbgEmWeSwygoT/vrOYXz37QWYzRb4+XqiZ3Qg+t4Tgj73hGDzpv/gm//YTvF++q9Tdq/lVW3Extrvn0/eDpPe9t0cFgBlFbXrA+rWRtmh12iAG4IbdVmUXlO7YVYTO2a1MqGy586YQCevQESkPr22+Xfc6TXq3ewKCQlBQUHjmbOLF2vuFISG2v9HtqqqCpmZmUhLS7MmWADg4eGBhKFD8faOHaiqqoJnM0makphkOchkMmHhwoXIysrC1atXcc899+D111/HQw891GZ9MpvNePapD2p+qH1XnaenFu9tnejSdkQEr83ejfxzJTbll41GXL58HjkHz8Ni3RnUke1A7WjltazviakWmAGg3t8SC2B/dqulame/6noTE80ki4jan/4BYdhbcBL25qu0tcfVEhsbi88//xylpaU2i99zcnKsx+0pLi5GdXU1zObGs3I3qqthsVjsHlML12Q5yNFN05RSVnYdz07Y9svtr9qEpMpkxuTELS5t6w9z/9UowaqvJomByxIsZ5eV6wBoLPXWYAmgtbcgvqkF8jadqdtrq+bLvFcfsF+PiMjNjY3shzAf/0aJgBZAmI8/xkb2U60viYmJMJvNWL9+vbXMZDJh48aNGDJkiHX7hry8PHz//ffWOkFBQfD390d2djaqqqqs5eXl5fj4yy9xV48ezd5qVBpnshxw+PBhfPDBBzabpiUnJ6Nv375IS0trdtM0pbz0bLb9xKZ2v6fJiX/Dlg+fcbqdyooqnD5V7PR1WsMl790TQIMGtw2lUZUGBXY+l8dSO4ul0SDj9VGIjGz5+jIiInfirfNA2oCRv+yTJRboNdo22SdryJAhGD9+PObOnYvCwkJERUXh/fffx9mzZ5GZmWmtl5ycjH379lnf1a3T6TB79mzMnz8f9957L5KTk2E2m5GZmYnzhYXYsmSJamOwh0mWA5zZNE0JFoul+ZmjhhtrOmHf3tM3r+TK24QuokVdfmQ701ef3R5bbGeu6q41aeI9TLCIqN3z1nngqaiBeCpqYFt3BZs3b8aCBQtsluF88skn+PWvf93sefPmzUNkZCRWr16NxYsXw2Qy4Z5+/fBhRgbGtfEWDkyyHNCSTdPUTLJmp2xTra3y8qqbV6rdENRViZYWsLtmwKHrWJOlFiaddrZ4MBh0GP1Ybxf0iIiI6nh7e2PFihVYsWJFk3W++OILu+WTJk3CpEmTfikwm4Ejbb9ZNNdkOcDRTdNMJhNKS0ttHq5QeEm9zTDj7r39pnUUmcOqS9ycVH/vrIYPNHho7SRYUVHdkPnXRGi17jVTR0RE7oczWQ5wdNO0P/7xj1i8eLHL+/Orkb7Y/+8yl1/Xnjt6dIVer0V1ddNzSxoAYsEvn67cghktk94bkyb8rcnjjW73OaNefx5/PAYVFTfwww/FKC6+jspKMyyWmiq33+6H3798P0JC/CAi0LjZLVByYz4+LrtFT0QO0OmAwYPbuhdMshzh6KZpc+fOxcyZM60/l5aWuuS24ov/Mxb7P8uq+cFeIiBS/z6Z095cMwa/f2lXs3W0ACwW1E5rtaDtFiQw2tpL1aV3QUEGlJUYYTLd/PqW2gskTY7FI4/cCV0rP5GdCRYREbUWkywHOLppmpeXl90ZMJewoGavgoZroWq3I3BlkhB4W2dk/u0pLFvyb/x4sqjJenVJUf0cy+78l67lfdNogIkT+mHM2D7Q6ni3m4iI3BeTLAc4ummakrb8XxKSnsiCaGC7kMgi0ADIyp7s0va8vPRYtPThZuuUllbgfF4J8s5dRWHhdZReq0RZmQkmYzW6dfPBrx7oiQGDwzhLREREHZJGhAsHWisnJwf33nuvzT5ZJpMJffv2RUBAAA4dOtSi65SWlqJLly4oKSlp9E5FR126dA2pL31cM3ukBd7dnAifzm23ERsREbWe0WjEmTNnEBkZaV3vS+q5Wfxb+vrNmSwHtHTTtLYQHOyPrOykNu0DERG5BudB2oar4s4ky0GObppGRER0Mx4eHtBoNLh+/XqbfizMrer69evQaDTw8HBu13veLmxDStwuJCKijuHixYu4du0a/Pz84OfnB71ezzWsChIRVFdXW/ex9Pf3t7snJsDbhURERO1acHAwDAYDCgsLXbZ5Nd2cTqdDSEgIunTp4vS1mGQRERG5IY1GA39/f3Tp0gVmsxnV1dVt3aUOT6/XQ6fTuWzGkEkWERGRG9NoNNDr9dDr+ZLd3nA3RyIiIiIFMMkiIiIiUgCTLCIiIiIFMMkiIiIiUgCTLCIiIiIF8K0KbahuH1juf0JERNR+1L1u32w/dyZZbaisrAwAEBER0cY9ISIiotYqKytrdtNSfqxOG7JYLLhw4QJ8fX1d+lEJpaWliIiIQH5+Pj+uR2GMtToYZ3UwzupgnNWhZJxFBGVlZQgNDYVW2/TKK85ktSGtVovw8HDFrl/3eVekPMZaHYyzOhhndTDO6lAqzi352B0ufCciIiJSAJMsIiIiIgUwyeqAvLy8sGjRInh5ebV1Vzo8xlodjLM6GGd1MM7qcIc4c+E7ERERkQI4k0VERESkACZZRERERApgkkVERESkACZZRERERApgkuWmTCYT5syZg9DQUBgMBgwZMgSffvppi84tKCjAhAkT4O/vDz8/P4wdOxY//fST3bqZmZno3bs3vL29ER0djTVr1rhyGG5P6Tjn5+dj8eLFiI+PR9euXREYGIhhw4bhs88+U2I4bk2t53Sd/fv3Q6PRQKPRoKioyBVDaBfUivPPP/+M6dOnIywsDN7e3ujRowemTJniyqG4NTXiXFJSgrS0NERHR8NgMOCOO+7AlClTkJeX5+rhuC1H43zy5Em88soruO++++Dt7Q2NRoOzZ882Wf+jjz7CwIED4e3tjdtvvx2LFi1CdXW18wMQcktPP/206PV6mT17tqxbt06GDh0qer1evvzyy2bPKysrk+joaAkKCpKMjAxZuXKlRERESHh4uBQVFdnUfffddwWAjBs3TtavXy9JSUkCQJYtW6bk0NyK0nFes2aNGAwGmThxorz99tvy1ltvycCBAwWAvPfee0oPz62o8ZyuYzabJTY2Vnx8fASAXL58WYkhuSU14pyXlycRERESEREhS5YskczMTElPT5cxY8YoOTS3onSczWazxMXFiY+Pj6SmpsqGDRtkzpw54uvrK2FhYVJaWqr0EN2Co3HeuHGjaLVa6du3r8TGxgoAOXPmjN26//jHP0Sj0cjw4cNl/fr18rvf/U60Wq28+OKLTvefSZYbysnJEQCyYsUKa1llZaX06tVLhg4d2uy5GRkZAkAOHz5sLcvNzRWdTidz5861llVUVEhAQIA89thjNuc/88wz4uPjI1euXHHRaNyXGnE+duxYoxd4o9Eod911l4SHh7toJO5PjVjX984770hAQIC8/PLLt1SSpVacExISJDIysskkt6NTI84HDhwQAPL222/bnP/ee+8JANm5c6eLRuO+nIlzcXGxNRFdsWJFs0nW3XffLf3795cbN25Yy+bNmycajUZyc3OdGgOTLDeUmpoqOp1OSkpKbMrfeOMNASB5eXlNnhsXFydxcXGNykeNGiW9evWy/rx7924BILt377apd/DgQQEgWVlZTo7C/akR56bMnDlTANwy/42qGevi4mIJCAiQtWvXyqJFi26pJEuNOOfm5goA+ctf/iIiNS96VVVVLhpB+6BGnPfs2SMAZMeOHTb16sr37Nnj5CjcnzNxrq+5JOv48eMCQNauXWtTXlBQIAAkPT3d4f6LiHBNlhs6cuQIYmJiGn2gZXx8PADg6NGjds+zWCz49ttvMXjw4EbH4uPjcfr0aZSVlVnbANCo7qBBg6DVaq3HOzI14tyUS5cuoVOnTujUqZNjnW9n1Iz1ggULEBwcjOnTp7um8+2IGnGuW0/YvXt3PPjggzAYDDAYDEhISGh2zUtHokacBw8eDB8fHyxYsAB79+5FQUEB9u3bh7S0NMTFxWHkyJGuHZQbcjTOrW0DaPxaGBoaivDwcKdfC5lkuaGLFy8iJCSkUXld2YULF+yed+XKFZhMphade/HiReh0OgQFBdnU8/T0REBAQJNtdCRqxNmeU6dOYefOnRg3bhx0Op0jXW931Ir1t99+i3Xr1mHlypW3TGzrUyPOP/74IwBg2rRp8PT0xPbt27Fs2TLs378fI0eOREVFhUvG4s7UiHNgYCC2b9+OkpISPPjggwgPD8ewYcMQGhqKvXv3Qq/Xu2o4bsvROLe2jfrXbNiOs210/N9SO1RZWWn3s5a8vb2tx5s6D0CLzq2srISnp6fd63h7ezfZRkeiRpwbqqiowPjx42EwGLBs2TKH+t0eqRXrGTNmICEhAaNGjXK6z+2RGnEuLy8HAAQHB2P37t3Qamv+Vw8PD8fEiROxdetWvPDCC06OxL2p9Xy+7bbbMGDAAKSkpKBPnz44evQoli9fjueffx47duxwehzuztE4t7YNoOnfSWlpqVPXZ5LlhgwGA0wmU6Nyo9FoPd7UeQBadK7BYEBVVZXd6xiNxibb6EjUiHN9ZrMZTz/9NE6cOIE9e/YgNDTU4b63N2rEevv27Th48CCOHTvmkj63R2r97QCACRMmWBMsABg/fjySkpJw8ODBDp9kqRHnn376CcOHD8fmzZsxbtw4AMDYsWPRo0cPPPfcc9izZw8SEhKcH4wbczTOrW0DaPp34mwbvF3ohkJCQqxTmPXVlTX14tytWzd4eXm16NyQkBCYzWYUFhba1KuqqkJxcfEtkQCoEef6pk6dik8++QSbNm3CiBEjnOl6u6NGrFNTUzF+/Hh4enri7NmzOHv2LK5duwagZr+yW+EWuBpxrvvavXt3m3o6nQ4BAQG4evWq4wNoJ9SI86ZNm2A0GjF69Gibeo8//jgA4MCBA44PoJ1wNM6tbaP+NRu242wbTLLcUGxsLH744YdG05Q5OTnW4/ZotVr069cPX3/9daNjOTk56NmzJ3x9fW2u0bDu119/DYvF0mQbHYkaca6TmpqKjRs3YtWqVZg4caJrBtCOqBHr/Px8bN26FZGRkdbH6tWrAQADBw7Eo48+6sIRuSc14jxo0CAANRtq1ldVVYWioiLcdtttzg7D7akR559//hkiArPZbFPvxo0bAOCajTLdnKNxbm0bQOPXwgsXLuD8+fPOt+HUexNJEYcOHWq0N4jRaJSoqCgZMmSItezcuXON9vBYtmyZAJCvvvrKWvb999+LTqeTOXPmWMsqKiqkW7duMnr0aJvzJ0+eLJ06dZLi4mJXD8vtqBFnEZHly5cLAHnttdcUGon7UyPW2dnZjR5PPfWUAJDNmzfL3r17FRyhe1AjzkajUYKCgqRnz55SWVlpLV+3bp0AkL///e9KDM2tqBHnN998UwDIxo0bbc5/6623BIB88MEHLh6V+3EmzvXdbJ+su+66S/r37y/V1dXWsvnz54tGo5ETJ044NQYmWW5q/PjxotfrJTU1VdatWyf33Xef6PV62bdvn7XOAw88IA3z5NLSUunVq5cEBQXJ8uXLZdWqVRIRESGhoaFSWFhoU3ft2rUCQBITE2XDhg2SnJwsAGTp0qWqjNEdKB3nnTt3CgCJjo6WrKysRo9Lly6pNta2psZzuqFbbZ8sEXXi/P777wsAiYuLkz//+c8ye/Zs8fDwkPvvv9/mhaojUzrORUVFEhwcLJ6enjJjxgxZt26dTJ8+XXQ6nfTp00dMJpNqY21Ljsb52rVrkp6eLunp6fLII48IAJk1a5akp6fLmjVrbOp+/PHHotFoZMSIEbJ+/XqZMWOGaLVamTp1qtP9Z5LlpiorK2X27NkSHBwsXl5eEhcXJ//85z9t6th7YomI5OfnS2Jiovj5+Unnzp1l9OjR8uOPP9ptZ/369XLnnXeKp6en9OrVS1atWiUWi0WRMbkjpeNc9yLf1OPzzz9XcnhuRa3ndH23YpKlVpy3bdsm/fv3Fy8vL+nevbukpKTcMpvriqgT5/Pnz8tvf/tbiYyMFE9PTwkJCZGpU6fy+dyCOJ85c6bJv7t33HFHo3ays7MlNjZWvLy8JDw8XObPn++STXY1IiLO3XAkIiIiooa48J2IiIhIAUyyiIiIiBTAJIuIiIhIAUyyiIiIiBTAJIuIiIhIAUyyiIiIiBTAJIuIiIhIAUyyiIiIiBTAJIuIiIhIAUyyiIiasWnTJmg0GruPV199FQDQo0cPa5lWq4W/vz/69euHadOmIScnx+51G17Lz88PDzzwAHbv3q3m8IhIQfq27gARUXuwZMkSREZG2pT17dvX+n1sbCxmzZoFACgrK0Nubi527NiBDRs24JVXXsHKlSsbXfOhhx5CcnIyRATnzp3DO++8gzFjxmDPnj14+OGHlR0QESmOSRYRUQskJCRg8ODBTR4PCwvD5MmTbcoyMjIwadIkrFq1CtHR0XjppZdsjsfExNicM27cONx9991YvXo1kyyiDoC3C4mIFGIwGJCVlYVu3bph6dKlEJFm6/fu3RuBgYE4ffq0Sj0kIiUxySIiaoGSkhIUFRXZPFqic+fO+M1vfoOCggKcOHHipm1cvXoVXbt2dUWXiaiN8XYhEVELjBw5slHZzWam6tSt3Tp9+jT69OljLTcajSgqKoKIIC8vD/Pnz4fZbEZiYqJrOk1EbYpJFhFRC6xduxYxMTEOndu5c2cANQvi68vMzERmZqb1Zw8PD6SlpWHmzJmOd5SI3AaTLCKiFoiPj2924XtzysvLAQC+vr425WPHjkVKSgqqqqrw1Vdf4Y033kBFRQW0Wq7kIOoImGQRESns2LFjAICoqCib8vDwcOttyEcffRSBgYFISUnB8OHD8eSTT6reTyJyLf67RESkoPLycmRnZyMiIgK9e/dutu706dPRq1cvzJ8/v8XrvYjIfTHJIiJSSGVlJZKSknDlyhXMmzcPGo2m2fp6vR6zZs1Cbm4udu3apVIviUgpvF1IROQCBQUF2LJlC4Ca2asTJ05gx44duHTpEmbNmoXp06e36DrPPfccFi5ciIyMDDzxxBMK9piIlMYki4jIBY4ePYqkpCRoNBr4+voiIiICY8aMwQsvvID4+PgWX8dgMCAlJQV/+MMf8MUXX2DYsGHKdZqIFKUR3vgnIiIicjmuySIiIiJSAJMsIiIiIgUwySIiIiJSAJMsIiIiIgUwySIiIiJSAJMsIiIiIgUwySIiIiJSAJMsIiIiIgUwySIiIiJSAJMsIiIiIgUwySIiIiJSAJMsIiIiIgUwySIiIiJSwP8D0wmRdupuXsgAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Decoy\n", - "False 32695\n", - "True 2763\n", - "Name: count, dtype: int64\n", - "771\n" - ] - } - ], - "source": [ - "exp_fdr_thres = calc_fdr_and_thres(\n", - " pept_act_sum_ps_exp,\n", - " score_col=\"target_decoy_score\",\n", - " return_plot=True,\n", - " filter_dict={\"log_sum_intensity\": [2, 100]},\n", - ")\n", - "report_decoy_type(df=exp_fdr_thres, isolated_decoys=isolated_decoys)" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.8594536216587714" - ] - }, - "execution_count": 63, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%autoreload 2\n", - "from peak_detection_2d.utils import plot_roc_auc\n", - "plot_roc_auc(\n", - " pred_df_list=[pept_act_sum_ps_full, pept_act_sum_ps_ref, pept_act_sum_ps_both],\n", - " color_list=[\"blue\", \"green\", \"orange\"],\n", - " label_list=[\"fullset\", \"ref full pred\", \"exp 30-min\"],\n", - " save_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\"),\n", - " dataset_name=\"fullset_all_sources\",\n", - " # filter_dict={\"log_sum_intensity\": [2, 100]}\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'ref full pred')" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'exp 30-min')" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, 'Target-Decoy Score')" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from turtle import title\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "pept_act_sum_ps_full = pd.merge(\n", - " left=maxquant_result_ref[[\"mz_rank\", \"source\"]],\n", - " right=pept_act_sum_ps_full,\n", - " how=\"inner\",\n", - ")\n", - "pept_act_sum_ps_full[\"Data\"] = \"Target\"\n", - "pept_act_sum_ps_full.loc[pept_act_sum_ps_full[\"Decoy\"], \"Data\"] = \"Competitor Decoy\"\n", - "pept_act_sum_ps_full.loc[\n", - " pept_act_sum_ps_full[\"mz_rank\"].isin(isolated_decoys), \"Data\"\n", - "] = \"Isolated Decoy\"\n", - "\n", - "# pept_act_sum_ps_full.loc[pept_act_sum_ps_full[\"Decoy\"], \"Data\"] = \"Decoy\"\n", - "fig, axs = plt.subplots(nrows=2, sharex=True, figsize=(8, 6))\n", - "plt.rc(\"font\", size=12) # Set the default font size for all text elements\n", - "sns.histplot(\n", - " pept_act_sum_ps_full.loc[pept_act_sum_ps_full[\"source\"] == \"ref\"],\n", - " x=\"target_decoy_score\",\n", - " hue=\"Data\",\n", - " fill=True,\n", - " hue_order=[\"Target\", \"Competitor Decoy\", \"Isolated Decoy\"],\n", - " ax=axs[1],\n", - " common_norm=True,\n", - " bins=20,\n", - " multiple=\"dodge\",\n", - " palette={\n", - " \"Target\": \"darkorange\",\n", - " \"Competitor Decoy\": \"lightsteelblue\",\n", - " \"Isolated Decoy\": \"royalblue\",\n", - " },\n", - " # title=\"ref 120-min\",\n", - ")\n", - "axs[1].set_title(\"ref full pred\")\n", - "sns.histplot(\n", - " pept_act_sum_ps_full.loc[pept_act_sum_ps_full[\"source\"] != \"ref\"],\n", - " x=\"target_decoy_score\",\n", - " hue=\"Data\",\n", - " fill=True,\n", - " hue_order=[\"Target\", \"Competitor Decoy\", \"Isolated Decoy\"],\n", - " common_norm=True,\n", - " palette={\n", - " \"Target\": \"darkorange\",\n", - " \"Competitor Decoy\": \"lightsteelblue\",\n", - " \"Isolated Decoy\": \"royalblue\",\n", - " },\n", - " ax=axs[0],\n", - " bins=20,\n", - " multiple=\"dodge\",\n", - " # title=\"exp 30-min\",\n", - ")\n", - "axs[0].set_title(\"exp 30-min\")\n", - "\n", - "plt.xlabel(\"Target-Decoy Score\")\n", - "plt.savefig(\n", - " os.path.join(\n", - " cfg.RESULT_PATH,\n", - " \"peak_selection\",\n", - " ps_dir,\n", - " \"results\",\n", - " \"target_decoy_score_exp_and_ref_hist.png\",\n", - " ),\n", - " dpi=300,\n", - " bbox_inches=\"tight\",\n", - ")\n", - "# # Customize the legend labels\n", - "# handles, labels = ax.get_legend_handles_labels()\n", - "# # custom_cmap = ListedColormap([\"#FF5733\", \"#33FF57\"]) # Custom colors\n", - "# custom_labels = [\"Targets\", \"Decoys\"] # Custom label names\n", - "# ax.legend(handles=handles, labels=custom_labels, loc=\"upper right\")" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-05 09:30:31,817 - peak_detection_2d.utils - INFO - Number of entries before filtering: 283473\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-05 09:30:31,825 - peak_detection_2d.utils - INFO - Number of entries after filtering by log_sum_intensity with condition [2, 100]: 148408\n" - ] - } - ], - "source": [ - "from peak_detection_2d.utils import calc_fdr_and_thres\n", - "\n", - "pept_act_sum_ps_full_new = calc_fdr_and_thres(\n", - " pept_act_sum_ps_full,\n", - " score_col=\"target_decoy_score\",\n", - " filter_dict={\"log_sum_intensity\": [2, 100]},\n", - " return_plot=True,\n", - " save_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\"),\n", - " dataset_name=\"fullset\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_full_new.to_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"pept_act_sum_ps_full_fdr_thres.csv\"\n", - " )\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Full set after target decoy competetion" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(Decoy\n", - " False 88828\n", - " True 52911\n", - " Name: count, dtype: int64,\n", - " 0.5956567748908002)" - ] - }, - "execution_count": 68, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from peak_detection_2d.utils import calc_fdr_given_thres\n", - "\n", - "calc_fdr_given_thres(pept_act_sum_ps_full_tdc)" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - } - ], - "source": [ - "plot_target_decoy_distr(\n", - " pept_act_sum_ps_full_tdc,\n", - " # threshold=(0.5, 1),\n", - " save_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\"),\n", - " dataset_name=\"fullset_tdc\",\n", - " main_plot_type=\"scatter\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.6274388922137127" - ] - }, - "execution_count": 70, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plot_roc_auc(\n", - " pept_act_sum_ps_full_tdc,\n", - " save_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\"),\n", - " dataset_name=\"fullset_tdc\",\n", - " # filter_dict={\"log_sum_intensity\": [2, 100]}\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-05 09:31:39,742 - peak_detection_2d.utils - INFO - Number of entries before filtering: 141739\n", - "2024-09-05 09:31:39,747 - peak_detection_2d.utils - INFO - Number of entries after filtering by log_sum_intensity with condition [2, 100]: 95026\n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from peak_detection_2d.utils import calc_fdr_and_thres\n", - "pept_act_sum_ps_full_tdc_new = calc_fdr_and_thres(\n", - " pept_act_sum_ps_full_tdc,\n", - " score_col=\"target_decoy_score\",\n", - " filter_dict={\"log_sum_intensity\": [2, 100]},\n", - " return_plot=True,\n", - " save_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\"),\n", - " dataset_name=\"fullset_tdc\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_full_tdc_new.to_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH,\n", - " \"peak_selection\",\n", - " ps_dir,\n", - " \"pept_act_sum_ps_full_tdc_fdr_thres.csv\",\n", - " ),\n", - " index=False,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Result Analysis (Figure 4)" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'/cmnfs/proj/ORIGINS/data/tims_ramp_time/combined/txt/evidence.txt'" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cfg.MQ_EXP_PATH" - ] - }, - { - "cell_type": "code", - "execution_count": 122, - "metadata": {}, - "outputs": [], - "source": [ - "maxquant_result_exp = pd.read_csv(\n", - " \"/cmnfs/proj/ORIGINS/data/tims_ramp_time/combined_30min_gradient/txt/evidence.txt\",\n", - " sep=\"\\t\",\n", - " low_memory=False,\n", - ")\n", - "mq_exp_100ms = maxquant_result_exp[\n", - " maxquant_result_exp[\"Raw file\"]\n", - " == \"Hela2ug_lowflow_30min_1to37to42_NCE29to59_100ms7R_RA2_1_2078\"\n", - "]\n", - "mq_exp_120ms = maxquant_result_exp[\n", - " maxquant_result_exp[\"Raw file\"]\n", - " == \"Hela2ug_lowflow_30min_1to37to42_NCE29to59_120ms7R_RA2_1_2082\"\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array(['Hela2ug_lowflow_30min_1to37to42_NCE29to59_140ms7R_RA2_1_2086',\n", - " 'Hela2ug_lowflow_30min_1to37to42_NCE29to59_100ms7R_RA2_1_2078',\n", - " 'Hela2ug_lowflow_30min_1to37to42_NCE29to59_120ms7R_RA2_1_2082',\n", - " 'Hela2ug_lowflow_30min_1to37to42_NCE29to59_160ms7R_RA2_1_2091',\n", - " 'Hela2ug_lowflow_30min_1to37to42_NCE29to59_80ms7R_RA2_1_2075'],\n", - " dtype=object)" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "maxquant_result_exp[\"Raw file\"].unique()" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array(['MixB_5ug_30min_7R_R1_RA1_1_5134',\n", - " 'MixA_5ug_30min_7R_R1_RA1_1_5133',\n", - " 'MixA_5ug_30min_7R_R2_RA1_1_5135',\n", - " 'MixA_5ug_30min_7R_R3_RA1_1_5137',\n", - " 'MixA_5ug_30min_7R_R4_RA1_1_5139',\n", - " 'MixB_5ug_30min_7R_R2_RA1_1_5136',\n", - " 'MixB_5ug_30min_7R_R3_RA1_1_5138',\n", - " 'MixB_5ug_30min_7R_R4_RA1_1_5140'], dtype=object)" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "mq_HYE = pd.read_csv(\n", - " \"/cmnfs/proj/ORIGINS/data/species_mix/DDA/txt_HYE_5ug/evidence.txt\",\n", - " sep=\"\\t\",\n", - " low_memory=False,\n", - ")\n", - "mq_HYE[\"Raw file\"].unique()" - ] - }, - { - "cell_type": "code", - "execution_count": 121, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'mq_HYE' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[121], line 9\u001b[0m\n\u001b[1;32m 1\u001b[0m mq_exp_100ms \u001b[38;5;241m=\u001b[39m maxquant_result_exp[\n\u001b[1;32m 2\u001b[0m maxquant_result_exp[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRaw file\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 3\u001b[0m \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mHela2ug_lowflow_30min_1to37to42_NCE29to59_100ms7R_RA2_1_2078\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 4\u001b[0m ]\n\u001b[1;32m 5\u001b[0m mq_exp_120ms \u001b[38;5;241m=\u001b[39m maxquant_result_exp[\n\u001b[1;32m 6\u001b[0m maxquant_result_exp[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRaw file\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 7\u001b[0m \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mHela2ug_lowflow_30min_1to37to42_NCE29to59_120ms7R_RA2_1_2082\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 8\u001b[0m ]\n\u001b[0;32m----> 9\u001b[0m mq_HYE_5137 \u001b[38;5;241m=\u001b[39m \u001b[43mmq_HYE\u001b[49m[mq_HYE[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRaw file\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMixA_5ug_30min_7R_R3_RA1_1_5137\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 10\u001b[0m mq_HYE_5134 \u001b[38;5;241m=\u001b[39m mq_HYE[mq_HYE[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRaw file\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMixB_5ug_30min_7R_R1_RA1_1_5134\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n", - "\u001b[0;31mNameError\u001b[0m: name 'mq_HYE' is not defined" - ] - } - ], - "source": [ - "mq_HYE_5137 = mq_HYE[mq_HYE[\"Raw file\"] == \"MixA_5ug_30min_7R_R3_RA1_1_5137\"]\n", - "mq_HYE_5134 = mq_HYE[mq_HYE[\"Raw file\"] == \"MixB_5ug_30min_7R_R1_RA1_1_5134\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], - "source": [ - "col_to_compare = [\"Modified sequence\", \"Charge\", \"Retention time\"]\n", - "compare_rt = pd.merge(\n", - " mq_HYE_5137[col_to_compare],\n", - " mq_HYE_5134[col_to_compare],\n", - " on=[\"Modified sequence\", \"Charge\"],\n", - " suffixes=(\"_100ms\", \"_120ms\"),\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.022000000000001574" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from utils.metrics import RT_metrics\n", - "\n", - "rt_eval = RT_metrics(\n", - " RT_obs=compare_rt[\"Retention time_100ms\"],\n", - " RT_pred=compare_rt[\"Retention time_120ms\"],\n", - ")\n", - "rt_eval.CalcDeltaRTwidth()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "maxquant_result_exp = maxquant_result_exp.loc[\n", - " maxquant_result_exp[\"Raw file\"].isin(cfg.FILTER_EXP_BY_RAW_FILE),\n", - " :,\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [], - "source": [ - "ps_exp_dir = os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir)\n", - "act_dir = os.path.join(cfg.RESULT_PATH, \"results\", \"activation\")" - ] - }, - { - "cell_type": "code", - "execution_count": 106, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 106, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 106, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pept_act_sum_df = pd.read_csv(os.path.join(act_dir, \"pept_act_sum.csv\"))\n", - "pept_act_sum_df[\"log_sum_intensity\"] = np.log10(pept_act_sum_df[\"pept_act_sum\"] + 1)\n", - "pept_act_sum_df[\"log_sum_intensity\"].hist()\n", - "pept_act_sum_ps = pd.read_csv(os.path.join(ps_exp_dir, \"pept_act_sum_ps.csv\"))\n", - "pept_act_sum_ps[\"log_sum_intensity\"] = np.log10(pept_act_sum_ps[\"sum_intensity\"] + 1)\n", - "pept_act_sum_ps[\"log_sum_intensity\"].hist()" - ] - }, - { - "cell_type": "code", - "execution_count": 251, - "metadata": {}, - "outputs": [], - "source": [ - "eval_dir = os.path.join(cfg.RESULT_PATH, \"results\", \"evaluation\")\n", - "os.makedirs(eval_dir, exist_ok=True)\n", - "act_dir = os.path.join(cfg.RESULT_PATH, \"results\", \"activation\")\n", - "pept_act_sum_df = pd.read_csv(os.path.join(act_dir, \"pept_act_sum.csv\"))\n", - "# TODO: fix im filter config\n", - "if cfg.RESULT_ANALYSIS.POST_PROCESSING.FILTER_BY_IM:\n", - " pept_act_sum_filter_by_im_df = pd.read_csv(\n", - " os.path.join(act_dir, \"pept_act_sum_filter_by_im.csv\")\n", - " )\n", - " pept_act_sum_filter_by_im_df = pept_act_sum_filter_by_im_df.rename(\n", - " {\"sum_intensity\": \"sum_intensity_filter_by_im\"}, axis=1\n", - " )\n", - " pept_act_sum_df = pd.merge(\n", - " left=pept_act_sum_df,\n", - " right=pept_act_sum_filter_by_im_df,\n", - " on=[\"mz_rank\"],\n", - " how=\"left\",\n", - " suffixes=(\"\", \"_filter_by_im\"),\n", - " )\n", - "\n", - "if cfg.PEAK_SELECTION.ENABLE:\n", - " pept_act_sum_ps = pd.read_csv(\n", - " os.path.join(ps_exp_dir, \"pept_act_sum_ps_full_tdc_fdr_thres.csv\")\n", - " )\n", - " pept_act_sum_ps = pept_act_sum_ps.rename(\n", - " {\"sum_intensity\": \"sum_intensity_ps\"}, axis=1\n", - " )\n", - " # pept_act_sum_df = pd.merge(\n", - " # left=pept_act_sum_df,\n", - " # right=pept_act_sum_ps,\n", - " # on=[\"mz_rank\"],\n", - " # how=\"left\",\n", - " # suffixes=(\"\", \"_ps\"),\n", - " # )\n", - " eval_dir = os.path.join(ps_exp_dir, \"results\", \"evaluation\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Result Plots" - ] - }, - { - "cell_type": "code", - "execution_count": 266, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.2985357025337282" - ] - }, - "execution_count": 266, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "10887 / (10887 + 25581)" - ] - }, - { - "cell_type": "code", - "execution_count": 267, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.03887113951011715" - ] - }, - "execution_count": 267, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "219 / (5415 + 219)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Dev" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Generate reverse sequence, eval RT and IM pred diff" - ] - }, - { - "cell_type": "code", - "execution_count": 272, - "metadata": {}, - "outputs": [], - "source": [ - "def reverse_seq(seq):\n", - " middle_seq = seq[1:-1]\n", - " return seq[0] + middle_seq[::-1] + seq[-1]\n", - "\n", - "\n", - "maxquant_result_ref_target = maxquant_result_ref.loc[~maxquant_result_ref[\"Decoy\"]]\n", - "maxquant_result_ref_decoy_reverse = maxquant_result_ref_target.copy()\n", - "maxquant_result_ref_decoy_reverse[\"Sequence\"] = maxquant_result_ref_target[\n", - " \"Sequence\"\n", - "].apply(reverse_seq)" - ] - }, - { - "cell_type": "code", - "execution_count": 281, - "metadata": {}, - "outputs": [], - "source": [ - "maxquant_result_ref_decoy_reverse = maxquant_result_ref_decoy_reverse.loc[\n", - " maxquant_result_ref_decoy_reverse[\"Modifications\"] == \"Unmodified\"\n", - "]\n", - "maxquant_result_ref_decoy_reverse[\"Modified sequence\"] = (\n", - " \"_\" + maxquant_result_ref_decoy_reverse[\"Sequence\"] + \"_\"\n", - ")\n", - "construct_dict_dir = os.path.join(cfg.RESULT_PATH, \"construct_dict_decoy_reverse\")\n", - "os.makedirs(construct_dict_dir, exist_ok=True)\n", - "dict_path = os.path.join(construct_dict_dir, \"maxquant_dict_decoy_for_pred.txt\")\n", - "maxquant_result_ref_decoy_reverse.to_csv(\n", - " dict_path,\n", - " sep=\"\\t\",\n", - " index=False,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 302, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'IsoMZ', 'IsoAbundance', 'mz_rank', 'mz_bin', 'mz_length',\n", - " 'pept_batch_idx', 'rt_start_bin', 'rt_end_bin', 'rt_center_bin',\n", - " 'mobility_pred'],\n", - " dtype='object', length=115)" - ] - }, - "execution_count": 302, - "metadata": {}, - "output_type": "execute_result" - }, - { - "ename": "KeyError", - "evalue": "\"['rt_pred'] not found in axis\"", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[302], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m maxquant_result_ref_decoy_reverse\u001b[38;5;241m.\u001b[39mcolumns\n\u001b[0;32m----> 2\u001b[0m \u001b[43mmaxquant_result_ref_decoy_reverse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdrop\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlabels\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrt_pred\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minplace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/frame.py:5581\u001b[0m, in \u001b[0;36mDataFrame.drop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m 5433\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdrop\u001b[39m(\n\u001b[1;32m 5434\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 5435\u001b[0m labels: IndexLabel \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 5442\u001b[0m errors: IgnoreRaise \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mraise\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 5443\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 5444\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 5445\u001b[0m \u001b[38;5;124;03m Drop specified labels from rows or columns.\u001b[39;00m\n\u001b[1;32m 5446\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 5579\u001b[0m \u001b[38;5;124;03m weight 1.0 0.8\u001b[39;00m\n\u001b[1;32m 5580\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 5581\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdrop\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 5582\u001b[0m \u001b[43m \u001b[49m\u001b[43mlabels\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlabels\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5583\u001b[0m \u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5584\u001b[0m \u001b[43m \u001b[49m\u001b[43mindex\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5585\u001b[0m \u001b[43m \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5586\u001b[0m \u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5587\u001b[0m \u001b[43m \u001b[49m\u001b[43minplace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minplace\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5588\u001b[0m \u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5589\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/generic.py:4788\u001b[0m, in \u001b[0;36mNDFrame.drop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m 4786\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m axis, labels \u001b[38;5;129;01min\u001b[39;00m axes\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m 4787\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m labels \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 4788\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_drop_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlabels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4790\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m inplace:\n\u001b[1;32m 4791\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_update_inplace(obj)\n", - "File \u001b[0;32m~/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/generic.py:4830\u001b[0m, in \u001b[0;36mNDFrame._drop_axis\u001b[0;34m(self, labels, axis, level, errors, only_slice)\u001b[0m\n\u001b[1;32m 4828\u001b[0m new_axis \u001b[38;5;241m=\u001b[39m axis\u001b[38;5;241m.\u001b[39mdrop(labels, level\u001b[38;5;241m=\u001b[39mlevel, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[1;32m 4829\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 4830\u001b[0m new_axis \u001b[38;5;241m=\u001b[39m \u001b[43maxis\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdrop\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlabels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4831\u001b[0m indexer \u001b[38;5;241m=\u001b[39m axis\u001b[38;5;241m.\u001b[39mget_indexer(new_axis)\n\u001b[1;32m 4833\u001b[0m \u001b[38;5;66;03m# Case for non-unique axis\u001b[39;00m\n\u001b[1;32m 4834\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", - "File \u001b[0;32m~/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/indexes/base.py:7070\u001b[0m, in \u001b[0;36mIndex.drop\u001b[0;34m(self, labels, errors)\u001b[0m\n\u001b[1;32m 7068\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mask\u001b[38;5;241m.\u001b[39many():\n\u001b[1;32m 7069\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m errors \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m-> 7070\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mlabels[mask]\u001b[38;5;241m.\u001b[39mtolist()\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not found in axis\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 7071\u001b[0m indexer \u001b[38;5;241m=\u001b[39m indexer[\u001b[38;5;241m~\u001b[39mmask]\n\u001b[1;32m 7072\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdelete(indexer)\n", - "\u001b[0;31mKeyError\u001b[0m: \"['rt_pred'] not found in axis\"" - ] - } - ], - "source": [ - "maxquant_result_ref_decoy_reverse.columns\n", - "maxquant_result_ref_decoy_reverse.drop(labels=[\"rt_pred\"], axis=1, inplace=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 303, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-09-06 15:59:15> Device: cpu\n", - "2024-09-06 15:59:15> dict size: (87378, 115)\n", - "2024-09-06 15:59:18> dict_for_pred size: (87378, 18)\n", - "2024-09-06 15:59:48> Columns in predict_df: Index(['sequence', 'charge', 'rt', 'ccs', 'mobility', 'scan_num', 'raw_name',\n", - " 'precursor_mz', 'score', 'proteins', 'genes', 'decoy', 'intensity',\n", - " 'spec_idx', 'mods', 'mod_sites', 'nAA', 'rt_norm', 'rt_pred',\n", - " 'rt_pred_norm'],\n", - " dtype='object')\n", - "2024-09-06 15:59:48> Columns in predict_df: Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'pept_batch_idx', 'rt_start_bin', 'rt_end_bin', 'rt_center_bin',\n", - " 'mobility_pred', 'sequence', 'charge', 'scan_num', 'raw_name',\n", - " 'rt_pred'],\n", - " dtype='object', length=120)\n", - "2024-09-06 15:59:48> dict size after dropping empty prediction: (87378, 116)\n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from prepare_dict.prepare_dict import dict_add_alpha_pept_pred\n", - "\n", - "# gpu_count = torch.cuda.device_count()\n", - "# match gpu_count:\n", - "# case 0:\n", - "# device = \"cpu\"\n", - "# Logger.info(\"No GPU available, using CPU\")\n", - "# case 1:\n", - "# device = \"cuda\"\n", - "# Logger.info(\"Using 1 GPU, device is %s\", device)\n", - "# case _:\n", - "# device = \"gpu\"\n", - "# Logger.info(\"Using multiple GPUs, device is %s\", device)\n", - "# add rt pred\n", - "\n", - "maxquant_result_ref_decoy_reverse = dict_add_alpha_pept_pred(\n", - " model_path=\"/cmnfs/proj/ORIGINS/SWAPS_exp/tims_ramp_time/120min_libaray_100ms_20240826_175342_706954/construct_dict/RT_transfer_learn/rt_model\",\n", - " pept_property=\"rt\",\n", - " dict_for_pred_path=dict_path,\n", - " maxquant_dict=maxquant_result_ref_decoy_reverse,\n", - " lc_grad=28.17,\n", - " device=\"cpu\",\n", - ")\n", - "\n", - "# add im pred" - ] - }, - { - "cell_type": "code", - "execution_count": 285, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-09-06 15:48:54> Device: cpu\n", - "2024-09-06 15:48:54> dict size: (87378, 115)\n", - "2024-09-06 15:48:57> dict_for_pred size: (87378, 18)\n", - "2024-09-06 15:49:27> Number of entries with empty prediction: 0\n", - "2024-09-06 15:49:28> dict size after dropping empty prediction: (87378, 116)\n" - ] - } - ], - "source": [ - "maxquant_result_ref_decoy_reverse = dict_add_alpha_pept_pred(\n", - " model_path=\"/cmnfs/proj/ORIGINS/SWAPS_exp/tims_ramp_time/full_pred_libaray_100ms_20240904_155157_142605/construct_dict/IM_transfer_learn/mobility_model\",\n", - " pept_property=\"mobility\",\n", - " dict_for_pred_path=dict_path,\n", - " maxquant_dict=maxquant_result_ref_decoy_reverse,\n", - " lc_grad=28.17,\n", - " device=\"cpu\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 307, - "metadata": {}, - "outputs": [], - "source": [ - "maxquant_td_compare = pd.merge(\n", - " left=maxquant_result_ref_target[[\"mz_rank\", \"rt_pred\", \"1/K0\"]],\n", - " right=maxquant_result_ref_decoy_reverse[[\"mz_rank\", \"rt_pred\", \"mobility_pred\"]],\n", - " on=[\"mz_rank\"],\n", - " suffixes=(\"_target\", \"_decoy_reverse\"),\n", - " how=\"inner\",\n", - ")\n", - "maxquant_td_compare[\"rt_diff\"] = abs(\n", - " maxquant_td_compare[\"rt_pred_target\"] - maxquant_td_compare[\"rt_pred_decoy_reverse\"]\n", - ")\n", - "maxquant_td_compare[\"mobility_diff\"] = abs(\n", - " maxquant_td_compare[\"1/K0\"] - maxquant_td_compare[\"mobility_pred\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 309, - "metadata": {}, - "outputs": [], - "source": [ - "maxquant_td_compare[\"rt_differentaible\"] = maxquant_td_compare[\"rt_diff\"] > 0.4\n", - "maxquant_td_compare[\"mobility_differentaible\"] = (\n", - " maxquant_td_compare[\"mobility_diff\"] > 0.02\n", - ")\n", - "maxquant_td_compare[\"differentaible\"] = maxquant_td_compare[\"rt_differentaible\"].astype(\n", - " int\n", - ") + maxquant_td_compare[\"mobility_differentaible\"].astype(int)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Seperated FDR" - ] - }, - { - "cell_type": "code", - "execution_count": 113, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.mixture import GaussianMixture\n", - "from scipy.stats import norm\n", - "import numpy as np\n", - "\n", - "\n", - "def calculat_post_prob(pept_act_sum_ps_full_tdc):\n", - " # Example DataFrame with ion scores (replace with your actual data)\n", - " # df = pd.DataFrame({'score': [100, 150, 200, 250, 300]})\n", - " scores = pept_act_sum_ps_full_tdc[\"target_decoy_score\"].values.reshape(\n", - " -1, 1\n", - " ) # Reshape for sklearn\n", - "\n", - " # Step 1: Fit the Gaussian Mixture Model with 2 components\n", - " gmm = GaussianMixture(n_components=2, random_state=42)\n", - " gmm.fit(scores)\n", - "\n", - " # Step 2: Retrieve the parameters of the GMM\n", - " pi_0, pi_1 = gmm.weights_ # Mixing coefficients (pi_0, pi_1)\n", - " mu_0, mu_1 = gmm.means_.flatten() # Means of the components (f_0 and f_1)\n", - " sigma_0, sigma_1 = np.sqrt(gmm.covariances_).flatten() # Standard deviations\n", - "\n", - " # Step 3: Calculate the posterior probability p(s_i) for each ion\n", - "\n", - " # Calculate the probability density function (PDF) values for each score under f_0 and f_1\n", - " f_0 = norm.pdf(scores.flatten(), mu_0, sigma_0) # f_0(s)\n", - " f_1 = norm.pdf(scores.flatten(), mu_1, sigma_1) # f_1(s)\n", - "\n", - " p_s_i = (pi_0 * f_0) / (pi_0 * f_0 + pi_1 * f_1)\n", - " logging.info(\n", - " \"Distribution f0, targets: mu=%.2f, sigma=%.2f, pi=%.2f\",\n", - " mu_0,\n", - " sigma_0,\n", - " pi_0,\n", - " )\n", - " logging.info(\n", - " \"Distribution f1, decoys: mu=%.2f, sigma=%.2f, pi=%.2f\",\n", - " mu_1,\n", - " sigma_1,\n", - " pi_1,\n", - " )\n", - "\n", - " # scores_target = pept_act_sum_ps_full_tdc.loc[\n", - " # ~pept_act_sum_ps_full_tdc[\"Decoy\"], \"target_decoy_score\"\n", - " # ].values\n", - " # scores_decoy = pept_act_sum_ps_full_tdc.loc[\n", - " # pept_act_sum_ps_full_tdc[\"Decoy\"], \"target_decoy_score\"\n", - " # ].values\n", - " # gmm_target = GaussianMixture(n_components=1, random_state=42).fit(\n", - " # scores_target.reshape(-1, 1)\n", - " # )\n", - " # gmm_decoy = GaussianMixture(n_components=1, random_state=42).fit(\n", - " # scores_decoy.reshape(-1, 1)\n", - " # )\n", - " # pi_target, pi_decoy = (\n", - " # pept_act_sum_ps_full_tdc[~pept_act_sum_ps_full_tdc[\"Decoy\"]].shape[0]\n", - " # / pept_act_sum_ps_full_tdc.shape[0],\n", - " # pept_act_sum_ps_full_tdc[pept_act_sum_ps_full_tdc[\"Decoy\"]].shape[0]\n", - " # / pept_act_sum_ps_full_tdc.shape[0],\n", - " # )\n", - " # f_target = gmm_target.score_samples(scores.reshape(-1, 1))\n", - " # f_decoy = gmm_decoy.score_samples(scores.reshape(-1, 1))\n", - " # # Compute the posterior probability p(s_i) using Equation 4\n", - " # p_s_i = (pi_target * f_target) / (pi_target * f_target + pi_decoy * f_decoy)\n", - " # # # Output the results\n", - " # # print(df[['score', 'posterior_probability']])\n", - " # logging.info(\n", - " # \"Distribution f0, targets: mu=%.2f, sigma=%.2f, pi=%.2f\",\n", - " # gmm_target.means_[0][0],\n", - " # np.sqrt(gmm_target.covariances_[0][0][0]),\n", - " # pi_target,\n", - " # )\n", - " # logging.info(\n", - " # \"Distribution f1, decoys: mu=%.2f, sigma=%.2f, pi=%.2f\",\n", - " # gmm_decoy.means_[0][0],\n", - " # np.sqrt(gmm_decoy.covariances_[0][0][0]),\n", - " # pi_decoy,\n", - " # )\n", - " # Add the posterior probabilities to the dataframe\n", - " pept_act_sum_ps_full_tdc[\"posterior_probability\"] = p_s_i\n", - "\n", - " return pept_act_sum_ps_full_tdc" - ] - }, - { - "cell_type": "code", - "execution_count": 114, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "\n", - "\n", - "def calculate_fdr(df, t):\n", - " # Filter the rows where score is greater than or equal to the threshold t\n", - " df_filtered_targets = df.loc[(df[\"target_decoy_score\"] >= t) & (df[\"Decoy\"] == 0)]\n", - " df_filtered_score = df[df[\"target_decoy_score\"] >= t]\n", - " # Calculate FDR\n", - " numerator = (\n", - " 1 - df_filtered_targets[\"posterior_probability\"]\n", - " ).sum() # Sum of (1 - p(si))\n", - " denominator = len(df_filtered_targets) # Number of ions with score >= t\n", - "\n", - " # Avoid division by zero\n", - " if denominator == 0:\n", - " return 0\n", - "\n", - " fdr = numerator / denominator\n", - " return fdr" - ] - }, - { - "cell_type": "code", - "execution_count": 115, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-09-06 12:37:19> Distribution f0, targets: mu=0.75, sigma=0.17, pi=0.51\n", - "2024-09-06 12:37:19> Distribution f1, decoys: mu=0.14, sigma=0.12, pi=0.49\n" - ] - }, - { - "data": { - "text/plain": [ - "0.26952076856189733" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.18209248697333189" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.1015720168403681" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.028603188101584683" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.002266328495745616" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.00010236930712945285" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "3.924521087973427e-06" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "1.4095940550176495e-07" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "5.577589577809187e-09" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "test = calculat_post_prob(pred_df_new)\n", - "calculate_fdr(test, 0.1)\n", - "calculate_fdr(test, 0.2)\n", - "calculate_fdr(test, 0.3)\n", - "calculate_fdr(test, 0.4)\n", - "calculate_fdr(test, 0.5)\n", - "calculate_fdr(test, 0.6)\n", - "calculate_fdr(test, 0.7)\n", - "calculate_fdr(test, 0.8)\n", - "calculate_fdr(test, 0.9)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Proper competition" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "maxquant_result_ref[\"rt_start_bin\"] = np.round(\n", - " maxquant_result_ref[\"RT_search_left\"], decimals=0\n", - ")\n", - "maxquant_result_ref[\"rt_end_bin\"] = np.round(\n", - " maxquant_result_ref[\"RT_search_right\"], decimals=0\n", - ")\n", - "maxquant_result_ref[\"rt_center_bin\"] = np.round(\n", - " maxquant_result_ref[\"RT_search_center\"], decimals=0\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "# maxquant_result_exp = dict_add_mz_bin(maxquant_result_exp)\n", - "mzbin_td_counts = (\n", - " maxquant_result_ref.groupby([\"mz_bin\"])\n", - " .agg(\n", - " {\n", - " \"RT_search_left\": \"min\",\n", - " \"RT_search_right\": \"max\",\n", - " \"IM_search_idx_left\": \"min\",\n", - " \"IM_search_idx_right\": \"max\",\n", - " \"1/K0\": \"mean\",\n", - " # \"1/K0\": \"std\",\n", - " \"id\": \"count\",\n", - " }\n", - " )\n", - " .reset_index()\n", - ")\n", - "mzbin_td_counts[\"rt_range\"] = (\n", - " mzbin_td_counts[\"RT_search_right\"] - mzbin_td_counts[\"RT_search_left\"]\n", - ")\n", - "mzbin_td_counts[\"im_idx_range\"] = (\n", - " mzbin_td_counts[\"IM_search_idx_right\"] - mzbin_td_counts[\"IM_search_idx_left\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "mzbin_td_counts_filtered = mzbin_td_counts.loc[mzbin_td_counts[\"id\"] > 1]\n", - "plt.scatter(mzbin_td_counts_filtered[\"id\"], mzbin_td_counts_filtered[\"rt_range\"])\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Get number of isolated decoys" - ] - }, - { - "cell_type": "code", - "execution_count": 79, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy\n", - "False 67770\n", - "True 13591\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 79, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_tdc[\"Decoy\"].value_counts()\n", - "pept_act_sum_ps_tdc = pd.read_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH,\n", - " \"peak_selection\",\n", - " ps_dir,\n", - " \"pept_act_sum_ps_full_tdc_fdr_thres.csv\",\n", - " )\n", - ")\n", - "maxquant_result_ref_tdc = pd.merge(\n", - " left=pept_act_sum_ps_tdc, right=maxquant_result_ref, on=[\"mz_rank\", \"Decoy\"]\n", - ")\n", - "%autoreload 2\n", - "from postprocessing.fdr import generate_signal_compete_pairs\n", - "\n", - "signal_compete_tdc = generate_signal_compete_pairs(\n", - " maxquant_dict=maxquant_result_ref_tdc, groupby_columns=\"mz_bin\"\n", - ")\n", - "signal_compete_all = generate_signal_compete_pairs(\n", - " maxquant_dict=maxquant_result_ref, groupby_columns=\"mz_bin\"\n", - ")\n", - "decoy_mz_ranks = set(maxquant_result_ref.loc[maxquant_result_ref[\"Decoy\"], \"mz_rank\"])\n", - "\n", - "from postprocessing.fdr import get_isolated_decoys_from_pairs\n", - "\n", - "isolated_decoys_set_pairs_tdc = get_isolated_decoys_from_pairs(\n", - " result=signal_compete_tdc, decoy_mz_ranks=decoy_mz_ranks\n", - ")\n", - "isolated_decoys_set_pairs_all = get_isolated_decoys_from_pairs(\n", - " result=signal_compete_all, decoy_mz_ranks=decoy_mz_ranks\n", - ")\n", - "\n", - "from postprocessing.fdr import get_isolated_decoy_from_mzbins\n", - "\n", - "isolated_decoys_mzbins_set = get_isolated_decoy_from_mzbins(\n", - " maxquant_result_ref=maxquant_result_ref,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 89, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/matplotlib_venn/_venn3.py:53: UserWarning: Circle A has zero area\n", - " warnings.warn(\"Circle A has zero area\")\n" - ] - }, - { - "data": { - "image/png": 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RDpWWrXpE9iIrC6iokLsKx+TQweRg1kEODSbF0MAD9XUeVveZYII+hKN0iOyFKAKnT8tdhWNy2GByvvg88qvz5S6DyEJnjGlzf52mBnqv+h6qhoi66vx5oKFB7iocj0MGkwZjA37M4SgcUg4VdKiv9bvhcWbfUggqTrxGZA+MRuDcObmrcDwOGUyO5BxBvZG/eZJyOJljYDYLNzzOAAOcQ/jgmshenDkDmNljwKYcLpgU1hQirThN7jKIrhEFNNYGt/vwWn0lNM6c24TIHtTUcMI1W3O4YHIo6xBEsCmclMMJITAaNR04Q4Q2oLy7yiEiG+PQYdtyqGCSUZ6BotoiucsgakYw9OnwOXWaGmhdG7uhGiKytaIiadI1sg2HCibJuclyl0DUjAo61Nd7dupctT/7mhDZi4sX5a7AcThMMEkvS0dpXancZRA1ozdHQGxHp1dr6tW10HlwLCKRPbh8WZrbhLrOYYLJsbxjcpdA1IK5of2dXq1R+ZbbphAi6la1tUBOjtxVOAaHCCZXyq6wtYQURwMPNDQ4d+ka9ap6TrpGZCcuXJC7Asdg98FEFEUcy2VrCSmPzhRpmwv5sK8JkT3IyJAmXaOusftgcqXsCsrqucYIKY+h/sYzvbZHg1APnRtH6BApndEIZGfLXYX9s/tgcrqQqyiR8mjhBYNBa7PrqX2rbHYtIuo+nGyt6+w6mJTWlaKgpkDuMoha0JpCbXq9ek0NVFqTTa9JRLaXlQWY+KXaJXYdTM4WnZW7BCKrTI2+Nr2eCBFO/jU2vSYR2Z7BwMc5XWW3wcRgMuBiCWe0IeVRwanLo3GsaXSuArjcApHipafLXYF9s9tgcrH0Igxmg9xlELWgM3d8Cvr2MMIIJ9+6brk2EdkO5zPpGrsNJnyMQ4pl8O++a3uyEyyR0tXWAuXlcldhv+wymORX53NCNVIkQVSjocG9265fL9RD48SJEoiULjdX7grsl10GkwslnF6PlEmHgE6vjdPue3jXduv1iajr+Din8+wumJhFM9LL2LOIlEltts2kam0xOjOYECldXp7cFdgvuwsmOZU5aDBxxVVSJpPBo9vv0Sg08HEOkcLV1wOl7HHQKXYXTK6UcVo9UioVGhtde+ROWj7OIVI8Ps7pHLsKJqIoIrMiU+4yiKzSwa/b+5c0MfFxDpHisQNs59hVMMmvzke9kUvAkzKpTd3fv6QJH+cQKV9eHiByTsQOs6tgwtYSUjKzwatH78fROUTK1tgIFBfLXYX9sa9gUs5gQspl6KH+JU3MTmw9JFK6/Hy5K7A/dhNMag21qGiokLsMIqs0cIPZ3LNfTo2qBnDtHCJl48icjrObYJJXxUHhpFwa0bvH72mGGTp3rhdFpGRlZXJXYH/sJpjkV7M9jJRLMHf//CXWaNz5OIdIyRhMOs5ugkleNVtMSMFM3bc+TlvMegYTIiUzGIDqarmrsC92EUwaTY0oq2PsJOUyGJxluS/7mRApH1tNOsYugkl+dT5EfvMlhRJENYwGnSz3NsMMnRv7mRApGYNJx9hNMCFSKq3Q8x1fr8d+JkTKxpE5HWMXwaSgukDuEohapRbl6fjaRNSxxYRIydhi0jF2EUzK6vlZJeUSzC6y3t+sZjAhUjIGk45RfDBpMDZwfRxSNNHsJOv9DQKDCZGSGY1AVZXcVdgPxQeT8vpyuUsgapPZpJf3/jBDrTfJWgMRta28XO4K7Ifigwkf45DSmU3yjMi5nsa5Ue4SiKgNdXVyV2A/FB9M2GJCSmc0aeUuASono9wlEFEb6tkjod0YTIi6QAUniGZB7jIAjswhUjS2mLQfgwlRF2jgJncJAACzhsGESMkYTNpP8cGkupGLDJByqUR5pqL/ObPAzq9ESsZHOe2n6GDSYGyAWTTLXQZRqwTI378EAExgMCFSMgaT9lN0MOH8JaR4ojKCiRlmQOB6UkRKxUc57cdgQtQFgqiRuwQLlZati0RKxWDSfsr5rmpFbw0m32/6Hh++/GGbx8QmxeKpt54CAGSfz0byrmRknctCVloWqsur0X9Yf/zfO/9n9dzVS1fjh29/aPP6c34zB7MemWX59/JfL8eF4xesHusb7ItXNr3S5vUclqjF99u/xIevPdPmYbFDx+Kp1z61/Luupgqb1qzAiQPbUFlWBE8ffwybOAuzH1oMJ2fXZucuf2oBLpz6sc3r/+KPr2NC4uMwN6o7/1qoTYcPf4xLlw4gM/MYcnNTYTQ2YuHC/2Hs2EXNjjOZDEhJ2YiUlI3IyDiCsrJsAAKCgwdg7NhFmDDh11CpWn6eGhvrsG/fW/jxx49RUpIOURTh6xuB4cPvxpQpT8DZ2bPFOefP78GOHa8hJycV1dXF8PQMQd++ozB9+h8RFja4zddTU1OG//f/ElBenosBA6Zj8eJtXXl76AaMRulDo+ifusqg6LeotwaTsP5hmP2r2Vb3Hf/uOHKv5GLg6IGWbSf3nsS2/22DRqtBQHgAqsvb7jA8ZPIQ+Ab7Wt238+OdaKhrwIDRA6zut1aXs7syOoDKQRQ1CIsegNkPLra6//iBrcjNuICBIyZatjXU1WL5UwuQffksBgyfgKQptyH70hns/PIdXDz1I57+1xfQ6q5Ncz9m+l3oP3h0i2ubTEZs++y/EAQV4oaOg0pgi0l32rjxBZSUZMLNzQ+ensEoKcm0elxR0WW8/fZd0OvdEBc3DYmJc1BfX4FTpzbh008fQ2rqFjz++EYIwrVh5iaTAa+/PgXp6T8iLGwIxoxZBEAKHt988wKOHv0Mzz13BDrdtXWZdu9eiS++eBIuLl4YOvQOuLn5o6DgAo4d+xLHj6/D7363BfHxN7X6ej7//AnU1VXY5s2hdqmvB9yUMZBP0RhMFCgsNgxhsWEtthsNRuxZuwcqtQpjZo+xbB9+03AMnjQYoTGhqC6vxrMznm3z+kMmD8GQyUNabM88l4lv3/0WoTGh6JvQ1+q5tz16W8dejIMTRTXCYgYiLGZgi31GQyP2fLMGKrUGY26507J9+9pVyL58FtMX/AZ3/GqJZfvX7y7D9i9WYde69zHzvsct28dOn2/13sf3b4Uoihg0egq8/AKhqmAH2O704IPvISCgH3x9I7Bt2zKsX/+c1eP0enfce++bGDNmIfT6a61fd921HMuXT0Zq6rc4fnwdhg+/9nk9cWI90tN/xJAh8/Db337d7Hr//e9cpKR8g2PH1mHMmIcASEHmm29egJOTB1588RR8fMKaXWvVqjuwdesrrQaT48e/wpEjn+Kee/6Dzz9/otPvCXUMg0n7sI+JHTm59yRqKmqQOCERHr4elu0h0SEIjwuHWtO1ZvxD3xwCAIy7fVyXrtOrmFvP9icP7UBNZRkSR0+Fh7c/AEAURRza8gX0zq6Y9cCTzY6f9cCT0Du74uDWL9p160PbpOPGzbhb2qBhi0l3io+/Cb6+ETc8zts7FJMnP9YslACAXu+Km26SHr9euLCv2b7i4isAgISEmS2uN2iQ9Ei1urrIsq26ugT19ZUIDU1oFkqajhcEAVVVRbCmqqoIn376W4we/aDl2tQzzPwSbRdFBxODmZNGXe/ghoMAgPFzx9v82o31jTiy7Qg0Og1G39rysUGTI9uOYMsHW7Dr0104n3we5l7+lSaKrX8JNQWM8TPvsWwrzElHeUkBogcOh97ZpdnxemcXRA8cjuK8LJQW5rZ537KiPJxJ3g9P3wAMGj0VACCoOCpH6dRqaRSXStU80IaEJAAATp/e2uKc1NTNEAQBsbFTLNs8PALh5uaHnJzTKC3NbnG8KIqIi5tmtYZPPvkNBEGNu+9+o0uvhTqul3+7bDdFP8rhHCbXlOSVIO1oGrwDvTFwTMvHBl11/LvjqKuuQ9ItSXD1dG31uPdfeL/ZvwPDA/HLv/4SkQMibV6TfbA+HX1JwVWknTgEb/9gDEyaZNleeDUDABAQav1RWUBoX5xN3o/CnAz4BIS0etfvt38J0WzGmJvvhFrd9GXMYKJ033//AQBgwIBbmm0fNGgWhgyZi5Mn1+Ovfx2K/v0nA5D6mBQXp+OBB95BePgwy/GCIODee9/EBx88gL/8JbFZH5PU1G8xfPh83H77X1vc//Dhj3HixNf47W83wNXVm31MepjIL9F2UXQwEflZtPh+4/cQzSLGzB4Dldr2DV2WxzhzrT/GGTxpMG556BaExYbBxd0FJXkl2P/1fuxduxdvPP4GXvzsRfgE+di8Lnv1/bafgsMtd0GlvvaIra6mCgDg7Opu9TxnV7efjqts9dqiKOL7bV8CAMbNXHBthwKW7KHW7d//Dk6f3orY2KkYNOjWZvsEQcCjj36FDRuex44d/0B29knLvjFjFiI+/uYW1xsx4m64u/vjvffuxaFDH1i2h4YOwujRD8HJqXlnhvLyXHzxxZNISroXQ4bcbtsXR+3CFpP2UXYw4W+AAACz2YzvN30PQRAwbo7t+38UZhfi4omL8Av1Q1xSnNVjbrq/eSe64L7BWPB/C+Ds6ozN723Gjo924J5n7rF6riMTraQBs9mM77evkz5fTf0/bCjtxPcozs9G/8RRCAiNvLaDE6wp1qlT3+Lzz5+Ar28EHn744xb7Gxtr8d579yI9/Uc8/PBnlk6r587twtq1i3H69FYsWfIj/PwiLeccPPg+PvvsMUya9DimTHkCnp5ByM9Pw/r1z+HNN2/Dvfe+icmTH7Mc/9FHj0Ct1uKee/7d7a+XrOPv2u2j6D4mJEk7kobS/FLEJsXCL9TP5tc/tPEQRFHE2NvGNhvC2B4T7pgAALicctnmddmrtOMHUVqYg9ghY+EX3LxjYlNLSVPLyc/V1VT/dJyH1f0AcOinvivjbu19QdAepaZuwdtv3wUPj0D84Q+74ekZ3OKYLVteQUrKRjzwwDtISloANzdfuLn5IilpAe6//21UVRVi69a/WY7Pz0/DJ5/8BgkJs3D33a/D3z8KOp0LwsOH4be/XQ8vr1CsX78EBoM0gOCHHz7E6dNbce+9b8LNzfbfQ4hsSdEtJgLbpgFc1+n1dtt3ejWbzDj87WGo1CqMnTO2w+e7ebpBEAQ01DXYvDZ7IFhp1Tu45adOr7cuaLEvoE8kAKkTrDVN25u1hFynpqoCJw9th4ubB4ZP/NkIDpFfL0qTmroZq1bdCTc3Pzz11B74+0dZPe7MGanT6/UdXJs0bcvKOmHZdvbsTpjNRqvH63QuiIwciZMn16Ow8BJCQxMs577zjvWh52fPbsejjwro02cwXnzxZIdeI7VfB3/v67WUHUz4WUR1eTVS9qXA1dMVQ6YMsfn1Uw+loryoHIPGD4J3gHeHz08/89MMlSHWJ2zrbaorypDyw064unthyLjpLfYHhPaFl28gLp85hoa62mYjcxrqanH5zDH4BYW12vH1x13rYWhswLiZC5pNwkbK0xRKXF198NRTexAQENPqsUZjIwBpKK+TU/P+R03DhLVavWWbydTYbN/PNW3XaKRzoqLGoKGh5cSLDQ3VSE7+At7efTBgwHT4+IS39+VRJ/BHWvsoOpioBD5pOrzlMIwGIybOnAitzvYLxrVn7pLinGI4uzm3GK1TVliGz5Z9BgAYOX2kzWuzD81bTA7v+hpGQyMmzr4PWp2+xdGCIGDcrQuw+aN/Y/PH/242wdrmj/+NhroazLz3sRbnNWkxd8n1lfD5tWKcPr0Vq1bdCRcXbzz11B4EBvZr8/iYmHHIzT2Nb799GQsX/g8qlfS9z2w2YePGPwMA+ve/1joSHS19vR448A4mTHgU3t6hze59+fIheHuHWcJQUtICJCW1bMErLs5AcvIXCA4eiIceeq9rL5puSMUfae2i6GCiUSm6vB7RFBzamrskPyMf21ZL61w0Nki/SeVn5mP10tWWYxYtXdTivMqSSqQeTIWHrwcSJyS2ev0Lxy/g02WfImZIDPxC/ODi4YLi3GKcPngaDXUNGDlzJEbPan3uE0cm/KzD6aGtawE0n7vk56bf/RukfL8T279YhexLZxDeLwFZF0/j7LEDiIwdjGl3Pmz1vMwLqbh6+RzC+yUgvF9Cy1r4KKdbHTz4Hi5dkh6r5uSkWrZduLAXABATMx7jxz+C/Pw0vPXWPBiNDYiNnYyjRz9rcS1f38hma+zMnPk8Tp78BocPr0FW1jHExkpz06SlfYe8vLMICOiHm2++tvZVVNRojBx5H44c+RRLl8ZjyJB58PAIQn7+OaSmfgtBUOGee1ay1Vlh+OloH0X/5HfS9O6m6vTT6ci9nIvIgZEIjQlt9biK4ooWi/JVllQ222YtmPzw7Q8wm8wYPWt0m7PGhseFY/i04chMy0Tm2UzU19bDxd0F0YOjMXbOWCTdktTxF+cgBJXR8vf0tJPIzTiPyLjBCI2yProJkCZSe3r5F9i0ZgWOH9iG8ymH4ekTgJvn/wqzH1wMnd76//tDlgnbWv7mCwCikQv4dadLlw7ihx+aL655+fIhXL58yPLv8eMfQUVFPoxGqc/V0aOfW71W//6TmgUTH59w/OlPx7B1699x9uw2HDjwNgABvr6RuOWWZzBjxnNwdW3+qPUXv/gIMTETcPjwGpw8uR6NjbVwdfXF4MFzMX36s4iK6p2/LCgZW0zaRxAVPFlIWnEa9mful7sMolY5G5JQV6OM+VucSgNQX9Z7F1QkUrp77gE8Wh9wRz9RdH7r7S0mZA+Us2yC2cAWEyIlc+bvDe3CYELUBdc/ypGbyaDoL2eiTlu9ehEefVTApk1L5S6l09RqQNuB8QtLly6FIAhYtGhRl+7blevYqoaOUvR3MgYTUjpRUFAwaWSLCZFSOfHHWbsxmBB1iTIe5QhQcYI1IgWzx8c4fn5+iI2NRXBwy9mKu5OiR+Xo1XoIELhmDimWKCgjmKihgnLabojo5+yxxeSJJ57AE0880eP3VXSLiSAIcNW53vhAIpmYhXq5SwAAqEU+xiFSMntsMZGLoltMAMBT74nqxpZTKRMpgQnK+L+pMtl+VmCi7lRXV4mdO5cjJeUbFBVdgtHYCFdXX3h5haJ//0mYNOm3Vqfxb2ysw7Zty5Cc/DlKSjLh5OSO2NipuP32v1qdYbes7CqOH/8Kp09vRWHhRVRU5EKt1iIgoB+GDJmHadMWt1gGAAA2bVqKb799GWPGLMT997+NnTuXIzn5cxQXX0FDQw3efvtaS35tbTl27/43UlK+QWHhJRiNDfD1jUBi4m245ZZn4eERYDWYFBUVYenSpdi4cSOKiooQFBSE2267DS+//HLX3txW1NfX45VXXsEXX3yBrKwsuLu7Y9q0aVi6dCliY2NbHL906VK8/PLLWLhwIVavXt1sX9Pkfenp6aiqqsJf//pX7N27F+Xl5YiMjMT999+PJUuWQKfTdbhOxQcTb2dv5FTlyF0GkVUm1EIQRIgy9+8QDAwmZD/q66vw6qujkZd3DoIgwN8/Gi4u3qiqKkROzilkZR1DcHB8i2BSV1eJV18dg5ycUwgKikNAQAzy88/j2LG1SEv7Dn/60zH4+kY0O+e771Zg587l0Gqd4ekZhNDQQaiuLsHVqynIyjqOo0c/wzPPHGwxgV0Tg6Eey5dPRnr6Yfj7RyMoKB4FBRcs+7OzU/Cf/8xCeXkOVCoNfH0joNU6o7DwAnbuXI4jRz7F4sU7MHJk89maMzIyMHHiRGRnZ0OlUmHgwIEwm8148803sWXLFsyePdtG77aksbERU6dOxQ8//ICYmBgMGDAAZ86cweeff45NmzZh69atmDBhQoevu2PHDixevBgajQaxsbHQaDS4cOEC/vznP+PUqVNYt25dh6+p+GDi5eQldwlEbVJrjDDKHAxM9QwmZD8OHnwfeXnnEBo6CI89thF+fpGWfQZDPU6d2gQvrz4tztu79z8IDR2E//f/LlhCS3FxOv7975koKDiPjRtfwi9+0Xx23oEDZyIx8TbExIyHSnXtkWdpaTY+//wJpKRsxIYNz+H++1dZrfX48XXw8grFc88dRWTkCABSqw0A1NSU4s03Z6O8PAfjx/8Kc+f+De7u/gCAuroKfP75kzh8eA3efvsu3H33aVz/I/fBBx9EdnY2Bg4ciA0bNiAmRno9586dw5w5c/DWW2918F1t27p16+Dp6YmDBw9i3LhxP70HpXjooYewefNmLFiwAOfOnYOnp2eHrvvEE0/gD3/4A15++WU4/dSR5tNPP8UDDzyAr776Cnv27MGUKS1XwW6LovuYAAwmpHxqtfwdYI21DCZkPwoK0gAA48Y93CyUAIBW64Thw+cjOnpMi/MEQYVf/3pts5YUP7++mDv3FQDAqVObWpwTHz8N/ftPahZKAMDHJwyPPPIZ1GotfvzxE5jNJqu1ms0mPPLIZ5ZQAgA6nfRcZufO11FWdhWDB9+OBx98xxJKAMDZ2RMLF36AsLChKCg4j717v7bsO3DgAA4elNZd+vjjjy2hRKo3HqtXr4bBYNvvKwaDAW+88YYllACAj48PPv/8c3h7eyMvLw/vv/9+h687ceJEvPrqq5ZQAgD33XefpcVn06aWn5MbYTAh6iJBJW8HWAECTPWKb/wksvDxkR63nDq1CfX17e+nNXDgdPj7R7fY3hRiamvLUFNT2mJ/XV0lDhx4F6tX/wJvvDEdr702Af/4x3isWHELBEGFhoZqFBZetHrP4OB4REePtbrv2DFp/aqJE39jdb9KpcbgwbcDAI4e/c6yfcuWLT+dNxFDhgxpcd64ceOQlGTbNciCgoKwYEHLdbbc3NzwyCOPAAA2b97c4es+/vjjVrePGSN9Ti5dutThayr+u5mL1gU6tQ6Npka5SyGySqVukPX+WmjBrw6yJ+PG/RK7dr2OtLTv8OyzwYiPvxkxMeMQHT0OkZFJLVo3mgQE9Le63d090PL3+voquLpeW7/qwoX9eOed+aiqKmyzpurqEqvbg4MHWt3e0FCDwkLph+7GjS9iy5a/Wj2uqqoAAFBQkG3ZlpYmtRgNHGj92k37jh492mbNHREfHw+12vr72lTHuXPnOnzd/v2tf04CA6XPSVVVVYevqfhgAkitJoU1bf+nIpKLKNTJen81R+SQnfHwCMRzzx3Bt9++jBMn1uPkSekDANzd/TF16u8xffqzUKub/4jS661PH6G6btne69elraurxDvv3IWqqiLExU3DjBlLEBqaCFdXb6jV0tfNkiXhKCvLhslk/dFJa/esrS23/D0zM/mGr7murtby96Yf1k0/vK1pa19ntOdenQkRrq5tf046s06wXQQTfxd/BhNSLLNQKev9hUYGE7I/fn59sWjRajz00PvIzj6Jy5cPITV1C86d24FvvvkT6uoqcOedr3bpHqdPb0FVVRG8vcPw+OObLH1DmoiiiNrask5d28nJzfL3v/3tCvz8+rZ6bHQ0MG3atX+7u0vDkwsKClo9p619ndGeezXVJTfF9zEBgGD3np0Ol6gjGtHymXZPMtXoZb0/UVeoVGpERAzH1KlPYvHibViwYCUAYP/+tzr12/b1iovTAQCRkUktQgkA5OaeRkND5+Yicnb2hLd3GADg6tVTbR7r/bORyHFxcQCAs2fPtnrOmTNnOlVXa9LS0mAyWe/g23Sv+Ph4m96zs+wimAS5BcldAlGrRMEAjUaekTkCBDRUMpiQ44iJkUaN1NdXob6+448WrqfTuQAAKiryrO7fseO1Ll1/xIi7AQC7dr3e6qgeAPDxaf7vmTNnAgD27duHU6dahpoffvjBpv1LACAvLw9ffvlli+3V1dWW0TizZs2y6T07yy6CiYvWBR56D7nLIGqVRitPPxOdqOfifWR31q9/Dvv2vYXKyuaPF2pry7F1698BAIGB/eHs3LXv+/36TQQAXLnyA/bvf8ey3WhsxDffvIgff/wEGk3HZyZtMn36H+HlFYKLF/dj1ao7UVR0pdl+URSRkXEUr776+2ZBY+LEiRg7Vhrp88ADD+DKlWvnnT9/HosWLYJWa9tHtFqtFosXL8YPP/xg2VZWVob7778fpaWlCAoKwi9/+Uub3rOz7KKPCSC1mlQ2yPssn6g1Kk0NgJ4Pz+oGO1wZjHq9vLxz2LZtGT799DH4+ITDwyMIjY01lunc9XpXPPDAu12+T3j4UIwe/SAOH/4In3zyKDZvfhmeniEoLLyIuroK3H77X3Hw4LsoKcns1PXd3f3x5JPb8N//3o6UlG+QkvIN/Pyi4O7uj8bGWsv09QCwYMHcZud+9NFHmDhxIlJTU9GvXz8kJCTAbDbjzJkz6Nu3L37zm99g5cqVXX0LLO666y5kZGRg7Nix6NevHzw8PHDmzBnU19fDxcUFn332Gby8vGx2v66wixYTAAh2Yz8TUi65OsCyfwnZo1mzXsStt76AmJjxEEUzrl49iaIiqQPp5MlP4KWXTqN//4k2udfChf/DHXe8isDAWFRVFaGo6DLCw4fht79dj1tv/VOXrx8aOggvvZSK+fP/hX79JqKurhyZmckoKcmAv380Zsx4HDt37sT48eObnRcVFYVjx47ht7/9LYKDg5GWlobKyko8/vjjOHr0KHx+/vyni3Q6HXbv3o0XXngBgiDg9OnTcHNzw913343k5GRMnjzZpvfrCkHsau+iHlJRX4EvznwhdxlEVmlFTxgqRvfoPQUIQHoYRDMf5RApVUwMMHWq3FXYF7tpMfF08oSL1kXuMoisMqASgqpnM75O1DOUECmcjRs+egW7CSYAEO4ZLncJRNYJInS6nu0Aq2rgYxwipbPxPGm9gt10fgWASK9IpBWnyV0GkVVqbQVQ33OtesZytiASKZlaDQQE2OZaH3zwAT744IN2H3/rrbfi+eeft83Ne5hdBZNQ91BoVBoYzUa5SyFqwaQqBtAznbS10MJQ0/lhjkTU/QIDpXBiC1lZWTh06FC7j79+xWJ7YzedX5vsvLwT6eXpcpdB1IIADcSKaUAPfEU513uiLser+29ERJ2WlAQMHSp3FfbHrvqYAECUd5TcJRBZJcIIfQ/1M+FjHCLlCwmRuwL7ZHfBJMIrAhqVXT2Bol5Ere3++Uz4GIdI+bRawN9f7irsk90FE41Kw9E5pFhSP5PupW1gawmR0gUFASq7+wmrDHb5tsX42G+nHnJsBlUh0M1TixjKGEyIlI6PcTrPLoNJhGcE3HRucpdB1IIZjdDrarrt+jro+BiHyA4wmHSeXQYTQRAQ5xcndxlEVqn13fc4R13t3m3XJiLb0OkAPz+5q7BfdhlMACDOLw4qwW7LJwfWKOR0y3VVUKG+iI9xiJQuJAQQuFpEp9ntT3YXrQsivSLlLoOoBaNQBZ2uwebXdWp0g2i22y9Zol4jMlLuCuybXX+XG+A/QO4SiKxS60ptfs3GIj7GIVI6lQqIiJC7Cvtm18EkxD0EXk5ecpdB1IJJnWfT6zmZXWCs5/w9REoXGgroub5ml9h1MAGAgf4D5S6BqIVGoQhqtclm1xPL2FpCZA+iODl5l9l9MInzi4OLlh0CSXn0zrZ5nKOFFg3lTja5FhF1H5WK/Utswe6DiVqlxpCgIXKXQdSCUZNlk+uoKzxtch0i6l59+vAxji3YfTABgHi/eLhqXeUug6iZRhR3eXSODjrUF/P/NpE96NdP7gocg0MEE7VKjaHBXFualEfjVNil81VlXrYphIi6lU7H0Ti24hDBBJD6mnCaelKaBlVGp8/Vi3rUlzrbrhgi6jZ9+wIaDpyzCYcJJipBhaFBbDUhZTGhFk7O1Z07udTLprUQUffhYxzbcZhgAgCxfrFw13FYJSmLoOv4FPVOZieOxCGyEx4eQHCw3FU4DocKJipBhTFhY+Qug6iZemRDpTJ36BxzsXc3VUNEtpaQwLVxbMmhggkARHpFItwzXO4yiCxEwQQnl6J2H+9sdEVjla4bKyIiW9HpgNhYuatwLA4XTABgXNg4aFTshUTK0aC5ALTjNyo11GjIZWsJkb2IiwO0WrmrcCwOGUzc9e6cdI0UxYRaODuX3/A4baUXzAZ19xdERF2mUkmPcci2HDKYAMDgwMHw1HPGTFIOk/ZKm/udRCfUF3HIO5G96NsXcOOXrM05bDBRq9QYFz5O7jKILBqFIuj1dVb3CRBgzPPp4YqIqCsGDZK7AsfksMEEAPp49EGMT4zcZRBZCE7W189xrvOEsY4PqonsRWAgEBAgdxWOyaGDCSB1hOU6OqQU9ciERmNstk0HLWrzPGSqiIg6g60l3cfhg4leo8fkyMlyl0EkEURoXK61mggQgEI/QOQkCET2wt1d6l9C3cPhgwkAhHqEYlAA4y0pQ73qsqXVxLnWi3OWENmZQYM4oVp36hXBBABGho6En4uf3GUQATBD65IFJ7MzH+EQ2RkPD2DAALmrcGy9JpioVWrcFHUTtCp2MCT5qZ0K4FThK3cZRNRBSUnS/CXUfXrV2+uh98CEiAlyl0G9nEpQ4aaoqRg2hBOpEdkTf38gOlruKhxfrwomABDjE4PEwES5y6BebHSf0QhwDUBMDODLRhMiuzFqlNwV9A69LpgAwKjQUYjwjJC7DOqFYnxikBBwbQ7rpCQZiyGidgsPB0JC5K6id+iVwUQQBEztOxW+zvx1lXpOiHtIi6Hr4eFAUJA89RBR+wgCW0t6Uq8MJgCgVWsxI2YGXLQucpdCvYC3kzduib4FKqHll9zo0Rx6SKRksbGANxf97jG9NpgAgKvOFdOjp0Oj0shdCjkwF60LZvabCZ3a+nwlAQFAfHwPF0VE7aLRAMOHy11F79KrgwkA+Lv6Y0rkFLnLIAelVWkxM2Ym3HRtL0E6ciTgwsY7IsUZNAhw5aomParXBxMA6OvdF+PDx8tdBjkYlaDCzdE3w9flxn2ZdDpgzJgeKIqI2s3NDRgyRO4qeh8Gk58M8B+AcWHj5C6DHIQAAZMiJqGPR592nxMdDYSFdWNRRNQhEycCWs7J2eMYTK4zMGAgxoaNlbsMsnMCBEzpOwX9fPt1+Nzx46Vn2kQkr9hYoE/7f68gG2Iw+ZmEgASGE+o0laDCtKhpiPGJ6dT57u7AsGE2LoqIOsTFhY9W5cRgYkVCQALG9OH/SuoYlaDCzVE3I8o7qkvXSUwEfHxsVBQRddjEiVK/L5IHg0krBgUOwug+o+Uug+yEWlBjevR0RHh1fUZhlQqYwCWdiGQREyNNfEjyYTBpQ2JgIqb2nWp1UiyiJhqVBjNiZiDM03Y9VwMDubQ6UU9zdgbGcQyE7PgT9wZifGIwq98s6NV6uUshBXLRumB2/9kI9Qi1+bVHjwa8vGx+WSJqxfjxgJ7f6mXHYNIOwe7BmBs3Fx56D7lLIQXxc/HDvLh5CHAN6JbrazTATTdxlA5RT4iKAvr2lbsKAhhM2s3TyRNz4+Yi0DVQ7lJIAaK8ozAndg5cdd07JaSPDzCWg8SIupWzs9RaQsrAYNIBThonzO4/u8ujLsi+DQ8ejpuibuqxNZbi4oB+HZ8ShYjaQRCAadMAJye5K6EmgiiKotxF2KNTBadwJOcIzKJZ7lKoh2hUGkyOnCxLMDUYgPXrgfLyHr81kUNLSgKGDpW7Croeg0kXFFQXYNeVXagx1MhdCnUzLycvTOs7rV3r3nSX0lJgwwbAaJStBCKHEh4OzJghdxX0cwwmXVRvrMfejL3IqsiSuxTqJnF+cRgbNrbHHt20JS0N2L9f7iqI7J+bG3DnnRyFo0QMJjZytugsDl89DKOZv846Cr1ajwkRExTXp2j3buDSJbmrILJfGg0wZw7g5yd3JWQNg4kNldWVYU/GHhTXFstdCnVRmEcYJkVOgovWRe5SWmB/E6KumTpVmuGVlInBxMZEUcTpwtNIzk2GwWyQuxzqIJ1ah1GhoxDvHy93KW2qrAS++Qaoq5O7EiL7MngwMGqU3FVQWxhMuklNYw0OZR9CRnmG3KVQO/Xz6YdRfUYpspXEmqIiYNMmdoYlaq+wMKmzqyDIXQm1hcGkm2WWZ+JQ9iFUN1bLXQq1wtfZF+PCxyHILUjuUjosKwvYvh3gVzFR23x8pH4lXDVY+RhMeoDRbERybjJOF57mvCcKolfrMSJkBAb4D4Bgx79CcaQOUds8PKRQ4mIfjaG9HoNJD6psqMSx3GO4VHoJIvi2y0WAgFi/WIwMHQknjWNM95icDBw/LncVRMrj4iKFEg8udWY3GExkUF5fjuTcZFwpuyJ3Kb2KAAH9fPthaNBQeDp5yl2Oze3bB5w/L3cVRMqh10uhxNtb7kqoIxhMZFRcW4zk3GROztbNVIIK/Xz6YWjwUIdeIdpslvqbZGfLXQmR/LRaYNYsIKB7Fv+mbsRgogAF1QU4mX8SWRVZfMRjQypBhf6+/TE0aCjc9e5yl9MjDAZppE4xp9KhXkytlkbfhIbKXQl1BoOJglQ1VOFM0RmcLz6PBlOD3OXYLSeNE/r79kdCQALcdG5yl9Pj6uuBb7+V1tYh6m0EAbj5ZiAyUu5KqLMYTBTIaDbiUuklnCk8g5K6ErnLsRsh7iGI94tHX+++UAkqucuRVX09sHkzUML/PtTLTJoExMbKXQV1BYOJwuVX5+Ns0VlklGdwHR4rnDROiPWNRZxfnEN2aO2KhgYpnPCxDvUWY8cCCQlyV0FdxWBiJ4xmIzLLM3Gp9BKyK7N79XwoWpUW4Z7hiPKOQoRXRK9vHWlLY6MUToqK5K6EqPuoVMDkyVz/xlEwmNihRlMjsiqykFGegayKrF7RkuKkcUK4ZzgivSIR5hEGtUotd0l2o7FRGq2Tlyd3JUS2p9FIfUrCwuSuhGyFwcTOmcwm5FfnI7cqF3nVeSisKXSI1hSVoIKfix9C3UMR7hmOANcAu56dVW4mE7BrF5CZKXclRLbj5CSNvuGQYMfCYOJgjGYjCqoLkFedh9yqXLsJKk4aJwS6BiLQLRBBbkHwd/Fnq4iNmc3SJGwXL8pdCVHXubkBt94KeHnJXQnZGoOJgzOZTSivL0dZfRlK60pRVleGsvoyVDVUyTJnikpQwUPvAU+9JzydPOHj7INA10B2XO1B338PnD4tdxVEneftLYUSV1e5K6HuwGDSSxnNRpTXl6O8vhy1hlrUGepQZ6xr8Wd7W1sECNCpddBr9NCr9ZY/nTRO8HTytAQRd507H8kowNmzUkAxK78xjaiZoCBg+nRpunlyTAwm1KZGUyNMZhPMohkmUfpTwLVgoRJU0Kl10Kl1DBx2Jj8f2LkTqKuTuxKi9omIAKZNkzq8kuNiMCHqxWpqpBE7nOuElG7IECApSZrZlRwbgwlRL2cyAfv3s1MsKZNeD0yZAoSHy10J9RQGEyICAJw6Bfz4I8DvCKQUfn7SHCXuvWMNTvoJgwkRWeTkSPOdNHANSZLZgAHAmDHSSsHUuzCYEFEzlZXAjh1cnZjkodEAEyYA/frJXQnJhcGEiFowmYDkZOnxDr9DUE/x8pIe3Xh7y10JyYnBhIhaVVAA7N0LVFTIXQk5uuhoYOJEQKuVuxKSG5dlbafJkydDEASsXr1alvsvWrQIgiBg6dKlsty/OwiCAEEQkJGRIdt1bFWDowoMBO68Exg4UO5KyFE5OQE33STNT8JQQgDAaWp6sRUrVqC8vByLFi1CZGSk3OWQQmk0wLhxQN++UutJdbXcFZGjiIoCxo+XwglREwaTdgoPD0dsbCw8PR1nTZcVK1YgMzMTkydP7rXBJDY2FgCg5a9qNxQSAsyfD/zwA5CWJnc1ZM+cnaVA0rev3JWQEjGYtNOaNWvkLoG6QRp/wnaIViv1A4iMlCZlq62VuyKyN/HxwMiRXOuGWsdgQkQdFh4O3H03cPy4tFIxFwOkG/HxkYYBBwbKXQkpHTu/tlNrnV+PHz+O+++/HxEREdDr9XBzc0NkZCRmzJiB5cuXw9qgp5KSEjz//PNISEiAq6sr3NzckJiYiD//+c+o6MTwhwMHDuCZZ57ByJEjERwcDJ1Oh8DAQMyaNQubNm1qcfzq1ashCAIyMzMBAFOmTLF0AhUEAYsWLWpxzp49ezB//nyEhoZCp9PB19cX06dPxzfffNNmbV999RXGjx8PNzc3eHl5YeLEiTc8pysOHjyIWbNmwc/PD87OzhgyZAj+85//wGQyWT2+tc6vS5cutbwXJpMJ//rXv5CYmAgXFxd4e3tj9uzZOHbsWLe9Dnug0wGjR0sBhU3y1BqNRmohueMOhhJqH7aYdMG2bdswZ84cGAwGuLm5oX///tBqtbh69Sq2b9+O7du3Y/HixdBctxTm2bNnccsttyAnJwdqtRoDBw6E2WzGmTNnkJqaijVr1mDnzp2IiYlpdx3z5s1DSUkJfHx8EBwcjJCQEGRnZ2PLli3YsmULlixZgr///e+W4wMDAzFu3DgkJyejoaEBCQkJzfrO9O/f3/J3URSxePFirFy5EgDg7e2NhIQE5ObmYseOHdixYweeeOIJy/7rvfTSS/jLX/4CAPD390dERATOnj2LuXPnYsWKFe1+fe21YcMGPP3003B2dkZcXBwKCgqQkpKC3/3ud/juu++wbt06qDs4jaTRaMStt96KHTt2ICYmBv3790daWho2b96M3bt3Y9++fUhKSrL5a7EnHh7S3BP5+VL/k6IiuSsiJVCpgLg4YNgwwMVF7mrInrDFpAuWLFkCg8GAZ599FoWFhUhNTcXx48dRWFiIzMxMvPrqq1Cprr3FDQ0NuOOOO5CTk4NRo0bhypUrSElJQWpqKi5cuIDBgwcjIyMDd911V6u/4VuzbNkyXL58GSUlJTh9+jSOHTuGwsJC7Ny5EwEBAVi2bBkOHz5sOX7mzJk4ePAggoKCAAArV67EwYMHLR/PP/+85djXXnsNK1euRJ8+fbBp0yaUlpbi+PHjyM/Px7Zt2xAQEID//Oc/+Oijj5rVtGvXLksoefXVV5Gfn4+jR48iPz8ff/7zn/HMM8906j1vy7PPPotFixahoKAAR48eRVZWFtavXw9nZ2ds2LABr7/+eoevuXbtWly4cAHJycm4ePEiTp48iatXr2Ls2LGoq6vD008/bfPXYa+CgoB586QF11xd5a6G5CIIQEyM1JI2fjxDCXUcg0kXNHWcfP755+Hs7NxsX3h4OJ599tlmwWTt2rU4f/48dDod1q1bh/DrlsuMjo7G2rVroVarkZKSgg0bNrS7jkceeQRRUVEttt90003429/+BgD48MMPO/LSAABlZWX4y1/+ArVajfXr12P27NnN9k+fPh1vvfUWADRrkbn+33Pnzm32Pmg0GixduhSTJ0/ucD03EhUVhXfeeQcu130nnDt3Ll544QUAwD/+8Q80dHARGIPBgDVr1mD48OGWbX5+fpYWogMHDnTq8Zsj69cPWLAAGDFCasan3iM8XJr3ZupUqSWNqDMYTLogIiICAPDpp5+26/jNmzcDAO6++2706dOnxf7+/ftjzpw5zY5tr7Nnz+Lll1/GnXfeiSlTpmD8+PEYP3483njjDQDAiRMnOnQ9ANiyZQuqq6sxYsQIjBgxwuoxt912G7RaLc6dO4e8vDwAQE1NDfbt2wcAePLJJ62e9/vf/77D9dzIk08+2SwINnn88ceh0WhQXFyMI0eOdOiaiYmJmDBhQovtQ4cOhV6vhyiKuHz5cqdrdlQajdSEf8890igMK58WciBBQcCcOcCMGVInV6Ku4O8zXfDHP/4RDz/8MB577DEsX74cN998M8aMGYNJkyZZQsv1zp8/DwBISEho9ZqDBg3C+vXrOzSMdcmSJfjHP/5htaNtk5KSknZfr0lKSgoAID09HePHj2/1OEEQAADZ2dkIDg7GpUuXLI+iBrYyZWhr27uitffV09MTffr0QUZGBs6dO2c1aLTm+v421xMEAQEBAcjOzkZVVVWn6u0NXFykkRjDhknr7pw7BxiNcldFtuLrCyQlSS0lRLbCYNIFv/zlL+Ht7Y1//vOfOHz4MFatWoVVq1YBAEaNGoVly5Y1e2TR9AOsqW+HNcHBwc2OvZHPP//c0pflpZdewh133IG+ffvC1dUVKpUKu3fvxrRp02AwGDr8+srKygAAhYWFKCwsvOHxtT9NatFUu0qlgr+/v9VjA7uhe35b1wwMDERGRkaHQ4RrG50lmlpnuNzUjbm6SkvYDx0qDS8+cwbo4FM1UpA+fYCEBAYS6h4MJl00b948zJs3DxUVFfj++++xf/9+fPnll/jxxx8xffp0HDlyBIMHDwYAuLu7AwDy8/NbvV7T45CmY2+kafjyU089ZXUdnc60lDRxc3MDADz00EMd6qPSVLvZbEZRURECAgJaHFNQUNDpulpTUFBgmcm1tfu1932l7uHkJPU9GTIEOH9eCinsomMftFqgf39p3SQvL7mrIUfGJ7824unpiZkzZ+Lvf/870tLSMHr0aDQ2NuK9996zHBMXFwcAOH36dKvXSU1NBQDEx8e3677p6ekAgIkTJ1rdf/1onJ9regTTmkGDBgEATp061a5amsTExFiG5Z49e9bqMWfOnOnQNdujtWtWVFTg6tWrANr/vlL30mikH3ALFgDTp0vT3ZMyeXgAY8cC998vrZnEUELdjcGkG2g0GowaNQoAkJOTY9k+a9YsANLonKYflNe7dOkSNm7c2OzYG2kagdLU0nK9oqKiNldDbjq3tpV5xWfPng1nZ2ecPHkSO3fubFc9gPT4oykoWZvfBIClU64trVy50upjlf/+978wGo3w8/PDyJEjbX5f6pqICGD2bOCuu4DERA4vVYqwMKkz6z33SI9tdDq5K6LegsGkkyorKzF//nxs374djY2NzfYdO3YMX3zxBQA0m3zr7rvvRmxsLBobGzF//nxkZWVZ9l25cgV33303TCYTBg8ejNtvv71ddUyaNAkA8Morr+DChQuW7enp6Zg9e3aroQOAZRK37777zur+gIAAy1Db+fPnY82aNTD+rOdiaWkp1qxZ02JekiVLlgAAvv76ayxfvhzmn+YsN5lM+Mtf/oI9e/a06/V1xKVLl/Cb3/wGdXV1lm0bN27EX//6VwDA008/DT0X6FAsHx9pJtn77wduvVV6bMC1FXuWu7sUDhcsAGbOZB8SkgeDSSeZzWasW7cOM2bMgLu7OwYOHIhRo0ahb9++GDFiBPLz8zFq1CgsXrzYco5Op8NXX32FkJAQHD58GFFRURg8eDASExPRr18/nDhxApGRkR2aofTZZ59FUFAQMjMzMXDgQAwcOBCJiYmIiYnBhQsX8M9//rPVcx966CEAwOuvv47o6GhMnDgRkydPxrJlyyzHPPfcc3jmmWdQUVGBhQsXwtvbG8OHD8eoUaMQGRkJPz8/LFy4EEePHm127VtuuQXPPfccACkQBAcHY+TIkQgKCsJLL72E1157rd3vdXu9+uqreP/99xEYGIikpCRERETg9ttvR21tLebMmYP/+7//s/k9yfYEQepcOXky8OCD0pwYYWEcctxd3N2BwYOlyfHuvVcKhw60iDrZIX6pd5K7uzs++eQTPPzww+jfvz8KCgpw7NgxVFRUYMKECVi5ciX279/fbLIvQBome+rUKTz33HOIjY3FxYsXcfnyZQwYMAAvvvgiTpw40aHp6JtCzv333w9vb29cvHgR5eXlWLhwIU6cONHmsNw777wTH3zwAUaNGoWioiIcPHgQ+/btazZUWRAE/OMf/8CRI0fwi1/8AoGBgTh79ixOnDgBg8GA6dOnY+XKlfj4449bXP+VV17B2rVrMXbsWFRXV+P8+fOIj4/Hhg0bmgU2W5k3bx727t2L8ePH48qVKygoKMCgQYPwxhtv4Ouvv262NADZB41GmkV05kypJWXsWKCVgV7UAT8PI6NG8X0l5RBEjnUkIjtTXQ3k5ABXr0p/1tfLXZHyubsDUVHSB0MIKRmDCRHZveJiKaDk5AB5eUAHlppyWM7OQHAwEBoqjXri4xmyFwwmRORQTCZppeOmFpWSEqA3fJdzc5Omhg8MlAIJp4Yne8VgQorR1rT31qxbt67NWXSJACmolJVJAaW09Nqf9vz4x81Nmk/E21sKIoGBXNGZHAeDCSnGjSZ8+7n09HRERkZ2TzHk8GpqmgeVkhKgqko5a/loNNLkZl5eLT/Yj5scGYMJEdF16uul0HL9R12dtL3pz/p6oLFRekTUke+gOh2g10sfTk7W/+7iIvUHcXOThk4T9TYMJkREXdQUUJo+zObmf1eppNDBoEF0YwwmREREpBicYI2IiIgUg8GEiIiIFIPBhIiIiBSDwYSIiIgUg8GEiIiIFIPBhIiIiBSDwYSIFGv16tUQBAGTJ0+Wu5QWMjIyIAhCh2csJqK2cWJjIuo2K1asQHl5ORYtWsTlA4ioXRhMiKjbrFixApmZmZg8eTKDCRG1Cx/lEBERkWIwmBAREZFiMJgQkc01dVrNzMwEAEyZMsXSUVQQBCxatMhybHV1NZ5//nlER0dDr9cjJCQEixYtQlZW1g3vYzQa8eGHH2L69OkICAiAXq9HaGgoJk2ahOXLl6OioqJLr0MURbz77rsYPnw4XFxc4Ovri5kzZ2L//v3tOn/Pnj2YP38+QkNDodPp4Ovri+nTp+Obb75p87y8vDwsWbIEQ4YMgYeHB1xcXNCvXz/cc8892LRpk9Vztm3bhjlz5iAwMBA6nQ5BQUGYO3cudu/e3eLY1157DYIgYNy4cW3W8dBDD0EQBDz++OPNtu/evRvz5s1DSEgItFotPD09ER0djXnz5uGDDz64wbtCdAMiEZGNbdmyRRw3bpyo1+tFAGJCQoI4btw4y8ff/vY3URRFsbS0VExMTBQBiADEuLg4cciQIaJGoxF9fX3FF198UQQgTpo0qcU9ioqKxLFjx1rODQoKEpOSksSIiAhRrVaLAMQ9e/Z06XU89NBDluuHhoaKI0aMEN3d3UW1Wi0uX77csu/nzGaz+Lvf/c6y39vbWxw6dKgYGBho2fbEE09YvefWrVtFDw8PEYCoUqnE+Ph4cdiwYaKPj48IQIyIiGhxzuLFiy3XDQgIEJOSkkQ/Pz/LthdeeKHZ8YWFhaJOpxMBiGfPnrVaR1lZmejs7CwCEE+cOGHZ/u6771qu6+XlJQ4ePFhMTEwUvb29Le8TUVcwmBBRt4mIiGgzIDzwwAMiADEkJERMTk62bM/OzhZHjRolarVaq8HEbDaLkydPFgGIYWFh4nfffddsf3l5ufjf//631R+67fHee++JAESNRiN+9NFHlu21tbXiI488YqnNWjB59dVXRQBinz59xE2bNjXbt23bNjEgIEAEIK5Zs6bZvjNnzoguLi4iAPGuu+4Sc3JyWuxftmxZs22rV68WAYhqtVp86623RJPJJIqiKBqNRnH58uWiIAgiAPHLL79sdt4999wjAhCfeuopq6//P//5jwhAHDFihGWb0WgUfX19RQDiv//9b9FgMDQ759y5c+Ibb7xh9XpE7cVgQkTdpq1gkpGRIapUKhGAuGHDBqv7NRqN1WCyceNGEYCo1+u7FD5aYzabxejoaBGA+Pvf/77FfpPJJMbGxloNJqWlpaKbm5uoVqvFo0ePWr3+V199JQIQ4+Pjm22/4447LK+3KWDcSFOdjz32mNX9TeEvISGh2fY9e/aIAER/f3+xoaGhxXlDhw4VAYhvv/22ZVteXp6lpYSouzCYEFG3aSuYrFq1SgQgRkZGimaz2er58+fPtxpMFi5cKAIQ77333m6oWhTT0tIsoePKlStWj3nzzTetBpOPP/5YBCCOGjWq1es3NjZaWlxyc3NFURTFuro6y6Ov7du3t6vOc+fOWWq4dOmS1WNSUlIsx2RmZjbb1xSu1q5d22x7cnKyCEB0dXUVKysrLdtNJpPo7OwsCoIgbt68uV01EnUUO78SkSzS0tIAAPHx8a3Onjpw4ECr21NTUwEAY8eO7dbaXFxc0Ldv3w7VlpKSAgBIT0/H+PHjrX40dQYGgOzsbADAxYsX0dDQAKD9r+v8+fMAAGdnZ0RHR1s9ZsCAAVCr1c1eV5Nf//rXAID333+/2fZ3330XALBgwQK4u7tbtqtUKjz99NMQRRGzZs1CYmIi/vCHP2Dt2rXIz89vV81EN8IJ1ohIFlVVVQCAwMDAVo9pbV9lZSUAwMvLy+Z1AddqCwgIaPWY1morKysDABQWFqKwsPCG96qtrQVw7TWp1Wq4ubl1qM623kONRgM/Pz8UFBRYjm+ycOFCPP/889i5cyeysrIQHh6O2tpafPbZZwCAX/3qVy2u9/LLLyMiIgIrV65ESkoKUlNTsWLFCgiCgGnTpuGf//wnBg8e3K76iaxhiwkRyaLpN/GCgoJWj2ltn4eHBwCgvLzc5nUB12prK1i0VltTqHjooYcgSo/L2/xoWgeo6TWZTCZUV1d3qM623kOj0Yji4uJmxzfx9fXFXXfdBbPZbBnmu3btWlRWViIhIQGjR49ucT1BEPDwww/j5MmTKCwsxPr16/H73/8eQUFB2LVrF6ZOnYqcnJx21U9kDYMJEXWbtha4i4uLAwCcO3cOoihaPebMmTNWtycmJgIAvv/++y5W2HZttbW1yMjI6FBtgwYNAgCcOnWqQ/fs378/nJycALT/dTXVWVdXh8uXL1s95uzZszCZTACkx2Y/9+ijjwIA/ve//8FsNuO9994DADzyyCM3vL+/vz/mzp2Lf/3rXzh//jz69u2L0tJSfP755+2qn8gaBhMi6jYuLi4Arj2uuN706dOhUqmQkZGBb7/9tsX+rKwsbNiwwep177rrLgDA119/belnYUv9+/dHVFQUAGDlypUt9ouiaHU7AMyePRvOzs44efIkdu7c2e576vV6zJ49GwCwbNmyVsPa9WJjYxETEwMAeP31160es3z5cgBSYAoLC2uxf8KECYiPj0dWVhb+/e9/49ChQ9Dr9XjwwQfbXTsgtcY0BUa2mFCXyNLlloh6hTlz5rQ5V8Z9991nme/j+PHjlu1Xr14Vx4wZ0+o8JqIoilOnTrVMOPbzUT8VFRXiW2+91aWhxO+8844IQNRqteInn3xi2V5XVyc++uijbc5j8re//U0EIHp6eooffvhhi/k+SkpKxA8//FB8+umnm20/e/asZR6TBQsWWEbsNLnRPCarVq2yjHAymUziihUrWp3H5HorVqywzNkCQLzvvvusHnfmzBnxl7/8pXjgwIEWw5l37Nghurm5iQDETz/9tNV7Ed0IgwkRdZt169ZZfnhHRUWJEyZMECdNmiT+/e9/F0VRFIuLi8WEhATLMfHx8eLQoUPbPfPr6NGjLecGBweLI0eOFCMjI20y86vZbLYEp6bwlJSUJHp4eLRr5tdnnnnGst/NzU0cNmyYOHLkSDEiIsISFqy9rq1bt4ru7u6WmV8HDBggDhs2zDKx2Y1mfg0MDBSTkpJEf39/y7Y//elPbb7W0tJS0cnJyXJ8a+/biRMnLMe4uLiIiYmJYlJSkhgSEmLZfvvtt7d7DhYiaxhMiKhbffDBB+KoUaNEd3d3yw/khQsXWvZXVlaKS5YsEfv27SvqdDoxODhYXLhwoZiZmSn+73//a/UHuChK84G8++674pQpU0QfHx9Rp9OJoaGh4qRJk8R//etfYkVFRZdqN5lM4qpVq8ShQ4eKTk5Oore3tzh9+nRx3759Ynp6eqvBpMmRI0fEX/ziF2J0dLTo5OQkarVaMSQkRJwxY4a4cuVKMTs72+p5V69eFZ966ilxwIABoouLi+jq6irGxMSI9913X6vzh2zZskWcPXu26O/vL2o0GjEgIEC8/fbbxV27drXrtTZNxNavX79Wj6mpqRHff/998b777hPj4uJEb29vUaPRiH5+fuJNN90krlmzhqGEukwQxXY8yCQiIod2yy23YOfOnVi2bBn++Mc/yl0O9WIMJkREvdzly5fRr18/aLVaZGVltTkvClF346gcIqJezGQy4Y9//CNEUcQ999zDUEKyY4sJETm0Dz74wDJ5WHvceuuteP7557uxImVYvXo1/ve//+Hy5cvIycmBm5sbUlNTERkZKXdp1MtxSnoicmhZWVk4dOhQu49vmhfE0WVkZGD//v1wc3PDxIkT8eqrrzKUkCKwxYSIiIgUg31MiIiISDEYTIiIiEgxGEyIiIhIMRhMiIiISDEYTIiIiEgxGEyIiIhIMRhMiIiISDEYTIiIiEgxGEyIiIhIMf4/PW06ZojhATwAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from utils.plot import plot_venn3\n", - "\n", - "plot_venn3(\n", - " set1=isolated_decoys_set_pairs_all,\n", - " set2=isolated_decoys_mzbins_set,\n", - " set3=set(\n", - " maxquant_result_ref_tdc.loc[maxquant_result_ref_tdc[\"Decoy\"], \"mz_rank\"].values\n", - " ),\n", - " label1=\"shared_bin\",\n", - " label2=\"isolated_bin\",\n", - " label3=\"tdc_decoys\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "isolated_decoys_all = isolated_decoys_set_pairs_tdc.union(isolated_decoys_mzbins_set)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Signal competition" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-11 15:43:56,306 - postprocessing.compete_signal - INFO - Number of pairs after filtering rt and im distance: 37640\n", - "2024-09-11 15:43:56,355 - postprocessing.compete_signal - INFO - Number of pairs after filtering by log sum intensity: 37640\n", - "2024-09-11 15:43:56,357 - postprocessing.compete_signal - INFO - Number of pairs with delta log intensity < 0.5: 691\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/postprocessing/compete_signal.py:106: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " result_filtered_no_low_int_and_only_close_int[[\"loser\", \"winner\"]] = (\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/postprocessing/compete_signal.py:106: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " result_filtered_no_low_int_and_only_close_int[[\"loser\", \"winner\"]] = (\n", - "/cmnfs/proj/ORIGINS/protMSD/maxquant/ScanByScan/postprocessing/compete_signal.py:124: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", - "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", - "\n", - "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", - "\n", - "\n", - " pept_act_sum_ps[\"competition\"].fillna(\"no_competition\", inplace=True)\n", - "2024-09-11 15:43:56,519 - postprocessing.compete_signal - INFO - Number of winners, losers and no competition: competition\n", - "no_competition 80002\n", - "loser 682\n", - "winner 677\n", - "Name: count, dtype: int64\n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from postprocessing.compete_signal import compete_candidates_for_signal\n", - "\n", - "# pept_act_sum_ps_all = pd.read_csv(\n", - "# os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"pept_act_sum_ps.csv\")\n", - "# )\n", - "pept_act_sum_ps_tdc_all, result_after_compete, result_filtered = compete_candidates_for_signal(\n", - " result=signal_compete_tdc, pept_act_sum_ps=pept_act_sum_ps_tdc, log_sum_intensity_thres=1, delta_log_sum_intensity_thres=0.01\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### FDR eval and result analysis" - ] - }, - { - "cell_type": "code", - "execution_count": 109, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy\n", - "False 67121\n", - "True 13356\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 109, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_full_tdc = pept_act_sum_ps_tdc_all.loc[\n", - " pept_act_sum_ps_tdc_all[\"competition\"] != \"loser\"\n", - "]\n", - "pept_act_sum_ps_full_tdc = pept_act_sum_ps_full_tdc.loc[\n", - " pept_act_sum_ps_full_tdc[\"log_sum_intensity\"] >= 2\n", - "]\n", - "pept_act_sum_ps_full_tdc[\"Decoy\"].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 114, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "3527" - ] - }, - "execution_count": 114, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_full_tdc.loc[pept_act_sum_ps_full_tdc[\"Decoy\"], \"mz_rank\"].isin(\n", - " isolated_decoys_all\n", - ").sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 113, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.1989839245541634" - ] - }, - "execution_count": 113, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.14643703162944532" - ] - }, - "execution_count": 113, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.05254689292471805" - ] - }, - "execution_count": 113, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "13356 / 67121\n", - "(13356 - 3527) / 67121\n", - "3527 / 67121" - ] - }, - { - "cell_type": "code", - "execution_count": 115, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from peak_detection_2d.utils import calc_fdr_and_thres\n", - "\n", - "fdr_no_loser_filter = calc_fdr_and_thres(pept_act_sum_ps_full_tdc, return_plot=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['Unnamed: 0', 'sum_intensity', 'mz_rank', 'out_score',\n", - " 'target_decoy_score', 'Decoy', 'TD pair id', 'log_sum_intensity',\n", - " 'Target', 'fdr', 'N_identified_target', 'competition'],\n", - " dtype='object')" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_full_tdc.columns" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-11 15:54:56,505 - result_analysis.result_analysis - INFO - Drop na values in pept_act_sum, Pept activation sum entries: 178795\n", - "2024-09-11 15:54:56,506 - result_analysis.result_analysis - INFO - Filtering the data by the sum of intensity threshold 2, number of entries before filtering 178795\n", - "2024-09-11 15:54:56,509 - result_analysis.result_analysis - INFO - Number of entries after filtering 178794\n", - "2024-09-11 15:54:56,510 - result_analysis.result_analysis - INFO - No decoy entries in the data, using FDR threshold of dictionary 1.0\n" - ] - } - ], - "source": [ - "from math import inf\n", - "from result_analysis.result_analysis import SWAPSResult\n", - "\n", - "pept_act_sum_df = pd.read_csv(\n", - " os.path.join(cfg.RESULT_PATH, \"results\", \"activation\", \"pept_act_sum.csv\")\n", - ")\n", - "swaps_result = SWAPSResult(\n", - " maxquant_dict=maxquant_result_ref,\n", - " pept_act_sum_df=pept_act_sum_df,\n", - " infer_intensity_col=\"pept_act_sum\",\n", - " fdr_thres=1.0,\n", - " log_sum_intensity_thres=2,\n", - " include_decoys=False,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-11 15:56:37,848 - result_analysis.result_analysis - INFO - Number of entries after merging 72936 and columns Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'Time_minute_right_ref', 'MS1_frame_idx_right_ref', 'IsoMZ',\n", - " 'IsoAbundance', 'mz_rank', 'mz_bin', 'mz_length', 'pept_batch_idx',\n", - " 'pept_act_sum', 'log_sum_intensity'],\n", - " dtype='object', length=114)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Data: Intensity_log pept_act_sum_log , slope = 0.281 , intercept = 3.673 , PearsonR = 0.305 , SpearmanR = 0.282\n" - ] - }, - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "plt.figure(figsize=(8, 6))\n", - "swaps_result.plot_intensity_corr(contour=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-11 15:48:53,555 - result_analysis.result_analysis - INFO - Drop na values in sum_intensity, Pept activation sum entries: 80477\n", - "2024-09-11 15:48:53,556 - result_analysis.result_analysis - INFO - Filtering the data by the sum of intensity threshold 2, number of entries before filtering 80477\n", - "2024-09-11 15:48:53,561 - result_analysis.result_analysis - INFO - Number of entries after filtering 80477\n", - "2024-09-11 15:48:53,564 - result_analysis.result_analysis - INFO - FDR threshold is larger than the maximum FDR, set to maximum FDR 0.199\n", - "2024-09-11 15:48:53,565 - result_analysis.result_analysis - INFO - Calculating FDR results after filter...\n", - "2024-09-11 15:48:53,568 - peak_detection_2d.utils - INFO - Number of entries before filtering: 80477\n", - "2024-09-11 15:48:53,573 - peak_detection_2d.utils - INFO - Number of entries after filtering by log_sum_intensity with condition [0, 100]: 80477\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-11 15:48:56,765 - result_analysis.result_analysis - INFO - Filtering the data by FDR threshold 0.199, number of entries before filtering 80477\n", - "2024-09-11 15:48:56,774 - result_analysis.result_analysis - INFO - Score threshold 0.0166004157587719, number of entries after filtering 78897\n", - "2024-09-11 15:48:56,775 - result_analysis.result_analysis - INFO - Removing decoy entries, number of entries before filtering 78897\n", - "2024-09-11 15:48:56,779 - result_analysis.result_analysis - INFO - Number of entries after filtering 65887\n", - "2024-09-11 15:48:57,018 - result_analysis.result_analysis - INFO - Number of entries after merging 32320 and columns Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'sum_intensity', 'out_score', 'target_decoy_score', 'Decoy_y',\n", - " 'TD pair id_y', 'log_sum_intensity', 'Target', 'fdr',\n", - " 'N_identified_target', 'competition'],\n", - " dtype='object', length=123)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Data: Intensity_log sum_intensity_log , slope = 0.939 , intercept = -0.036 , PearsonR = 0.837 , SpearmanR = 0.822\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from result_analysis.result_analysis import SWAPSResult\n", - "\n", - "swaps_result = SWAPSResult(\n", - " maxquant_dict=maxquant_result_ref,\n", - " pept_act_sum_df=pept_act_sum_ps_full_tdc,\n", - " infer_intensity_col=\"sum_intensity\",\n", - " fdr_thres=0.2,\n", - " log_sum_intensity_thres=2,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-11 15:51:49,149 - result_analysis.result_analysis - INFO - Number of entries after merging 32320 and columns Index(['Sequence', 'Length', 'Modifications', 'Modified sequence',\n", - " 'Oxidation (M) Probabilities', 'Oxidation (M) Score Diffs',\n", - " 'Acetyl (Protein N-term)', 'Oxidation (M)', 'Missed cleavages',\n", - " 'Proteins',\n", - " ...\n", - " 'sum_intensity', 'out_score', 'target_decoy_score', 'Decoy_y',\n", - " 'TD pair id_y', 'log_sum_intensity', 'Target', 'fdr',\n", - " 'N_identified_target', 'competition'],\n", - " dtype='object', length=123)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Data: Intensity_log sum_intensity_log , slope = 0.939 , intercept = -0.036 , PearsonR = 0.837 , SpearmanR = 0.822\n" - ] - }, - { - "data": { - "image/png": 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", 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", 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/lf34giB43I/5yBVjFyxYgAMHDmDFihXIyMiAXq+HKIq49tprIYpit9TQkfcoNDQUcXFxrf7hnzhxAgkJCW59up1VXV2NiRMnIiQkBE899RR69+4NjUaDn3/+GY888ojbe9eZP9rGx3r44YcxY8YMj/tcGTDdyVtfSE154zX76t+ep/fL4XCgrKysTT8fERHhDOe4uDiPLayioiIAQHx8fCcqdTVhwgRcuHABv/zyC+rr63HVVVfh8uXLAIC+ffs691OpVPjXv/6Fv//97zh37hxiYmLQt29fLFq0CDzPd8lntdvCovGkrPPnz7vdd/bsWZfbvXv3xq5duzB27Fiv/ZFcefTjDY2Db7/++muzRyxVVVX49ttv8eSTT+Jvf/ubc7un96E9NSYlJbm9bwCcXTOeToLriDlz5uDtt9/Gvn37XLq8Gu3duxd5eXlYtmyZV56vqT179qCiogKffPIJJkyY4Nyem5vb5sdISkrC7t27YTQaXVoX2dnZLvs1HqEqlcpWjz69+Vm68nPAGEN2drZzALolSUlJOHHiBERRdGldXPkZaK7e9rxmKTX97pg8ebJzu81mQ25urkuXUUsuXrzoscXhye7du51nhmdkZGD37t2oqalxOSBqnBySkZHRpsdsK0EQXB5z165dAODxdxQTE+OcQOJwOLBnzx6MGjWqS1oW3TZmERcXh4yMDKxfv96l+2Dnzp1u/esLFiyAw+HA008/7fY4dru9Q2c4N54F6s2zo4cOHYqUlBSsWrXK7XEbj6waj7yuPNJatWpVp2qcNWsWDh8+jIMHDzq31dfX46233kJycrLbOFBHrVixAlqtFsuWLUNFRYXLfZWVlfjTn/4EnU6HFStWeOX5mvL03lmtVmcfblvMmDEDNpsNb7/9tnObKIp47bXXXPaLjo7GpEmT8OabbzqPGJtqekTqzc/Sv//9b5duvi1btqCoqKhNM4lmzZqF4uJifPjhh85tdrsda9asgV6vx8SJEwH8Npvmynrb85qlNHz4cERFRWHt2rXOPnmgYaZce34HHR2zmD9/PhwOB9566y3nNovFgnXr1mHUqFEuM6EKCgrcxtI6o6ysDM8//zyGDBnSaqD/85//RFFREf785z977fmb6tZuqOeeew6zZ8/GuHHjcPvtt6OyshJr1qxBeno66urqnPtNnDgRy5Ytw3PPPYesrCxMnz4dSqUS58+fx+bNm7F69WrMnz+/Xc+dkZEBQRDw/PPPw2AwQK1WY/Lkyc2Oi7QFz/N44403cN111yEjIwNLly5FXFwczpw5g5MnT+Kbb75BSEgIJkyYgBdeeAE2mw0JCQnYsWOHx6PjYcOGAWiYQrhw4UIolUpcd911Hpc7ePTRR7Fp0ybMnDkTy5cvR0REBNavX4/c3Fx8/PHHbv3YHdWnTx+sX78eN998MwYPHow77rgDKSkpyMvLwzvvvIPy8nJs2rTJ2crypszMTISHh2Px4sVYvnw5OI7Dhg0b2tXF8fvf/x4jR47En//8Z2RnZ6N///74/PPPnVMomx51v/baaxg3bhwGDx6MO++8E6mpqSgpKcHBgwdRWFiI48ePA2j5s9Q43XvdunVtWssrIiIC48aNw9KlS1FSUoJVq1YhLS3NZUC+OXfddRfefPNNLFmyBD/99BOSk5OxZcsW7N+/H6tWrXKOIWm1WgwcOBAffvgh+vbti4iICAwaNAiDBg1q82vurEmTJuH777/vUPeUUqnEM888g2XLlmHy5Mn4wx/+gNzcXKxbt67ZMQtPOjpmMWrUKNx444147LHHUFpairS0NKxfv975N9DUbbfd5vY6DQYD1qxZAwDYv38/AODVV19FWFgYwsLCcO+99zr3nThxIsaMGYO0tDQUFxfjrbfeQl1dHbZt2+byN/3+++/j448/xoQJE6DX67Fr1y589NFH+OMf/4gbbrih3a+xTbw+v+q/mjsp7+OPP2YDBgxgarWaDRw4sNmT8hhrmBo3bNgwptVqWXBwMBs8eDD7y1/+wi5fvuzcp/GkvCt5mg779ttvs9TUVCYIQrMn5TVCG6bONtq3bx+bNm0aCw4OZkFBQWzIkCFszZo1zvsLCwvZ3LlzWVhYGAsNDWU33ngju3z5ssfpjE8//TRLSEhgPM+3+aS8sLAwptFo2MiRI5s9Ke/KaayN0wivPCmtOSdOnGA33XQTi4uLY0qlksXGxrKbbrrJ49Rbb06d3b9/Pxs9erTzhK+//OUv7Jtvvmn2BDFPysrK2KJFi5wn5S1ZsoTt37/feVJcUzk5Oey2225jsbGxTKlUsoSEBDZnzhy2ZcsWl/2a+yytWbOGAWBff/11i6+16cljjz32GIuOjmZarZbNnj2b5efnu+zb0msrKSlhS5cuZT169GAqlYoNHjzY4+/0wIEDbNiwYUylUrl97trymls6Ke9Knv6ehw0bxmJjY1t8TxhreeWH119/3Xli6/Dhw1s8Ka+9n73WmEwm9vDDD7PY2FimVqvZiBEjPP6OG6cTN9XSlN0r36cHH3yQpaamMrVazaKiotiiRYs8Lnfz448/sgkTJrDw8HCm0WjYVVddxdauXesyZd/bOMZ8ZBSYkG702WefYe7cudi3bx/Gjh3rtcddsGAB8vLycPjw4Rb327NnD6655hps3ry53a1kuamtrUVERARWrVrlNmWZyIdPzoYixJtMJpPLRAmHw4E1a9YgJCQEQ4cO9drzMMawZ88evP/++157TH/www8/ICEhoU1da8R3UVgQv3fffffBZDJhzJgxsFgs+OSTT3DgwAE8++yzXp2SynGc23k0BJg9ezZmz54tdRmkkygsiN+bPHkyXnrpJWzbtg1msxlpaWlYs2aNy8AiIaRlNGZBCCGkVT5xWVVCCCG+jcKCEEJIqygsCCGEtIrCghBCSKsoLAghhLSKwoIQQkirKCwIIYS0isKCEEJIqygsCCGEtIrCghBCSKsoLAghhLSKwoIQQkirKCwIIYS0isKCEEJIqygsCCGEtIrCghBCSKsoLAghhLSKwoIQQkirKCwIIYS0isKCEEJIqygsCCGEtIrCghBCSKsoLAghhLSKwoIQQkirKCwIIYS0isKCEEJIqygsCCGEtIrCghBCSKsoLAghhLSKwoIQQkirFFIXQIgUbA4bLA4LrA4rLHaL8/+tDitEJrrtz4EDx3EQOAECLzj/y3M81IIaWqUWOqUOCp7+pIh/ok828StGmxE1lhoYzAbUWGpQY6mB2W5uCIUm4cDAuuT5lbzSGRxahdbl/3VKHbRKLYJVwdAqtV3y/IR0FY4x1jV/NYR0kaaBYLAYXMLBJtqkLq9NNAoNIrQRCNeEI1wbjghtBCK0EVAJKqlLI8QjCgvi0yx2C0rqS1BaX4qSuhKUGctgdVilLqvLBCmDnOERrvktRARekLo0EuAoLIjPYIyhylyFkroSZ0BUm6ulLktyAicgOiga8cHxiA+OR3RQNIUH6XYUFkQyDtGBoroiFNcVo7S+FKX1pX7davAWBa9wCw+eo4mNpGtRWJBuVW+tR4GhAAWGAlyqvQS7aJe6JNlT8ArE6mMRp49zhgfHcVKXRfwMhQXpcuXGcuRW5SLfkI9KU6XU5fg9jUKD5LBkpISlICEkgVodxCsoLIjXMcZQUl+C3Kpc5Fbnos5aJ3VJAUslqJAYmojU8FT0CulFYx2kwygsiNdUmipxpvwMcipzYLKbpC6HXEElqJAcloy0iDQkBCdQVxVpFwoL0il20Y7symycKT+D0vpSqcshbaRT6pAanoo+EX0QFRQldTlEBigsSIeU1ZfhTPkZZFdmy+ZEOOJZlC4Kg6IHoXdEbxrfIM2isCBtZnVYcb7iPM6Un0GFqULqcoiXaRVaDIgagIFRA6FT6qQuh/gYCgvSqtL6UpwqO4ULVRdoqmsA4DkeKWEpSI9OR6w+VupyiI+gsCDNulRzCceKj+Fy7WWpSyES6aHr0dBFFd6bZlIFOAoL4qbAUIBjRcdQUl8idSnER2gUGgzoMQCDYwZDo9BIXQ6RAIUFccqrzsPPRT+j3FgudSnERyl5JQbHDMaQmCG0Qm6AobAIcIwxXKi6gGPFx+jsatJmakGNjNgMpEen0wWfAgSFRYASmYjsymxkFWfRyq6kw3RKHa6OvRoDogbQtFs/R2ERgAoMBTh48SAMFoPUpTgJjIOa46FmPNQcDxXjoAIHpchBCUDBAKXIwDEGcBwYGlpF4NBwm6Hh/wEwACLHwc4BVg6wQoSNAyycCCNEmJgDDo4+9t4UrArGsPhh6BPRh84M91MUFgGkxlKDAxcPoMBQIMnz6yAghAkIZgKCRA4akUFjd0Blt4MT3a973ZVEnoNdUMAmCDAJHOp5oIYXYYAd9ZyjW2vxJ2GaMAyPH47U8FSpSyFeRmERAGwOG44VH8OJkhMQWdd/KeuhQA+mQKiDh9YZCDZwojw+aoznYVEoYFYIqBc41PEiqjkHqkFnqrdVlC4K45PGo4euh9SlEC+hsPBz2ZXZOFR4CEabsUseX8k4RDEVejABwXYRWqsNgsM/j8xFnodRrUK1gkeF4EAZs1J3Vgs4cEiPTseI+BFQCkqpyyGdRGHhp8qN5Thw8QCK64q9+rgq8IhnakQ4OIRY7VBbA/fKdozjYFapUKMUUCGIKOGssKJ7u9PkIEgZhLGJY5Eclix1KaQTKCz8jNluxpFLR3Cm/AwYvPOrDWVKJDAlIq0O6CwWeOlh/ZJFpUKlSsBlhQPlCNwg9SQ5LBlje41FkCpI6lJIB1BY+JFzFedw8OJBWByWTj0ODyCWqRHjEBBusUFpo776jrArFKjSqFAsOFAECxhNEoKSV2J4/HAMih5Es6ZkhsLCDxhtRuzN34t8Q36HH0NgHBKZBjF2INhsAd/Ns5P8nUMQUKNRoUTBcImzwB7gzbMeuh6YkDSBBsBlhMJC5nIqc7D/4n6Y7eYO/XwUUyHJLiDcRAHRXRjPoUajwSUlQyHMAdvi4MBhUPQgjEgYQWeBywCFhUyZ7WbsK9iHC1UX2v2zGvBIcWgQYwnsAWpfYBcUKNeqkKuwogaBufx7mCYMU1KmIFIXKXUppAUUFjJ0ufYyvsv9rl3TYTkG9IQGPa1AiNlMg9Q+yKhR46KaRwFnCrg5VQInYGTCSAyOGSx1KaQZFBYyIjIRRy4dwYmSE22e6aRmPPqKGsQYLX57/oO/cQgCSrQqXBCsAXc2ea+QXpiUPAlapVbqUsgVKCxkwmA24Lvc71BmLGvT/joI6GdXI8po7valNIiXcEC1VouzKntAnT2uVWhxTco16BnSU+pSSBMUFjJwoeoC9uTtadMlTUOZEn3tCkQYTdTV5EcMOi3OqeyoDJDQ4MBhaNxQDI0bSlNsfQSFhY87cukIjhUfa3W/HlAhzSog1GjqhqqIVGq0GpxXiwFzwl/PkJ6YnDKZrs7nAygsfJTNYcPuvN3Iq85rcb9YqJFm5hBk7tjUWSJPdf8NjdIACA2dUoepqVMRq4+VupSARmHhg2osNdiRs6PFK9eFQYmBFgHBJgqJQFav0eCcxv9Dg+d4jE8cj349+kldSsCisPAxl2svY9eFXc2eZKeDgIE2FSLrqbuJ/KYqSItflVYY4d+zp4bGDcXw+OFSlxGQKCx8yMnSkzhYeNDjNScExmGAqEV8Pc1uIp4xnselIDVOC/59nkZaRBomJU+iy7h2MwoLHyAyEfsK9uFM+RmP9ycxDdLq7VDYA/MMX9I+NqUS53UCLnL+20UZp4/D9N7ToVaopS4lYFBYSMxsN2NHzg6P150IZ0qkWwQavCYdUqfR4Fe1AwbOP6fbhmnCMDNtJoLVwVKXEhAoLCRUZ63DtnPbUGOpcdnOMWCgqENCnQkc/XpIZ3BAaZAOvwom2Pzwqn5ahRYz0mYgOiha6lL8HoWFRGosNdh2bhvqrHUu28OZEkNMHDS0wB/xIptSgVNBAorRuWud+CIFr8DklMl0Jb4uRmEhgWpzNbad2+ayECC1Jkh3KNHr8Itg8rtrh3PgMLrnaFqIsAtRWHSzCmMFvjz/pcvUWGpNkO5kUanwixao4Pzv8zY8fjiGxg2Vugy/RGHRjUrrS/HV+a+clz2l1gSRDAcU6rU4xZv87uJLI+JH4Oq4q6Uuw+9QWHSTotoifJ39NWxiw8yUYKbAUDMPjcX/ju6IfJjUamRpHX534aWRCSOREZshdRl+hcKiGxTWFGJHzg7nqrE9mQYDaq10GVPiExjPIU+vwTnev1YFGN1zNIbEDJG6DL9BYdHF8qvzsevCLjhYwzIMQxw6xNW2/Qp3hHSXqiAtflaaYfejte3H9BxDg95eQmHRhfKq87Drwi6ITISa8RhuVUFPC/8RH2ZRqfCTVkQt5z/dUpm9MjEoepDUZcgehUUXKa4rxpfnvoSDORDJVMioF2m5DiILIs/jdLAKhX60XMi4xHEYGDVQ6jJkjcKiC1SZqvD52c9hcViQxrRIrTWDE+ltJvJyMUSHU7z/dJmOTxyPAVEDpC5DtigsvKzeWo+tZ7fCaK3DUJuWlhInslYVpMVPCrPfnMQ3MWkiXROjg2iNXy+yOqz4KvsrmK31yDRrKCiI7IXXmzDWrIKWCVKX4hV7C/biUs0lqcuQJQoLL3GIDuzI2QGjqRpjTUpaKZb4Da3Fgsx6DiFQSF1Kp4lMxM4LO1Ftrpa6FNmhsPCS3Xm7UVNbijH1Ap1oR/yOwm7HyFqGCCilLqXTrA4rvs7+utmrURLPKCy84MDFA6iuuojRtQwqm39eO4AQweHAsBoHYpj8LzhUY6nBzpydHq9KSTyjsOikEyUnUF56HsNqHBAc/n39Y0J4UcRVtVYkMI3UpXRaUV0Rfsj/QeoyZIPCohNyKnNQdDELQwy0dAcJHJzIMKjGjGQ/CIxzFeeQVZwldRmyQGHRQZWmSlzKPYz+BjOtGEsCDwP6GcxIY1qpK+m0w5cOI686T+oyfB6FRQdYHVZkn/8BSdW1UpdCiKR6G0wY4NBJXUanfZf7HcqN5VKX4dMoLDogJ3svYspKpS6DEJ+QWGuUfWDYRTu+yf7G5eqVxBWFRTsVFxyHrjBH6jII8SmJtUbZd0nV2+pphlQLKCzawVx+EZbsw1KXQYhP6l1jQqLMB71L6ktw9PJRqcvwSRQWbeQoL0H5L7sAGswmxDMG9K+xIE7m52FkFWehsKZQ6jJ8DoVFG7CKCpT/+i0cIp1wR0hLOMYwqNaGSKaSupRO2Z27GyYbre3WFIVFa2pqUJO1G2ZHndSVECILvCji6jqHrNeSMtlN+C73O9Ci3L+hsGiJ0Qjzvl2oRqXUlRAiK4LDgRF1gA7yXa32Uu0l/FL6i9Rl+AwKi+Y4HBB37UCFulrqSgiRJYXdjpFGASoZf80cvnQYlSY6WAQoLJq3bx+qVLWwgy6FSkhHqa1WDLfId/xCZCK+y/0ODpHWfaOw8OT0aZhL8lCnpAEuQjor2GTGYBmftFdpqsSRy0ekLkNyFBZXKisDO3QQlZF0Yg4h3hJfa0QvGZ+DcaLkBC7XXpa6DElRWDRlNgM7d8IQo4INNE2WEG/qX2uV9QypH/J/COjuKAqLRowB334LKyyoUdP6MIR4Gy+KGFbPQQFO6lI6pMZSE9DLmVNYNDpyBOzSJVRGc6CZ1YR0DZXNhuFW+XZHZRVnocZSI3UZkqCwAIC8PCArC7WxWlg4un42IV0p1GhCukwHvB3Mgf0F+6UuQxIUFgYDsGcP7BoFqoPoAu6EdIeetUbEy3QNqYs1FwPyYkmBHRZ2O7BzJ2C1ojJOAUYdUIR0m4F1dqiZPL+CDlw8ALsYWOdgyfM35S179wKVlaiP0sLEU6uCkO4kOBy42ibP1kWdtQ4/F/0sdRndKnDDIj8fOH8eooJHVQiNUxAihVCjCamiPAe8T5ScQLW5Wuoyuk1ghoXNBuzbBwCoidXAgcCdO02I1HrXWaGX4fkXIhOxr2Cf1GV0m8AMix9/BOrr4VAJqFVT9xMhUuJFERlm+YUFAFyuvYzsymypy+gWgRcWJSXAqVMAAEOsGiJoWQ9CpBZkNqOPKM9reB8qPBQQg92BFRaiCPzwAwDArlGgTklnahPiK5LrLAhi8rv+hdFmxOmy01KX0eUCKyyOHQOqqgAA1TFKmihLiA/hRREZVqXUZXRIVnGW37cuAicsqqsbwgKANUiJegUtP06Ir9GbzEiRYXeUyW7CqbJTUpfRpQInLH74oaEbCoAhWn5NXUICRarRJsvFBv29dREYYXHqFFBcDACwhKhgpBPwCPFZCrsdAxzya12Y7WacLD0pdRldxv/Dor4eOHzYebO6h/yOWAgJNHH1JlkOdh8vOQ6bwz+vheP/YbF/P2BtOEPbFK6BmbNIXBAhpDWcyJAuw8Fus92Mk2X+2brw77AoLW1Yfvy/qiPonApC5CLcZEY0VFKX0W4nSk74ZevCv8PiyG8XWTeHqmAFrQFFiJwMkOGkRbPdjF9Lf5W6DK/z37AoKgIuXXLerA3335dKiL/SWKzoLcOptCdKTsDq8K+DU//9Bm3SqrBrFDAKNAOKEDlKrpffVFqLw+J3Z3X7Z1gUFjqnygJAbZT8+j0JIQ0UDjv6yXAq7elyCgvfd/So839FnkOdiloVhMhZnNEiu9ZFjaUGFw0XpS7Da/wvLAoKGmZB/Vd9FK0sS4jcCQ4H0mQ4duFPS4D4X1g0aVUAQK2egoIQf5BQb5XdF1aBoQB11jqpy/AKub33LcvNBcrLnTfNYWrYaLosIX5B4bDLbmYUA/ObgW7/CQvGgJ9+ctlUGy6vPk5CSMt6mWzgZHZtgTPlZyAy+fdw+E9Y5OQAlZXOm3atghYMJMTPKG12pEBerQuT3YS86jypy+g0/wmLrCyXm7U9aLosIf4o0eSQuoR284eBbv8Ii+Jil1YF40DTZQnxU2qrFYlMI3UZ7XK59jKqzdVSl9Ep/hEWZ8643DSHa2i6LCF+LNkss4ELyL91If+wsFqBCxdcNtUHS1QLIaRbaC0WhDN5LWF+ruIcHKL8utAayT8szp0D7L9dypDxHEwKmi5LiL9LccgrLKwOKy7WyPeMbvmHxRVdUKZwOmObkEAQYbLI7gsspzJH6hI6TG7vtauSEpeBbQAwBtO5FYQEAsHhQKIor4HuAkMB7KK99R19kLzD4rTrmZGM52AS6LKphASKBKu8Brptok22iwvKNyw8DGxTFxQhgUVvtiCYKaQuo11yquTZFSXfsDh/3mVgG6AuKEICUYoorxNw5doVJd+wuKILSuQ5uhoeIQEoymiV1XpRdtGOSzWXWt/Rx8gzLEpL3Qa2TREaMMjoE0MI8QqFw46ekNdAd74hX+oS2k2eYXHunNsmo16COgghPiHeJq8u6PzqfDAmr4NbeYZFQYHLTcYBJuqCIiRghZjldc6FyW5CaX1p6zv6EDm9vw0qK4E61ytPWULU1AVFSADjRRHxMltcUG5dUfILiytaFQBg0QsSFEII8SVxdnl1RRUY3L/LfJn8wiLfPY3NKvkuzkUI8Y5Qs7xmRVWZqmB1yGcdO3mFhdncMBOqCcYBFl4+bzghpGsIDgdiOLXUZbQZA0NxXbHUZbSZvMKisLDhWttN0HgFIaRRrF1eXdIUFl3F03hFkLxeAiGk64RZ5XVmNIVFV2AMuOi+AJdZQ60KQkgDtdUKPeSzVlRpfalsLogkn7AoKQEsrivKMg6wcLTKLCHkN/GifC6KJDJRNudbyCcsPHVB0XgFIeQKEfLqiZJNV5S8w4LGKwghVwiy2qQuoV0oLLyprs5t4UCAxisIIe4UdjuCmHxmRZXUl8hinSh5hEVJidsmGq8ghDQnCvK5xoXVYUWFqULqMlolj7AoL3fbZNcqabyCEOJROI1beJ08wqLCPXVtOvk0Mwkh3SvYJo/pqI3K6sukLqFV8ggLDy0Lm1oepRNCup/WZoUC8llYsNpcLXUJrfL9b9y6uoY1oa5gU4gSFEMIkQUGRDH5jFsYLAapS2iV74eFhy4oALAK8mpmEkK6V4Qon65qq8OKemu91GW0yPfDwkMXFANg52Q2gkUI6Vahdnn1Pvh6V5Qsw8Kuo5lQhJCWaWR2ch6FRWd5mgmllU/zkhAiDaXDAYHRILe3+HZYmM1u19sGAJtaPh8AQoh0Qjn5rEBLYdEZHrqgAMCmpC4oQkjrQmS07AeFRWc0MxOKps0SQtoiSPTtr7im6m31sDl8d5zFt99JD2HBANjgu28oIcR3BIny6oXw5daFb4dFba3bJodaoJlQhJA20dD0Wa/x7bAwGt02iSr59EESQqSlssvrfKxaq/sBsq/w7bAwmdw2ORS+XTIhxHcIDgfUMpo+a7a7L23kK3z3m9dqBTwcFYgK+fziCSHSC5PRtS0oLDrCQxcUADgoLAgh7aD14a+5K1FYdEQzYSGjtcEIIT5ALaP5MBQWHdFcy0KQ0W+eECI5FY1ZeIXvhoWHwW0AEHkKC0JI28lpwQcKi45ormXByeg3TwiRnFJGJ+bZRTvsom9O95VdWIicvE6yIYRIS8HkExaA77YuZBcWDtAV8gghbacQ5XWASWHRXh7CgnGACHn94gkh0hIoLLzCd8PCwwA3LfVBCGkvwSGv3ggKi/bydPY2L58pcIQQ38CLDHKaF2N1WKUuwSOfuIxUcnIy8vPz3bb/z8SJeG3RIkx66SV8f+6cy32L5kzAsw/c3F0lki728vovsHrDNpdtqb1i8N26pwAAf3joJfx4ouXPQPLUZW6P+8rjf8T114xw3v731t1Yv3UPCosrkBAdgXsWzcQN08d486UQH6QCD4uHLuxzP5/Djg07UHC6AIZyA+7+593ImJThvH/ZcPfPFADMWz4PM26bAQDY/s52/LL/F1w8exEKpQKr9qxy27+yuBIbn9uIs0fPQqPTYPSc0Zh7z1wICvfeEuajA/I+ERZHjhyBo0lT8ddff8W0adNw47Bhzm13jhuHvy68ASXRDdey0Krls94LaZu+yfF4/4UHnLcVgusf0k2zxuHBJdc7b3v6DLy4YjEmjkh33g7R65z/v+Hz7/HCO5/huQdvwVX9kpF1Ng+P/d8GhAbrMHXMVV58JcTXcM10SlhNVvTs0xNjrx+LtSvWut3/wtcvuNz+9cCv2PD0BgydPNS5zW63Y9iUYUgdnIr9W/e7PYboELHm/jUIjQzFI+8+AkO5AeueWAdBIWDuPXPd9vfVSzD4RFhERUW53P7Hc8+hd1QUJvbt69ymU6kQGxYKFkEXPvJXgsAjOiK02fs1GlWL9wMN4dDcPp/uOoRFs8fjuv+2NBLjo3DibB7W/ucbCgs/xzEO8BAYg8YOwqCxg5r9udAerp+l498fR9/hfRHV87fvrOuXNRzAHPjigMfHOHXoFIpyi/Dg6w8iJDIEvfr1wvV/uh6frPkE1911HRRK169hkfnmgLzPjVlYrVa8v3Ejbs/MBNfkcGDj4cOI/9NyTP/jk3j+X5/CZPbNfj3ScXmXSjHyD3/B+Fsex/3PvoNLJZUu92/99jCunvdQi5+Bv72yCVfPewi/u+c5fPTVfpcmvdVmh1qldNlfo1Li+Nk82OzyGgQl7dNcy6I9aipq8Mu+XzDud+Pa9XMXfrmAhLQEhESGOLelj0mHud6MyzmX3fanbqg2+uyzz1BdXY0lmZnObYtGjEBSZCR6xPfAPkMe/vH2J7hQWIw3V94tYaXEmzIGpOCfK5YgtVcMSisMWL1hGxY8+CK++dcT0Os0+N3kEUiIiURMZBjO5BZ6/Aw8tOR6ZGb0g0atwt6fTuGvr3yAerMFS+dOBgBMGD4Q//lqH6aPzcCgPon45Vw+/vPVftjsDlQZ6hAd2XKrhcgX76lZ0U4Htx2EJkiDq6+5ul0/Z6gwICQixGVbY3DUVNS47U/dUG30zjvvYOaMGYgPC3Nuu2vCBACAJUSFHlExiI4IxaIVLyP/chmS4qOaeSQiJ9eM/K0rYEBqT2QMSMG4RY/hy++P4g8zx2HRnAnO+/unJnj8DCy/ZbZzn0F9EmEyW/HWRzucYbH8ltkoq6zB3Pv+AcaAHuEhuGH6aLz54Q5wNNPOvzHmsRuqPfZ/vh8jrx0JpVrZ+s6dQN1QbZCfn49du3bhj3fc0eJ+Gf1TADR0WxD/FKrXIaVnDPIulXm8vy2fgYz+KSgqq4LF2jDOpVGr8OKKxTj95avYt/FZHPjgOfSM6QG9ToPIUL33XwTxHZ3shzp/7DxK8ksw7vft64ICgNDIUNRUurYgGlsUTbumGvGcT30tO/lUVevWrUN0dDRmz5nj8f7GudKnci4CAHUb+LF6kxn5RWXN/o7b8hk4lXMRocE6t3EKpUJAXFQ4BIHHF3uOYPKoweB5n/pTIF4mdrJrZ//W/UgckIhefXu1+2dTB6fiUvYll8A49eMpaII0iEuNc9uf80KXWVfwmW4oURSxbt06LF68GArlb3/cOWVl+ODwYcwaNAjB0WH4ITsPT7/xEUYO6YMBqT0lrJh409/f3IIpo4cgISYCpRUGvLz+Cwg8j+uvGYH8y2XY+t1hXDNyEMJCgnDmwiW3z8Cug8dRXlWLqwekQK1SYu9Pp/Hapq9w543TnM9xobAEx8/kIqN/Cgx1Rvxryy6cy72Ml/6yRKJXTboLY/DYDWU2mlF28bfWa/mlclw8exFBoUGIiI0AAJjqTPhp10+Y/8B8j49dWVyJekM9KosrIYoiLp5tOJCJ6hUFjU6DgaMHIi4lDuv+tg7zls9DTUUNPn/jc0xaMAlKlXuXFueN0fgu4DNhsWvXLhQUFOD22293aTKqBAG7Tp/Gqm+/Rb3VgrjoCMwcPxT33jxLwmqJtxWVVWH5s/9CdU09IkL1GD4oDZ+ueRSRYcGwWG3Y9/NpvPvxtzCaLYj38BlQCAL+vXUPnn7jIzAGJCVE4a9/uhE3zfqt20B0iHh78y5cKCyGUhAwOqMfPn7lL+gV20OKl0y6EWvmFO78U/n4vz/9n/P25pc3AwDGzBmDJSuXAACO7DgCxhhGXjvS42N8vvZzHNx20Hn7mZufAQA8tPYh9BveD7zA495V9+KD5z7A80ufh1qrxpg5Y5xTbq/kq91QHPPVeVr/+hdwxQJgNp0Cl+N8c613Qojv2h3GwyqTRUjH9hqL9Oj01nfsZr4ZYQDgqQ/ZN2ONEOLj5BIUgO+2LHyzKgBQuS/lwNvl8wsnhPgGhyCv1arVCrXUJXjku2Gh1bpt4m0UFoSQ9nHIbKabRqGRugSPfPdd1OncNnEABMjrKIEQIi0KC+/w3XfRQ1gAAO/DJRNCfI9dZmfnU1i0VzNhITDfLZkQ4ntsPnreQnMoLNqruZaF6LslE0J8j5xaFipBRbOh2s3DADcACDTGTQhpB6t8ssJnWxWAL4dFsy0LGf3mCSGSs8roAtwUFh3R3JiFXT6/eEKI9GwUFl4hu7Dg6YJmhJB2qOPk03dNYdERCoXHs7gFOjGPENIO1bBJXUKbUVh0lKezuGnJD0JIG9kFAXYZLSpHYdFRHrqiBCuFBSGkbaxKn7kKQ5uEqN2vnOcrfDssQtzfOMHqoLO4CSFtYhTk9V0RpgmTuoRm+fY72cPzRWmUrGsvmE4I8Q9GGZ2Qx4FDqNp3LxXt22ERGelxs9Lh22UTQnxDHS+fbutgdTAE3ncXSvXtb93ISJdLrDZSyumUTEKIZAyQz5U1fbkLCvD1sFAqgVD3ZpnSLJ+jBUKIRDigjqOw8BbfDgvAY1eU0iifedOEEGlYFUoZXUyVwqLzPAxyKyw0I4oQ0jKj0nf7/z2hsOisZmdEyWv+NCGkexkEeY1thmvCpS6hRb4fFs3OiJLXUQMhpHuVC/JZSE6j0ECtUEtdRot8Pyw0GkCvd9ustMnrqIEQ0n0Yz6ESVqnLaDNf74IC5BAWgMeuKKVZPkcNhJDuZVKpZDW47etdUIBcwsLjjCj5TIkjhHQvg0IeX22NooOipS6hVfJ4Rz3NiDI7IIDGLQgh7ipldOY2AMTqY6UuoVXyCIvYWI9ncqtFWiOKEOKujJPPuVhahRahGt9dE6qRPMJCrQZiYtw3m+VRPiGk+1iVClhkdHW8uOA4qUtoE/l82yYmum3S1Mjn6IEQ0j3qVPLqcZBDFxQg87BQ1dvoTG5CiItymQ1lUlh4W0SEx/MtNKL7dboJIYHrMmeRuoQ2UwkqRGo9n3jsa+QTFoDH1gWNWxBCGpnUalmNV0QHRYPzMHnHF8nrm5bGLQghLahQyasPKk4vj8FtQG5hER8PKFwXEKRxC0JIoyJBXgePchmvAOQWFgpFQ2BcgcYtCCE2pQKVkE9Y8BwvizO3G8krLADP4xYmefT5EUK6TqXMpsxGB0X79DW3r+QXYaGpo0UFCQl0l5Xy+h5IDHX/LvNl8gsLvR4Id12hUVVnpXWiCAlgdkGBUhktSQ4AyWHJUpfQLvILCwBITnbbpLXTuAUhgapaI68uqFB1qCyuYdGUPMOiXz+3TTqDfOZWE0K8q0Ahr0sWJIUlSV1Cu8kzLEJCgIQEl02aagt1RRESgCwqlaxWmQXk1wUFyDUsAGDAAJebHACdjbqiCAk0xRpF6zv5EI1Cg5gg91W0fZ18wyI5GdBqXTbpDPKaDUEI6RzGccjlzFKX0S4pYSmyWeKjKfmGBc8Dffu6bFIbaFYUIYHEoNXIai0oAOgd0VvqEjpEvmEBAP37u9ykrihCAstFpbyCQqvQymo9qKbkHRahoW7Lf9CsKEICg02pkNVy5ACQEi7PLihA7mEBuA10awwWCJDXgBchpP1KZHZuBQCkhqdKXUKHyT8sUlIAjcZlk84qvw8RIaR9cgV5nbGtV+ll2wUF+ENYeBjoDqqhrihC/FmNVgMj5DX7cUCPAbLtggL8ISwAt64otcECBXVFEeK3slXyOiDkOR79e/RvfUcf5h9hERrqdkZ3sIlmRRHij+o0apRx8uqCSg5LhlapbX1HH+YfYQEAQ4e63AwqM4ODfJt8hBDPctVSV9B+A6MGSl1Cp/lPWMTFAT17Om8KNhFBNk0LP0AIkRuTWi276bJhmjDEB7tf4VNu/CcsAGD4cJebwZXyWomSENKyXI38egv8oVUB+FtYREe7XElPVWeDhsmwzUoIcWNRqXBRZutAKXgF+kb2bX1HGfCvsADcWxcG+R2JEELc5Wnlt+5bWkQaVIJ/TLbxv7Do0aPhRL3/0laYaRotITJnVSqRD5PUZbSbv3RBAf4YFgAwbBjw35NfONA0WkLk7qJOASazToIoXRR66HpIXYbX+GdYREQAqb+twaIvpWm0hMiVRaVCjgxbFenR6VKX4FX+GRaAS+uCt4vQ0zRaQmTprJaTXasiRB2CtIg0qcvwKv8Ni7AwoE8f583gcppGS4jcGHRaFMnsvAoAGBo3FDznX1+v/vVqrjR0aMNCgwCURhu0IrUuCJELxnE4qbRJXUa7hahD0CeiT+s7yox/h0VICJD+W79hWJm8VqkkJJCVBGlRy8mvR2Bo3FBZry7bHP8OCwAYMQLQ6wE0nKQXZKfWBSG+ziEIOCXIb1A7VB3ql60KIBDCQqEAxo933gwrtdO8KEJ8XJ5eBRvHpC6j3YbFD/PLVgUQCGEBAL16AWkNMxMUJjv0NnkvFUyIPzOrVMjm5NeqCNOEoXd4b6nL6DKBERYAkJnpvPxqaImVzrsgxEed0crzb9NfxyoaBU5YaDTA6NEAAMHiQIiFWheE+JoyvQ4lMpwqG64J9+tWBRBIYQE0XKv7v9e8CCk2gw+wl0+IL7MpFTihkF/3E+D/rQog0MICaBjsVijA20WEGmn5ckJ8xRmdADvkN6gdqY1Eanhq6zvKXOCFRXCwcxnz4BIzBFqRlhDJVQRpZXcFvEbjEsf5fasCCMSwAIDBg4EePcCJDKF1FBaESMmmVOC4Ql4XNWrUL7IfYvQxUpfRLQIzLDgOmDAB4HnoS81QQil1RYQErJM6QZbnVKgFNUb1HCV1Gd0mMMMCaLhI0tCh4BgQWR64bwMhUiqW6ewnABiRMAIaReCsCBHY35JDhwKJiVAbLAimE/UI6VYWlQq/KIxSl9EhUbooDOgxQOoyulVghwUATJ4MhIQg7LKFBrsJ6SYiz+OYlkGUupAO4MBhfNL4gBjUborCQqUCpk0DDx4R1RQWhHSHs8EqGDj5LT8OAAOiBvjV5VLbisICACIjgfHjoaswQ+eg7ihCulJRsA4FnDxnP2kUGoyIHyF1GZKgsGjUpw8wcCAiLlvpzG5CukidVoMTgjzHKQBgdM/RUCsC82Re+lZsKjMTQngPhNeqpK6EEL9jUypwRG2VuowOi9XHom9kX6nLkAyFRVM8D0ydCn0tBw0LzKMHQroC4zkc03GwynJIG1DwCkxMmih1GZKisLhSUBAwZQoiShgtY06Il5wL1qBKpgPaQEP3U6gmVOoyJEVh4Ul8PJSDrkaoiQa7CemsEr0OeTK8mFGjxNBEDIwaKHUZkqOwaM5VVyFEFwc1o/ELQjqqRqvBcRkPaGsUmoDvfmpEYdECbtI16IFYmh1FSAcYNWocVlnAZNybOyFpArRK6mEAKCxaxvNQTJyCSCFO6koIkRWLSoUfNTY4ZLhAYKOBUQORHJYsdRk+g8KiNUoldKOnIFgTLXUlhMiCTanEIZ1dtjOfgIYLGo3pOUbqMnwKhUVbaDQIz5gKlTpY6koI8Wl2QYHDQQxmGQeFgldgSuoUCLwgdSk+hcKijbggPXpkXAtOQQPehHgi8jx+1nOog13qUjplXOI4hGnCpC7D51BYtINSH46gQZMg8vS2EdIU4zkcD1HI+lwKAOgT0Segz9JuCX3rtVNkZDJsaRkUGIT8F+M4nAxWoxTyXcoDaLhGxfik8VKX4bPoG68D+vQchtL4XmAUGCTAMZ7HryEqXJLpKrKN9Co9ZqTNgIKnyxQ0h77tOoDjOFzVeyLOR4ZSC4MELJHnkRWiwGWZXha1kZJXYkbvGdApdVKX4tPom66DNAoNMnpPQlaYBnYFHY2QwOIQBPwUIsi+64kDh8kpkxGpi5S6FJ9HYdEJUUFRGJ46EYf1HKxKpdTlENIt7AoFDgdzqIS8B7MBYFTPUUgKS5K6DFmgsOikXqG9MCx5LA7oHDCpaVlz4t+sSiUO6hlqZD49FgD69+iPITFDpC5DNigsvKBvZF8MThiKA1or6rQaqcshpEuYVSocDHLACIfUpXRafHA8xiWOk7oMWaGw8JKhcUPRN2oADqrNqAqihceIfzFq1Digtcn6zOxGoepQTEudBp6jr7/2oHfLi8b2GovEsGQcVppQoqeZFcQ/VARpsV9jgU3GiwI2UgtqXJt2bcBeR7szKCy8iOMaZlbEBMUgS2HEhRAtGCfj9ZlJYOOA/BAtjipNftCe+O8U2bQZAX/Fu47iGGPyP1zwMRa7BVvPbkW1uRo9oMJVdSIUdvkPCJLAIfI8TgYrZX8ORSMFr8CsPrMQq4+VuhTZorDoInXWOnx25jMYbUZowGO4WYUgs7zPciWBwaJS4Wed6BcznoCGoJiZNhNxwXRdms6gsOhClaZKbDu3DWa7GRwDBos6xNXK9xKTxP9V67T4SWWGHf7xtaDgFbg27VrEB8dLXYrsUVh0sWpzNbad2wajrSEkejEN+tdawYv+0AtM/AYH5AdrcYY3SV2J1wicgBlpM9AzpKfUpfgFCotuUGOpwbZz21BnrQMAhECBoUYeaqu8l0og/sGmVOLXIE72S3c0RUHhfRQW3aTOWodt57ahxlIDAFCAQ4ZNg8h6/zmSI/JTHqTFcaX/dDsBAM/xmN57OhJDE6Uuxa9QWHQjo82IL899iSpzlXNbPFNjQL2DZkuRbmUXFDijV8h+afEr8RyPaanTaL2nLkBh0c3MdjO2n9+OcmO5c5uScbjKTq0M0j2qdVocU1lg9YuzJ37Dczympk5Fcliy1KX4JQoLCVgdVmw/vx2l9aUu26mVQbqSQxCQrVchj/O/gxKVoML03tNp1lMXorCQiM1hw9fZX6OorshlO7UySFeo02pwTG3zi0UAr6RX6TEzbSbCteFSl+LXKCwkZBft2JmzExdrLrrdR60M4g12hQI5QUq/bE0ADdfNvjbtWmiVtHhnV6OwkJjIRBwqPIRfS391u0/JOKQ7tIiuN4GjXxNpB8ZzKNJpcFrhXzOdmkoKTcKU1Cl03exuQmHhI86Un8G+gn0QmfugYwgUSLcoEGLyr5krpGsYdFr8qrKhzk+W6/BkUPQgjOk5Bhwt1NltKCx8SHFdMXbm7ITJ7rnLIIFp0NfogMom/8tZEu+zqFQ4p+X8ZvE/TzhwGN1zNAbHDJa6lIBDYeFj6qx1+Cb7G1SYKjzezzEgjWmRVG+F4PC/wUrSfiLP46JejbOcCcyPD7QVvAKTUybT1FiJUFj4ILtox568PbhQdaHZfRTgMMChRVy9GRytMxWQRJ5HqU6DswqzX1zBriVahRYz0mYgOiha6lICFoWFD/u56GccvXy0xX004NHXrkaM0UKLEwYIkedREqTBWd4MC+f/v/NYfSympk6FTklXn5QShYWPy6vOw+7c3bCJLY9TKBmHPqIG8UbqnvJXDkFAkU6N84LZ786+bs5VMVdhRMIIul62D6CwkIFKUyV25uyEwWJodV+BcUhlGvQy2aC0+e9smEDiEARcDlLjHG/y22mwV1ILakxKnkRrPPkQCguZsIt2HLh4AGfKz7Rpf44BSdAi2eSgpdBlyq5Q4JJWifO8GQ4ucP5Mo4OiMSVlCoLVwVKXQpqgsJCZC1UXsDd/LyyOtk+PTGAaJFkYgs3+O6XSn9RpNShQAYUw+/Xspitx4JARm4Fh8cOo28kHUVjIUJ21Drtzd7utK9UaHQSkOFSINtvpXA0f4xAElGvVyBGsqOUCr/swSBmEySmT6TrZPozCQqYYYzhRcgJHLx+Fg7V/QDuGqZBoFxBustDUWwnVatS4pOZwkfP3ya/NSwlLwYSkCVAr1FKXQlpAYSFzVaYq7MnbgzJjWYd+XgEOyUyDOLMDOguNbXQHs0qFcrUCuYLFL1eBbSutQosxvcYgLSJN6lJIG1BY+AGRicgqzsLPRT97XFuqrUKgQIJDhR42B3QWCwJk4k3X44B6tQblKg4XOSvqucANiEb9e/THqIRR1JqQEQoLP1JhrMAP+T90uJXRlAo8EkQ1ou1AiJlO+GsvxnOoVatRquRQyFkC4uS5tgjXhGN80njE6mOlLoW0E4WFHzpTfgZHLh1pdkHC9uIYEMOpEWsXEG6x0eB4M2xKJWpVCpQIIi7z1oA5J6ItBE7A0LihuCr2KprpJFMUFn7K6rDi6OWjOFV2qlNdU54EMwWimRLhDkBvtUMdiOHBAWalCjUqAZUCQylsMFH3kkcJwQkYnzQeIeoQqUshnUBh4eeqTFU4cPEALtVe6rLnUDMe0VAhXOQRbBehtdr8bskRxvOoVylRo+RRwYso5ajl0BqNQoPMXpk0gO0nKCwCRG5VLg4VHkKttbZbnk8PBSKZAnqRg04E1HYH1HYRCodvn0PgEARYlAqYBB51AodaToSBs/v1hYS8jed49O/RHyPiR9AAth+hsAggdtGO48XHcbzkOOyiNF9+CnAIgQLBTIBe5KETGTQOEYLIIDhECMwBTuy6j6SD52FXKGDneVh5wMrzqBMYajgHqmEPmAX6ugIHDr0jemN4/HDqcvJDFBYBqM5ahx8Lf0ROVY7UpXgkMA5qjoeKcdBwApSMg4pxUIJD49AoY2hYCoMx55IYDL/N9hUBWDkGC8SGf5wIK0SKgi6SHJaM4fHDEaGNkLoU0kUoLAJYlakKx4qPIacyB4z630kHJAQnYETCCLooUQCgsCAwmA3IKs7C+crzXp85RfxTTFAMRiSMQHxwvNSlkG5CYUGcai21yCrOwtmKsxQaxKNIbSRGJIxAYmii1KWQbkZhQdzUW+txvOQ4zpSfkWwgnPiW+OB4DIoehOSwZKlLIRKhsCDNMtlMOFFyAqfKTrV6WVfifxS8An0i+iA9Op0GrgmFBWmd1WHF+YrzOF1+GpWmSqnLIV0sWBWM9Oh09IvsR+dJECcKC9IuZfVlOF1+GjmVOdTa8DM9Q3oiPSodiaGJ4LgAukQfaRMKC9IhNocNOVU5OFN+BqX1pVKXQzpIySvRJ7IPBkUPQpgmTOpyiA+jsCCdVmmqxJnyMzhfcb5d1wYn0uA5HgnBCUiLSENyWDKUglLqkogMUFgQr3GIDlyouoCcqhwU1hTS9FsfE6uPRVpEGlLDU6FRaKQuh8gMhQXpElaHFQWGAuRV56HAUEBTcCXAgUOsPhYp4SlIDkuGXqWXuiQiYxQWpMvZRTsKawpRYChAgaEARptR6pL8Fs/xiA+OR0pYQ0BolVqpSyJ+gsKCdLtyY7kzOMrqy2hdqk7gOR5RuijEB8cjPjgeMfoYKHiF1GURP0RhQSRlsVtQUl+CkroSlNSXoKy+jKbktoADh6ig38IhVh9L4UC6BYUF8SmMMVSaKl0CpMZSI3VZkuE5HpHaSMQHxyMuOA5x+jiavUQkQWFBfJ7ZbnZpeVSbq1Fvq5e6LK/iwCFEHYJwbTgitBGI0EYgXBOOUE0oeI5v/QEI6WLUfpXQe++9h6VLlwIA9u7di3HjxrnczxhDYmIiCgsLMXv2bGzbtk2KMiWnUWhw6dQl7NixAw888ADCwsJgF+2osdSgxlIDg9kAg8Xg/H9fDhIOHIJUQc4wiNBGIFwbjjBNGHUnEZ9Gn04foNFo8MEHH7iFxffff4/CwkKo1bQ+z4EDB/Dkk09iyZIlCAtr+GJtPAK/UtMgqbHUwGw3w+qwwmK3NPzXYXG57WCOTtenFtTQKXXQKrUN/1Vonf/f9LZWoaWlNIgsUVj4gFmzZmHz5s145ZVXoFD89iv54IMPMGzYMJSXl0tYnfy0FCSe2EU7rA6rM0Cam53FczwEToDACy7/rxJU1FVE/B59wn3ATTfdhIqKCuzcudO5zWq1YsuWLVi0aJHb/v/85z+RmZmJyMhIaLVaDBs2DFu2bHHZZ926deA4Du+++67L9meffRYcx2H79u3ObdXV1ViyZAlCQ0MRFhaGxYsXIysrCxzH4b333nPuN2nSJEyaNMmtniVLliA5ObndNQIAx3G499578dlnn2HQoEFQq9VIT0/H119/7dxn5cqVWLFiBQAgJSUFHMeB4zjk5eW5PV5HKHgFdEodwjRhiNHHIFYf6/FfdFA0InWRCNOEIUQdgiBVEDQKDQUFCQj0KfcBycnJGDNmDDZt2uTc9tVXX8FgMGDhwoVu+69evRpXX301nnrqKTz77LNQKBS48cYb8eWXXzr3Wbp0KebMmYOHHnoIFy9eBAD88ssvePLJJ3HHHXdg1qxZABrGRX73u99hw4YNuOWWW/DMM8+gsLAQixcv7tRrakuNjfbt24f/+Z//wcKFC/HCCy/AbDbjhhtuQEVFBQBg3rx5uOmmmwAAL7/8MjZs2IANGzYgKiqqUzUSQtqBEcmsW7eOAWBHjhxhr776KgsODmZGo5ExxtiNN97IrrnmGsYYY0lJSWz27NnOn2vcp5HVamWDBg1ikydPdtleVFTEIiIi2LRp05jFYmFXX301S0xMZAaDwbnPZ599xgCwF154wbnNbrez8ePHMwBs3bp1zu0TJ05kEydOdHsdixcvZklJSS7b2lojAKZSqVh2drZz2/HjxxkAtmbNGue2F198kQFgubm5bs9PCOl61LLwEQsWLIDJZMK2bdtQW1uLbdu2eeyCAgCt9rclHKqqqmAwGDB+/Hj8/PPPLvvFxsbitddew86dOzF+/HhkZWXh3XffRUhIiHOf7du3Q6FQ4O6773ZuEwQB9913X6deT1trBICpU6eid+/ezttDhgxBSEgILly40KkaCCHeQwPcPiIqKgpTp07FBx98AKPRCIfDgfnz53vcd9u2bXjmmWeQlZUFi+W3JcE9zbJZuHAh3n//fXz55Ze46667MGXKFJf78/PzERcXB73edZG5fv36der1tKfGxMREt23h4eGoqqrqVA2EEO+hloUPWbRoEb766iusXbsWM2fORFhYmNs+e/fuxfXXXw+NRoPXX38d27dvx86dO7Fo0SIwD+dXVlRU4OjRowCAU6dOQRQ7vmx4c1M+HQ7XqaftrVEQBI+P62lfQog0KCx8yNy5c8HzPA4dOtRsF9THH38MjUaDb775BrfffjtmzpyJqVOnNvuY99xzD2pra/Hcc89h3759WLVqlcv9SUlJKCoqQl1dncv2s2fPuj1WeHg4qqur3bbn5+d3qsa2oHMTCJEWhYUP0ev1eOONN7By5Upcd911HvcRBAEcx7kczefl5eGzzz5z23fLli348MMP8Y9//AOPPvooFi5ciL/+9a84d+6cc59Zs2bBbrfjjTfecG5zOBxYs2aN2+P17t0bZ86cQVlZmXPb8ePHsX///g7X2FZBQUEA4DGsCCFdj8LCxyxevBhPPPGEywBxU7Nnz4bRaMS1116LtWvX4qmnnsKoUaOQlpbmsl9paSnuvvtuXHPNNbj33nsBAK+++ipCQkKwZMkSZ3fUddddh7Fjx+LRRx/FPffcg9deew3Tp0+HwWBwe+7bb78dNpsNM2bMwGuvvYYnnngC06dPR3p6eodqbI9hw4YBAB5//HFs2LAB//nPf1Bf77vLehDidySejRXQmk6dbcmVU2ffeecd1qdPH6ZWq1n//v3ZunXr2BNPPMGa/jrnzZvHgoODWV5enstjbd26lQFgzz//vHNbRUUFu/XWW1lISAgLDQ1lt956Kzt27Jjb1FnGGHv//fdZamoqU6lULCMjg33zzTcep862pUbGGqbO3nPPPR5f8+LFi122Pf300ywhIYHxPE/TaAnpZrTqLPEoLy8PKSkpWLduHZYsWSJ1OYQQiVE3FCGEkFZRWBBCCGkVhQUhhJBW0ZgFIYSQVlHLghBCSKsoLAhpo19++QXz589HUlISNBoNEhISMG3aNOcJjAMHDsRVV13l9nOffvopOI7DxIkT3e579913wXEcduzY4bJ9+/bt4DgO8fHxzS7Rkpyc7Ly2B8dxiI6Oxvjx4/Hpp5+67CeKIv79739j1KhRiIiIQHBwMPr27YvbbrsNhw4d6ujbQQIMhQUhbXDgwAEMHz4cx48fx5133olXX30Vf/zjH8HzPFavXg0AGDduHH799Ve3Exr3798PhUKBI0eOwGazud0nCALGjBnjsn3jxo1ITk5GUVERvvvuu2brysjIcF7f4+GHH8bly5cxb948rF271rnP8uXLsXjxYsTFxWHlypV4/vnnMXPmTBw6dMjlIlOEtEja0zwIkYdZs2axqKgoVlVV5XZfSUkJY4yx9evXMwBs+/btLvePHj2aLVq0iAFgBw8edLmvb9++7Oqrr3bZVldXx4KCgtgrr7zCrr76arZkyRKPNV15siZjDdcwCQoKYn379mWMMVZcXMw4jmN33nmn28+LouisnZDWUMuCkDbIyclBenq6x5WAo6OjATS0LAC4rJVlNpvx888/Y968eUhNTXW5r6ysDOfOnXP+XKNPP/0UJpMJN954IxYuXIhPPvkEZrO5TXXGxsZiwIAByM3NBQDk5uaCMYaxY8e67dvYdUVIW1BYENIGSUlJ+Omnn/Drr782u09qairi4+Oxb98+57YjR47AarUiMzMTmZmZLmFx4MABAHALi40bN+Kaa65BbGwsFi5ciNraWnzxxRdtqtNms+HixYuIjIx01g0AmzdvhtFobNuLJcQDCgtC2uDhhx+G0WhERkYGMjMz8cgjj2DHjh1uYxBjx47F4cOHndv379+PlJQUxMXFuYVFY6g0DYvS0lLs2rXLee31xMREjBkzBhs3bvRYl81mQ3l5OcrLy3HixAncdtttKCkpwY033ggAiIuLw2233YYvv/wSPXv2xLx58/DSSy/hzJkz3ntzSGCQuh+MELk4fPgwmzt3LtPpdAwAA8CioqLY1q1bnfusXr3aZWxizpw57Oabb2aM/XZt8XPnzjHGGBszZgxLSUlxeY7Vq1czlUrFKisrndvWrFnjto2xhjGLxjoa/wmCwG699VaXa6A7HA726quvsqFDh7rsO3nyZFZYWOjdN4n4LQoLQtrJYrGww4cPs8cee4xpNBqmVCrZyZMnGWOM/fTTTwwA++c//8lEUWQRERHs9ddfZ4w1fGmHhISwdevWMZPJxFQqFbv11ltdHnvEiBFs3Lhx7Pz5885/+/btYwDYm2++6bJvUlISGzVqFNu5cyfbtWsXO3DggMcB+KbKy8vZ1q1b2cyZMxkANm7cOO+9McSvUVgQ0gmNy8yvXLmSMcaY3W5nwcHB7Pe//z07deoUA8CysrKc+0+bNo3dcccd7IcffnALgHPnzrm1FJr+mzBhgstze5oN1R4TJ05kANyWsSfEE0W39XcR4oeGDx8OACgqKgLQcJXA0aNHY//+/di3bx9CQkIwePBg5/6ZmZn48MMPnReCajpesXHjRiiVSmzYsMHtuuT79u3DK6+8goKCAiQmJnqt9u+//x5FRUXOgXBCmkMD3IS0we7du8E8LKO2fft2AEC/fv2c28aNG4eysjKsW7cOo0aNAs//9meWmZmJs2fPYuvWrYiMjMSAAQOc923cuBHjx4/HH/7wB8yfP9/l34oVKwAAmzZtalfdxcXFOHXqlNt2q9WKb7/9FjzPd+oKhiRwUMuCkDa47777YDQaMXfuXPTv3x9WqxUHDhzAhx9+iOTkZCxdutS5b2Nr4eDBg1i5cqXL44wePRocx+HQoUO47rrrwHEcAODHH39Edna28xK4V0pISMDQoUOxceNGPPLII22uu7CwECNHjsTkyZMxZcoUxMbGorS0FJs2bcLx48fxwAMPoEePHu18N0hAkrofjBA5+Oqrr9jtt9/O+vfvz/R6PVOpVCwtLY3dd999bmdB19fXM4VCwQCwHTt2uD3WkCFD3C5te9999zEALCcnp9kaVq5cyQCw48ePM8baNmZRU1PDVq9ezWbMmMF69uzJlEolCw4OZmPGjGFvv/02E0WxPW8DCWC0RDkhhJBW0ZgFIYSQVlFYEEIIaRWFBSGEkFZRWBBCCGkVhQUhhJBWUVgQQghpFYUFIYSQVlFYEEIIaRWFBSGEkFZRWBBCCGkVhQUhhJBWUVgQQghp1f8H6tVJCWajxdcAAAAASUVORK5CYII=", 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "from peak_detection_2d.utils import plot_target_decoy_distr\n", - "\n", - "plot_target_decoy_distr(pept_act_sum_ps_full_tdc)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 46, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "result_filtered.loc[result_filtered[\"delta_log_sum_intensity\"] < 0.05][\n", - " \"delta_log_sum_intensity\"\n", - "].hist(bins=20)" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy_count\n", - "1 1561\n", - "0 1177\n", - "2 457\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 47, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_378798/1046279344.py:7: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " result_after_compete_tdc[\"target_mz_rank\"] = result_after_compete_tdc.apply(\n" - ] - } - ], - "source": [ - "result_after_compete[\"Decoy_count\"].value_counts()\n", - "result_after_compete_tdc = result_after_compete.loc[\n", - " result_after_compete[\"Decoy_count\"] == 1\n", - "]\n", - "from postprocessing.compete_signal import get_target_mz_rank\n", - "\n", - "result_after_compete_tdc[\"target_mz_rank\"] = result_after_compete_tdc.apply(\n", - " get_target_mz_rank, axis=1\n", - ")\n", - "result_after_compete_tdc = pd.merge(\n", - " left=result_after_compete_tdc,\n", - " right=maxquant_result_ref[[\"mz_rank\", \"source\"]],\n", - " left_on=\"target_mz_rank\",\n", - " right_on=\"mz_rank\",\n", - ")\n", - "result_after_compete_tdc_exp = result_after_compete_tdc.loc[\n", - " result_after_compete_tdc[\"source\"] != \"ref\"\n", - "]\n", - "result_after_compete_tdc_winner = set(result_after_compete_tdc[\"winner\"]) - set(\n", - " result_after_compete_tdc[\"loser\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "476" - ] - }, - "execution_count": 48, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Number of decoys that are winners\n", - "len(result_after_compete_tdc_winner.intersection(decoy_mz_ranks))" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_tdc = pd.read_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH,\n", - " \"peak_selection\",\n", - " ps_dir,\n", - " \"pept_act_sum_ps_full_tdc_fdr_thres.csv\",\n", - " )\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_all = pd.merge(\n", - " left=pept_act_sum_ps_all,\n", - " right=maxquant_result_ref[[\"mz_rank\", \"Decoy\"]],\n", - " on=[\"mz_rank\"],\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy\n", - "False 2097\n", - "True 872\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_all.loc[\n", - " pept_act_sum_ps_all[\"competition\"] == \"winner\", \"Decoy\"\n", - "].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_378798/1344436282.py:9: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " pept_act_sum_ps_all_no_loser[\"log_sum_intensity\"] = np.log10(\n" - ] - }, - { - "data": { - "text/plain": [ - "Decoy\n", - "True 87954\n", - "False 87770\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 52, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_all_no_loser = pept_act_sum_ps_all.loc[\n", - " pept_act_sum_ps_all[\"competition\"] != \"loser\"\n", - "]\n", - "# pept_act_sum_ps_all_no_loser = pd.merge(\n", - "# left=pept_act_sum_ps_all_no_loser,\n", - "# right=maxquant_result_ref[[\"mz_rank\", \"Decoy\"]],\n", - "# on=[\"mz_rank\"],\n", - "# )\n", - "pept_act_sum_ps_all_no_loser[\"log_sum_intensity\"] = np.log10(\n", - " pept_act_sum_ps_all_no_loser[\"sum_intensity\"] + 1\n", - ")\n", - "pept_act_sum_ps_all_no_loser[\"Decoy\"].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 136, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-09-06 13:11:07> FDR after TDC: (Decoy\n", - "False 54928\n", - "True 25967\n", - "Name: count, dtype: int64, 0.47274614040198076)\n" - ] - } - ], - "source": [ - "from peak_detection_2d.utils import compete_target_decoy_pair\n", - "\n", - "pept_act_sum_ps_all_no_loser_full, pept_act_sum_ps_all_no_loser_tdc = (\n", - " compete_target_decoy_pair(pept_act_sum_ps_all_no_loser, maxquant_result_ref)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy\n", - "False 77163\n", - "True 40799\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 57, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_all_no_loser_filtered_by_int = pept_act_sum_ps_all_no_loser.loc[\n", - " (pept_act_sum_ps_all_no_loser[\"log_sum_intensity\"] > 2)\n", - " # & (pept_act_sum_ps_all_no_loser[\"target_decoy_score\"] > 0)\n", - "]\n", - "pept_act_sum_ps_all_no_loser_filtered_by_int[\"Decoy\"].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "11048" - ] - }, - "execution_count": 60, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_all_no_loser_filtered_by_int.loc[\n", - " pept_act_sum_ps_all_no_loser_filtered_by_int[\"Decoy\"], \"mz_rank\"\n", - "].isin(isolated_decoys_all).sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 82, - "metadata": {}, - "outputs": [], - "source": [ - "def eval_fdr_and_decoy_composition(\n", - " pept_act_sum_df: pd.DataFrame, filter_dict: dict, isolated_decoys_all: set\n", - "):\n", - " pept_act_sum_df_filtered = pept_act_sum_df\n", - "\n", - " for col, value in filter_dict.items():\n", - " assert col in pept_act_sum_df.columns\n", - " f\"Column '{col}' not found in pept_act_sum_df\"\n", - " pept_act_sum_df_filtered = pept_act_sum_df_filtered.loc[\n", - " (pept_act_sum_df_filtered[col] >= value[0])\n", - " & (pept_act_sum_df_filtered[col] <= value[1])\n", - " ]\n", - " print(pept_act_sum_df_filtered[\"Decoy\"].value_counts(normalize=True))\n", - " print(\n", - " pept_act_sum_df_filtered.loc[pept_act_sum_df_filtered[\"Decoy\"], \"mz_rank\"]\n", - " .isin(isolated_decoys_all)\n", - " .sum()\n", - " )\n", - " n_targets = (~pept_act_sum_df_filtered[\"Decoy\"]).sum()\n", - " n_decoys = pept_act_sum_df_filtered[\"Decoy\"].sum()\n", - " n_isolated_decoys = (\n", - " pept_act_sum_df_filtered.loc[pept_act_sum_df_filtered[\"Decoy\"], \"mz_rank\"]\n", - " .isin(isolated_decoys_all)\n", - " .sum()\n", - " )\n", - " logging.info(f\"Number of targets: {n_targets}\")\n", - " logging.info(f\"Number of decoys: {n_decoys}\")\n", - " logging.info(f\"Number of isolated decoys: {n_isolated_decoys}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['sum_intensity', 'mz_rank', 'out_score', 'target_decoy_score',\n", - " 'competition', 'Decoy', 'log_sum_intensity'],\n", - " dtype='object')" - ] - }, - "execution_count": 74, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_all.columns" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-08 19:08:55,348 - root - INFO - Number of targets: 78790\n", - "2024-09-08 19:08:55,349 - root - INFO - Number of decoys: 42242\n", - "2024-09-08 19:08:55,349 - root - INFO - Number of isolated decoys: 11095\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Decoy\n", - "False 0.650985\n", - "True 0.349015\n", - "Name: proportion, dtype: float64\n", - "11095\n" - ] - } - ], - "source": [ - "pept_act_sum_ps_all[\"log_sum_intensity\"] = np.log10(\n", - " pept_act_sum_ps_all[\"sum_intensity\"] + 1\n", - ")\n", - "eval_fdr_and_decoy_composition(\n", - " pept_act_sum_df=pept_act_sum_ps_all,\n", - " filter_dict={\"log_sum_intensity\": [2, 100]},\n", - " isolated_decoys_all=isolated_decoys_all,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-08 19:27:42,708 - root - INFO - Number of targets: 78790\n", - "2024-09-08 19:27:42,709 - root - INFO - Number of decoys: 42242\n", - "2024-09-08 19:27:42,710 - root - INFO - Number of isolated decoys: 11095\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Decoy\n", - "False 0.650985\n", - "True 0.349015\n", - "Name: proportion, dtype: float64\n", - "11095\n" - ] - } - ], - "source": [ - "eval_fdr_and_decoy_composition(\n", - " pept_act_sum_df=pept_act_sum_ps_all,\n", - " filter_dict={\"log_sum_intensity\": [2, 100], \"target_decoy_score\": [0.0001, 1]},\n", - " isolated_decoys_all=isolated_decoys_all,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-08 19:09:29,949 - root - INFO - Number of targets: 77163\n", - "2024-09-08 19:09:29,950 - root - INFO - Number of decoys: 40799\n", - "2024-09-08 19:09:29,950 - root - INFO - Number of isolated decoys: 11048\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Decoy\n", - "False 0.654134\n", - "True 0.345866\n", - "Name: proportion, dtype: float64\n", - "11048\n" - ] - } - ], - "source": [ - "eval_fdr_and_decoy_composition(\n", - " pept_act_sum_df=pept_act_sum_ps_all_no_loser,\n", - " filter_dict={\"log_sum_intensity\": [2, 100]},\n", - " isolated_decoys_all=isolated_decoys_all,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 101, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-09-08 19:28:04,439 - root - INFO - Number of targets: 67630\n", - "2024-09-08 19:28:04,440 - root - INFO - Number of decoys: 13529\n", - "2024-09-08 19:28:04,441 - root - INFO - Number of isolated decoys: 3529\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Decoy\n", - "False 0.833303\n", - "True 0.166697\n", - "Name: proportion, dtype: float64\n", - "3529\n" - ] - } - ], - "source": [ - "eval_fdr_and_decoy_composition(\n", - " pept_act_sum_df=pept_act_sum_ps_tdc,\n", - " filter_dict={\"log_sum_intensity\": [2, 100]},\n", - " isolated_decoys_all=isolated_decoys_all,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 102, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.1478633742422002" - ] - }, - "execution_count": 102, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(13529 - 3529) / 67630" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### where is the MQ exp ID lost" - ] - }, - { - "cell_type": "code", - "execution_count": 181, - "metadata": {}, - "outputs": [], - "source": [ - "mq_exp_rank = maxquant_result_ref.loc[\n", - " (maxquant_result_ref[\"source\"] != \"ref\") & (maxquant_result_ref[\"Decoy\"] == 0),\n", - " \"mz_rank\",\n", - "].values" - ] - }, - { - "cell_type": "code", - "execution_count": 182, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "27211" - ] - }, - "execution_count": 182, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_all_no_loser[\"mz_rank\"].isin(mq_exp_rank).sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 183, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_target_decoy_distr(\n", - " pept_act_sum_ps_all[pept_act_sum_ps_all[\"mz_rank\"].isin(mq_exp_rank)],\n", - " # save_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\"),\n", - " dataset_name=\"fullset_no_loser\",\n", - " main_plot_type=\"scatter\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 165, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_target_decoy_distr(\n", - " pept_act_sum_ps_all_no_loser_filtered_by_int,\n", - " # save_dir=os.path.join(cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\"),\n", - " dataset_name=\"fullset_no_loser\",\n", - " main_plot_type=\"scatter\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 214, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-09-06 14:43:03> Number of entries before filtering: 80895\n", - "2024-09-06 14:43:03> Number of entries after filtering by log_sum_intensity with condition [1, 100]: 60080\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from peak_detection_2d.utils import plot_target_decoy_distr, calc_fdr_and_thres\n", - "\n", - "pred_df_new = calc_fdr_and_thres(\n", - " pept_act_sum_ps_all_no_loser_tdc,\n", - " filter_dict={\"log_sum_intensity\": [1, 100]},\n", - " return_plot=True,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 233, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 233, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import seaborn as sns\n", - "\n", - "sns.histplot(\n", - " data=pept_act_sum_ps_all_no_loser_tdc.loc[\n", - " pept_act_sum_ps_all_no_loser_tdc[\"sum_intensity\"] > 10\n", - " ],\n", - " x=\"target_decoy_score\",\n", - " bins=20,\n", - " kde=True,\n", - " hue=\"Decoy\",\n", - " common_norm=True,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 234, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy\n", - "False 37763\n", - "True 6186\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 234, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pred_df_new.loc[pred_df_new[\"target_decoy_score\"] > 0.2, \"Decoy\"].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 235, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1591" - ] - }, - "execution_count": 235, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pred_df_new.loc[\n", - " (pred_df_new[\"target_decoy_score\"] > 0.2)\n", - " & (pred_df_new[\"mz_rank\"].isin(difficult_decoy_mz_rank_all))\n", - "][\"mz_rank\"].count()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### First TDC, then compete for signals" - ] - }, - { - "cell_type": "code", - "execution_count": 236, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-09-06 14:54:59> FDR after TDC: (Decoy\n", - "False 72748\n", - "True 16649\n", - "Name: count, dtype: int64, 0.22885852532028372)\n" - ] - } - ], - "source": [ - "pept_act_sum_ps_all, pept_act_sum_ps_tdc = compete_target_decoy_pair(\n", - " pept_act_sum_ps_all, maxquant_result_ref\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 237, - "metadata": {}, - "outputs": [], - "source": [ - "maxquant_result_ref_tdc = pd.merge(\n", - " left=maxquant_result_ref,\n", - " right=pept_act_sum_ps_tdc[\"mz_rank\"],\n", - " on=[\"mz_rank\"],\n", - " how=\"right\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 238, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Processing groups: 100%|██████████| 17663/17663 [00:42<00:00, 416.10it/s]\n" - ] - } - ], - "source": [ - "mz_bin_groups_tdc = (\n", - " maxquant_result_ref_tdc.groupby(\"mz_bin\")\n", - " .filter(lambda x: len(x) > 1)\n", - " .groupby(\"mz_bin\")\n", - ")\n", - "# Step 3: Apply the function to each group and concatenate the results\n", - "signal_compete_tdc = pd.concat(\n", - " [\n", - " generate_signal_compete_pairs_within_group(group)\n", - " for name, group in tqdm(mz_bin_groups_tdc, desc=\"Processing groups\")\n", - " ]\n", - ").reset_index(drop=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 239, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-09-06 14:57:44> Number of pairs after filtering rt and im distance: 44289\n", - "2024-09-06 14:57:44> Number of pairs after filtering by log sum intensity: 38638\n", - "2024-09-06 14:57:44> Number of pairs with delta log intensity < 0.5: 20282\n", - "2024-09-06 14:57:49> Number of winners, losers and no competition: competition\n", - "no_competition 42946\n", - "loser 24165\n", - "winner 22286\n", - "Name: count, dtype: int64\n" - ] - } - ], - "source": [ - "pept_act_sum_ps_tdc, result_after_compete_tdc = compete_candidates_for_signal(\n", - " result=signal_compete_tdc,\n", - " pept_act_sum_ps=pept_act_sum_ps_tdc,\n", - " log_sum_intensity_thres=1,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 261, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2024-09-06 15:12:40> Number of entries before filtering: 65232\n", - "2024-09-06 15:12:40> Number of entries after filtering by log_sum_intensity with condition [2, 100]: 56996\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pred_df_new = calc_fdr_and_thres(\n", - " pept_act_sum_ps_tdc.loc[\n", - " (pept_act_sum_ps_tdc[\"competition\"] != \"loser\")\n", - " # & (~pept_act_sum_ps_tdc[\"mz_rank\"].isin(difficult_decoy_mz_rank_all))\n", - " ],\n", - " filter_dict={\"log_sum_intensity\": [2, 100]},\n", - " return_plot=True,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 262, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy\n", - "False 38982\n", - "True 5870\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 262, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "1451" - ] - }, - "execution_count": 262, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pred_df_new.loc[(pred_df_new[\"target_decoy_score\"] > 0.2), \"Decoy\"].value_counts()\n", - "pred_df_new.loc[\n", - " (pred_df_new[\"target_decoy_score\"] > 0.2)\n", - " & (pred_df_new[\"mz_rank\"].isin(difficult_decoy_mz_rank_all))\n", - "][\"mz_rank\"].count()" - ] - }, - { - "cell_type": "code", - "execution_count": 310, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_log_int_filter = pept_act_sum_ps.loc[\n", - " pept_act_sum_ps[\"log_sum_intensity\"] > 2\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 312, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy\n", - "False 67630\n", - "True 13529\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 312, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_log_int_filter[\"Decoy\"].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 330, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "9542" - ] - }, - "execution_count": 330, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_log_int_filter[\"mz_rank\"].isin(isolated_decoys).sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 317, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_all_no_loser_log_int_filter = pept_act_sum_ps_all_no_loser.loc[\n", - " pept_act_sum_ps_all_no_loser[\"log_sum_intensity\"] > 2\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 318, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy\n", - "False 52233\n", - "True 21814\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 318, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_all_no_loser_log_int_filter[\"Decoy\"].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 263, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "91564" - ] - }, - "execution_count": 263, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def check_unique_candidate(\n", - " result_filtered, col_entry1=\"mz_rank_entry1\", col_entry2=\"mz_rank_entry2\"\n", - "):\n", - " # Assuming result_filtered is your DataFrame with 'mz_rank_entry1' and 'mz_rank_entry2'\n", - " # Get unique values from each column\n", - " unique_values_entry1 = result_filtered[col_entry1].unique()\n", - " unique_values_entry2 = result_filtered[col_entry2].unique()\n", - "\n", - " # Combine the unique values from both columns\n", - " all_unique_values = pd.unique(\n", - " pd.concat([pd.Series(unique_values_entry1), pd.Series(unique_values_entry2)])\n", - " )\n", - "\n", - " # Calculate the total number of unique values\n", - " total_unique_values = len(all_unique_values)\n", - " return total_unique_values\n", - "\n", - "\n", - "check_unique_candidate(result_filtered_with_score_no_low_int)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import logging\n", - "from itertools import combinations\n", - "\n", - "\n", - "def compete_pairs(candidates, thres):\n", - " \"\"\"\n", - " Compete pairs of candidates and eliminate the one with the lowest score\n", - " based on the weighted Intersection over Union (wIoU) metric.\n", - "\n", - " Args:\n", - " candidates (list): A list of candidate objects.\n", - " thres (float): Threshold for wIoU comparison.\n", - "\n", - " Returns:\n", - " list: The remaining candidates after competition.\n", - " \"\"\"\n", - " # Generate all unique pairs from the candidates list\n", - " candidate_pairs = list(combinations(candidates, 2))\n", - "\n", - " # Iterate through each pair of candidates\n", - " while len(candidate_pairs) > 0:\n", - " (i, j) = candidate_pairs[0]\n", - " # Calculate the weighted IoU between the two candidates\n", - " if wIoU(i, j) > thres:\n", - " # Identify the candidate with the lower score\n", - " loser = i if score(i) < score(j) else j\n", - "\n", - " # Remove the loser from the candidates list\n", - " candidates = [x for x in candidates if x != loser]\n", - "\n", - " # Remove all pairs involving the loser\n", - " candidate_pairs = [pair for pair in candidate_pairs if loser not in pair]\n", - "\n", - " # Log the removal\n", - " logging.info(\"Removed candidate %s\", loser)\n", - " else:\n", - " candidate_pairs.remove((i, j))\n", - "\n", - " # Return the remaining candidates\n", - " return candidates\n", - "\n", - "\n", - "# Example placeholder functions for wIoU and score\n", - "def wIoU(candidate1, candidate2):\n", - " # This function should compute the weighted Intersection over Union between two candidates\n", - " # Replace this with the actual computation\n", - " return 0.3 # Dummy value\n", - "\n", - "\n", - "def score(candidate):\n", - " # This function should return a score for a candidate\n", - " # Replace this with actual scoring logic\n", - " return 0.5 # Dummy value" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Target Decoy Log Intensity" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'pept_act_sum_df_full' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[75], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mpept_act_sum_df_full\u001b[49m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mData\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTarget\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2\u001b[0m pept_act_sum_df_full\u001b[38;5;241m.\u001b[39mloc[pept_act_sum_df_full[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDecoy\u001b[39m\u001b[38;5;124m\"\u001b[39m], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mData\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDecoy\u001b[39m\u001b[38;5;124m\"\u001b[39m\n", - "\u001b[0;31mNameError\u001b[0m: name 'pept_act_sum_df_full' is not defined" - ] - } - ], - "source": [ - "pept_act_sum_df_full[\"Data\"] = \"Target\"\n", - "pept_act_sum_df_full.loc[pept_act_sum_df_full[\"Decoy\"], \"Data\"] = \"Decoy\"" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'pept_act_sum_df_full' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[74], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m pept_act_sum_ps_full \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mmerge(\n\u001b[0;32m----> 2\u001b[0m left\u001b[38;5;241m=\u001b[39m\u001b[43mpept_act_sum_df_full\u001b[49m,\n\u001b[1;32m 3\u001b[0m right\u001b[38;5;241m=\u001b[39mpept_act_sum_ps,\n\u001b[1;32m 4\u001b[0m on\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmz_rank\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDecoy\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mData\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[1;32m 5\u001b[0m how\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mleft\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 6\u001b[0m suffixes\u001b[38;5;241m=\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m_ps\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 7\u001b[0m )\n\u001b[1;32m 8\u001b[0m pept_act_sum_ps_full[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlog_sum_intensity_ps\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mfillna(\u001b[38;5;241m0\u001b[39m, inplace\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n", - "\u001b[0;31mNameError\u001b[0m: name 'pept_act_sum_df_full' is not defined" - ] - } - ], - "source": [ - "pept_act_sum_ps_full = pd.merge(\n", - " left=pept_act_sum_df_full,\n", - " right=pept_act_sum_ps,\n", - " on=[\"mz_rank\", \"Decoy\", \"Data\"],\n", - " how=\"left\",\n", - " suffixes=(\"\", \"_ps\"),\n", - ")\n", - "pept_act_sum_ps_full[\"log_sum_intensity_ps\"].fillna(0, inplace=True)\n", - "# # pept_act_sum_ps_full = pept_act_sum_ps\n", - "# pept_act_sum_ps_full[\"Data\"] = \"Target\"\n", - "# pept_act_sum_ps_full.loc[pept_act_sum_ps_full[\"Decoy\"], \"Data\"] = \"Decoy\"" - ] - }, - { - "cell_type": "code", - "execution_count": 159, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_ps_full.loc[\n", - " pept_act_sum_ps_full[\"target_decoy_score\"] < 0.2, \"log_sum_intensity_os\"\n", - "] = 0" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [ - { - "ename": "ValueError", - "evalue": "Could not interpret value `Data` for `hue`. An entry with this name does not appear in `data`.", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[73], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m ax \u001b[38;5;241m=\u001b[39m \u001b[43msns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhistplot\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[43mpept_act_sum_ps_tdc_all\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlog_sum_intensity\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43mhue\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mData\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[43mfill\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[43mhue_order\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mDecoy\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mTarget\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# palette=custom_cmap,\u001b[39;49;00m\n\u001b[1;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[43mmultiple\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mdodge\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 9\u001b[0m \u001b[43m \u001b[49m\u001b[43mcommon_norm\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43mbins\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m20\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 11\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m 12\u001b[0m plt\u001b[38;5;241m.\u001b[39mxlabel(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mLog10(Infered Intensity)\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 13\u001b[0m plt\u001b[38;5;241m.\u001b[39msavefig(\n\u001b[1;32m 14\u001b[0m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(\n\u001b[1;32m 15\u001b[0m ps_exp_dir, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpaper_figures\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtarget_decoy_score_after_ps_and_tdc.png\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 18\u001b[0m bbox_inches\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtight\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 19\u001b[0m )\n", - "File \u001b[0;32m~/.local/lib/python3.10/site-packages/seaborn/distributions.py:1379\u001b[0m, in \u001b[0;36mhistplot\u001b[0;34m(data, x, y, hue, weights, stat, bins, binwidth, binrange, discrete, cumulative, common_bins, common_norm, multiple, element, fill, shrink, kde, kde_kws, line_kws, thresh, pthresh, pmax, cbar, cbar_ax, cbar_kws, palette, hue_order, hue_norm, color, log_scale, legend, ax, **kwargs)\u001b[0m\n\u001b[1;32m 1358\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhistplot\u001b[39m(\n\u001b[1;32m 1359\u001b[0m data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m,\n\u001b[1;32m 1360\u001b[0m \u001b[38;5;66;03m# Vector variables\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1376\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m 1377\u001b[0m ):\n\u001b[0;32m-> 1379\u001b[0m p \u001b[38;5;241m=\u001b[39m \u001b[43m_DistributionPlotter\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1380\u001b[0m \u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1381\u001b[0m \u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mdict\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhue\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweights\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mweights\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1382\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1384\u001b[0m p\u001b[38;5;241m.\u001b[39mmap_hue(palette\u001b[38;5;241m=\u001b[39mpalette, order\u001b[38;5;241m=\u001b[39mhue_order, norm\u001b[38;5;241m=\u001b[39mhue_norm)\n\u001b[1;32m 1386\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ax \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "File \u001b[0;32m~/.local/lib/python3.10/site-packages/seaborn/distributions.py:110\u001b[0m, in \u001b[0;36m_DistributionPlotter.__init__\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m 104\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 105\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 106\u001b[0m data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 107\u001b[0m variables\u001b[38;5;241m=\u001b[39m{},\n\u001b[1;32m 108\u001b[0m ):\n\u001b[0;32m--> 110\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/.local/lib/python3.10/site-packages/seaborn/_base.py:634\u001b[0m, in \u001b[0;36mVectorPlotter.__init__\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m 629\u001b[0m \u001b[38;5;66;03m# var_ordered is relevant only for categorical axis variables, and may\u001b[39;00m\n\u001b[1;32m 630\u001b[0m \u001b[38;5;66;03m# be better handled by an internal axis information object that tracks\u001b[39;00m\n\u001b[1;32m 631\u001b[0m \u001b[38;5;66;03m# such information and is set up by the scale_* methods. The analogous\u001b[39;00m\n\u001b[1;32m 632\u001b[0m \u001b[38;5;66;03m# information for numeric axes would be information about log scales.\u001b[39;00m\n\u001b[1;32m 633\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_var_ordered \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124my\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mFalse\u001b[39;00m} \u001b[38;5;66;03m# alt., used DefaultDict\u001b[39;00m\n\u001b[0;32m--> 634\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massign_variables\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 636\u001b[0m \u001b[38;5;66;03m# TODO Lots of tests assume that these are called to initialize the\u001b[39;00m\n\u001b[1;32m 637\u001b[0m \u001b[38;5;66;03m# mappings to default values on class initialization. I'd prefer to\u001b[39;00m\n\u001b[1;32m 638\u001b[0m \u001b[38;5;66;03m# move away from that and only have a mapping when explicitly called.\u001b[39;00m\n\u001b[1;32m 639\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m var \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhue\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msize\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstyle\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n", - "File \u001b[0;32m~/.local/lib/python3.10/site-packages/seaborn/_base.py:679\u001b[0m, in \u001b[0;36mVectorPlotter.assign_variables\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m 674\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 675\u001b[0m \u001b[38;5;66;03m# When dealing with long-form input, use the newer PlotData\u001b[39;00m\n\u001b[1;32m 676\u001b[0m \u001b[38;5;66;03m# object (internal but introduced for the objects interface)\u001b[39;00m\n\u001b[1;32m 677\u001b[0m \u001b[38;5;66;03m# to centralize / standardize data consumption logic.\u001b[39;00m\n\u001b[1;32m 678\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minput_format \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlong\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 679\u001b[0m plot_data \u001b[38;5;241m=\u001b[39m \u001b[43mPlotData\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 680\u001b[0m frame \u001b[38;5;241m=\u001b[39m plot_data\u001b[38;5;241m.\u001b[39mframe\n\u001b[1;32m 681\u001b[0m names \u001b[38;5;241m=\u001b[39m plot_data\u001b[38;5;241m.\u001b[39mnames\n", - "File \u001b[0;32m~/.local/lib/python3.10/site-packages/seaborn/_core/data.py:58\u001b[0m, in \u001b[0;36mPlotData.__init__\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m 51\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 52\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 53\u001b[0m data: DataSource,\n\u001b[1;32m 54\u001b[0m variables: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, VariableSpec],\n\u001b[1;32m 55\u001b[0m ):\n\u001b[1;32m 57\u001b[0m data \u001b[38;5;241m=\u001b[39m handle_data_source(data)\n\u001b[0;32m---> 58\u001b[0m frame, names, ids \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_assign_variables\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 60\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mframe \u001b[38;5;241m=\u001b[39m frame\n\u001b[1;32m 61\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnames \u001b[38;5;241m=\u001b[39m names\n", - "File \u001b[0;32m~/.local/lib/python3.10/site-packages/seaborn/_core/data.py:232\u001b[0m, in \u001b[0;36mPlotData._assign_variables\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m 230\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 231\u001b[0m err \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAn entry with this name does not appear in `data`.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 232\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(err)\n\u001b[1;32m 234\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 235\u001b[0m \n\u001b[1;32m 236\u001b[0m \u001b[38;5;66;03m# Otherwise, assume the value somehow represents data\u001b[39;00m\n\u001b[1;32m 237\u001b[0m \n\u001b[1;32m 238\u001b[0m \u001b[38;5;66;03m# Ignore empty data structures\u001b[39;00m\n\u001b[1;32m 239\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(val, Sized) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(val) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n", - "\u001b[0;31mValueError\u001b[0m: Could not interpret value `Data` for `hue`. An entry with this name does not appear in `data`." - ] - } - ], - "source": [ - "ax = sns.histplot(\n", - " pept_act_sum_ps_tdc_all,\n", - " x=\"log_sum_intensity\",\n", - " hue=\"Data\",\n", - " fill=True,\n", - " hue_order=[\"Decoy\", \"Target\"],\n", - " # palette=custom_cmap,\n", - " multiple=\"dodge\",\n", - " common_norm=True,\n", - " bins=20,\n", - ")\n", - "plt.xlabel(\"Log10(Infered Intensity)\")\n", - "plt.savefig(\n", - " os.path.join(\n", - " ps_exp_dir, \"paper_figures\", \"target_decoy_score_after_ps_and_tdc.png\"\n", - " ),\n", - " dpi=300,\n", - " bbox_inches=\"tight\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 161, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "log_sum_intensity_ps Data \n", - "0.000000 Decoy 75806\n", - " Target 21627\n", - "4.853750 Target 2\n", - "3.772958 Target 2\n", - "4.910022 Target 2\n", - " ... \n", - "4.277771 Target 1\n", - "4.277759 Target 1\n", - "4.277755 Target 1\n", - "4.277733 Target 1\n", - "7.219709 Decoy 1\n", - "Name: count, Length: 81312, dtype: int64" - ] - }, - "execution_count": 161, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_full[[\"log_sum_intensity_ps\", \"Data\"]].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 162, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Data\n", - "Decoy 89397\n", - "Target 89397\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 162, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pept_act_sum_ps_full[\"Data\"].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 164, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.847970289830755" - ] - }, - "execution_count": 164, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "0.24192086982784658" - ] - }, - "execution_count": 164, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "75806 / 89397\n", - "21627 / 89397" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Protein level FDR" - ] - }, - { - "cell_type": "code", - "execution_count": 97, - "metadata": {}, - "outputs": [], - "source": [ - "dict_with_int = pd.merge(\n", - " maxquant_result_ref,\n", - " pept_act_sum_ps.loc[\n", - " (pept_act_sum_ps[\"log_sum_intensity\"] > 2)\n", - " & (pept_act_sum_ps[\"target_decoy_score\"] >= 0.55)\n", - " ],\n", - " on=[\"mz_rank\", \"Decoy\"],\n", - " how=\"inner\",\n", - ")\n", - "dict_with_int[\"Leading razor proteins_td_labeled\"] = dict_with_int[\"Proteins\"].str.cat(\n", - " dict_with_int[\"Decoy\"].astype(str), sep=\"_\"\n", - ")\n", - "td_protein_count = (\n", - " dict_with_int.groupby([\"Leading razor proteins_td_labeled\", \"Decoy\"])[\"Sequence\"]\n", - " .count()\n", - " .reset_index()\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Decoy\n", - "False 4441\n", - "True 1316\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 99, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "td_protein_count_filtered = td_protein_count.loc[td_protein_count[\"Sequence\"] >= 2]\n", - "td_protein_count_filtered[\"Decoy\"].value_counts()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Batch effect trouble shooting" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "metadata": {}, - "outputs": [], - "source": [ - "pept_act_sum_df = pept_act_sum_ps" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 62, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Batch effect from different source in Intensity')" - ] - }, - "execution_count": 62, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import seaborn as sns\n", - "\n", - "dict_with_int_all = pd.merge(maxquant_result_ref, pept_act_sum_df, on=[\"mz_rank\"])\n", - "dict_with_int_all = dict_with_int_all.loc[dict_with_int_all[\"Decoy\"] == 0]\n", - "sns.kdeplot(\n", - " data=dict_with_int,\n", - " x=\"log_sum_intensity\",\n", - " hue=\"source\",\n", - " fill=True,\n", - " common_norm=False,\n", - ")\n", - "plt.title(\"Batch effect from different source in Intensity\")\n", - "plt.savefig(\n", - " os.path.join(ps_exp_dir, \"results\", \"batch_effect_intensity_target.png\"), dpi=300\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 69, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Batch effect from different source in target-decoy score')" - ] - }, - "execution_count": 69, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dict_with_int_all = pd.merge(\n", - " maxquant_result_ref, pept_act_sum_df, on=[\"mz_rank\"], how=\"inner\"\n", - ")\n", - "dict_with_int_all = dict_with_int_all.loc[dict_with_int_all[\"Decoy\"]]\n", - "sns.kdeplot(\n", - " data=dict_with_int_all,\n", - " x=\"target_decoy_score\",\n", - " hue=\"source\",\n", - " fill=True,\n", - " common_norm=False,\n", - ")\n", - "plt.title(\"Batch effect from different source in target-decoy score\")\n", - "plt.savefig(\n", - " os.path.join(ps_exp_dir, \"results\", \"batch_effect_td_score_decoy.png\"), dpi=300\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 70, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Batch effect from different source in target-decoy score')" - ] - }, - "execution_count": 70, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dict_with_int_all = pd.merge(maxquant_result_ref, pept_act_sum_df, on=[\"mz_rank\"])\n", - "dict_with_int_all = dict_with_int_all.loc[dict_with_int_all[\"Decoy\"] == 0]\n", - "sns.kdeplot(\n", - " data=dict_with_int_all,\n", - " x=\"target_decoy_score\",\n", - " hue=\"source\",\n", - " fill=True,\n", - " common_norm=False,\n", - ")\n", - "\n", - "plt.title(\"Batch effect from different source in target-decoy score\")\n", - "plt.savefig(\n", - " os.path.join(ps_exp_dir, \"results\", \"batch_effect_td_score_target.png\"), dpi=300\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Batch effect on target_decoy_score')" - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sns.kdeplot(\n", - " data=dict_with_int_all,\n", - " x=\"target_decoy_score\",\n", - " hue=\"source\",\n", - " fill=True,\n", - " common_norm=True,\n", - ")\n", - "plt.title(\"Batch effect on target_decoy_score\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "sbs", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/paper_03_ref_vs_pred_im.ipynb b/notebooks/paper_03_ref_vs_pred_im.ipynb deleted file mode 100644 index 56a8374..0000000 --- a/notebooks/paper_03_ref_vs_pred_im.ipynb +++ /dev/null @@ -1,338 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from importlib import reload\n", - "from IPython.core.interactiveshell import InteractiveShell\n", - "%load_ext autoreload\n", - "InteractiveShell.ast_node_interactivity = \"all\"\n", - "import logging\n", - "logging.basicConfig(\n", - " level=logging.INFO, format=\"%(asctime)s - %(name)s - %(levelname)s - %(message)s\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-30 12:18:44,247 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n", - "2024-10-30 12:18:44,249 - numexpr.utils - INFO - NumExpr defaulting to 8 threads.\n", - "/cmnfs/home/z.xiao/miniconda3/envs/sbs/lib/python3.10/site-packages/pandas/core/arrays/masked.py:60: UserWarning: Pandas requires version '1.3.6' or newer of 'bottleneck' (version '1.3.5' currently installed).\n", - " from pandas.core import (\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "import pandas as pd\n", - "import os\n", - "import sys\n", - "import matplotlib.pyplot as plt\n", - "\n", - "module_path = os.path.abspath(os.path.join(\"..\"))\n", - "if module_path not in sys.path:\n", - " sys.path.append(module_path)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Load data" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "metadata": {}, - "outputs": [], - "source": [ - "## IM_ref\n", - "swaps_config_path = \"/cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_ref_20241002_165602_293498/config_20241003_074426_198157.yaml\"\n", - "ps_dir = \"exp_20241003_083433_946837\"\n", - "from utils.config import get_cfg_defaults\n", - "from utils.singleton_swaps_optimization import swaps_optimization_cfg\n", - "\n", - "cfg = get_cfg_defaults(swaps_optimization_cfg)\n", - "cfg.merge_from_file(swaps_config_path)\n", - "cfg.PEAK_SELECTION.merge_from_file(\n", - " os.path.join(\n", - " cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"updated_peak_selection_config.yaml\"\n", - " )\n", - ")\n", - "maxquant_result_ref = pd.read_pickle(cfg.DICT_PICKLE_PATH)\n", - "\n", - "mobility_values_df = pd.read_csv(os.path.join(cfg.RESULT_PATH, \"mobility_values.csv\"))\n", - "ms1scans = pd.read_csv(os.path.join(cfg.RESULT_PATH, \"ms1scans.csv\"))\n", - "pept_act_sum_ps_full_tdc = pd.read_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH,\n", - " \"peak_selection\",\n", - " ps_dir,\n", - " \"pept_act_sum_ps_full_tdc_fdr_thres.csv\",\n", - " )\n", - ")\n", - "test_pred_df = pd.read_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\", \"test_pred_df.csv\"\n", - " )\n", - ")\n", - "# test_pred_df = pd.merge(test_pred_df, maxquant_result_ref, on=[\"mz_rank\", \"Decoy\"])\n", - "test_pred_df = pd.merge(test_pred_df, maxquant_result_ref, on=[\"mz_rank\", \"Decoy\"])\n", - "save_dir = \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/ref_vs_pred_im/\"\n", - "dataset_name = \"im_ref\"" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": {}, - "outputs": [], - "source": [ - "## IM pred\n", - "swaps_config_path = \"/cmnfs/proj/ORIGINS/SWAPS_exp/short_gradient/30min_3to45_7R_120min_lib_im_pred_20241004_074414_299434/config_20241004_074414_299434.yaml\"\n", - "ps_dir = \"exp_20241004_093657_807920\"\n", - "\n", - "cfg = get_cfg_defaults(swaps_optimization_cfg)\n", - "cfg.merge_from_file(swaps_config_path)\n", - "cfg.PEAK_SELECTION.merge_from_file(\n", - " os.path.join(\n", - " cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"updated_peak_selection_config.yaml\"\n", - " )\n", - ")\n", - "maxquant_result_ref = pd.read_pickle(cfg.DICT_PICKLE_PATH)\n", - "\n", - "mobility_values_df = pd.read_csv(os.path.join(cfg.RESULT_PATH, \"mobility_values.csv\"))\n", - "ms1scans = pd.read_csv(os.path.join(cfg.RESULT_PATH, \"ms1scans.csv\"))\n", - "pept_act_sum_ps_full_tdc = pd.read_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH,\n", - " \"peak_selection\",\n", - " ps_dir,\n", - " \"pept_act_sum_ps_full_tdc_fdr_thres.csv\",\n", - " )\n", - ")\n", - "test_pred_df = pd.read_csv(\n", - " os.path.join(\n", - " cfg.RESULT_PATH, \"peak_selection\", ps_dir, \"results\", \"test_pred_df.csv\"\n", - " )\n", - ")\n", - "# test_pred_df = pd.merge(test_pred_df, maxquant_result_ref, on=[\"mz_rank\", \"Decoy\"])\n", - "test_pred_df = pd.merge(test_pred_df, maxquant_result_ref, on=[\"mz_rank\", \"Decoy\"])\n", - "save_dir = \"/cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/ref_vs_pred_im/\"\n", - "dataset_name = \"im_pred\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Peak selection and scoring model performance\n", - "Use only test_pred_df" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [], - "source": [ - "from matplotlib.colors import ListedColormap\n", - "\n", - "custom_cmap = ListedColormap([\"#FF5733\", \"#33FF57\", \"#3357FF\"]) # Custom colors\n", - "custom_labels = [\"Targets\", \"Decoys\"] # Custom label names" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plot" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [], - "source": [ - "test_pred_df_full = pd.merge(\n", - " left=test_pred_df,\n", - " right=maxquant_result_ref[[\"mz_rank\", \"Decoy\"]],\n", - " on=[\"mz_rank\", \"Decoy\"],\n", - " how=\"left\",\n", - ")\n", - "test_pred_df_full[\"Data\"] = \"Target\"\n", - "test_pred_df_full.loc[test_pred_df_full[\"Decoy\"], \"Data\"] = \"Decoy\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Test set targets" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_843811/3333441363.py:2: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " test_pred_df_targets[\"Pass Intensity Filter\"] = (\n", - "/tmp/ipykernel_843811/3333441363.py:5: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " test_pred_df_targets[\"Pass Conf. Score Filter\"] = (\n", - "/tmp/ipykernel_843811/3333441363.py:8: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " test_pred_df_targets[\"Pass Both Filter\"] = (\n" - ] - } - ], - "source": [ - "test_pred_df_targets = test_pred_df_full.loc[~test_pred_df_full[\"Decoy\"]]\n", - "test_pred_df_targets[\"Pass Intensity Filter\"] = (\n", - " test_pred_df_targets[\"log_sum_intensity\"] >= 2\n", - ")\n", - "test_pred_df_targets[\"Pass Conf. Score Filter\"] = (\n", - " test_pred_df_targets[\"target_decoy_score\"] >= 0.2\n", - ")\n", - "test_pred_df_targets[\"Pass Both Filter\"] = (\n", - " test_pred_df_targets[\"Pass Intensity Filter\"]\n", - " & test_pred_df_targets[\"Pass Conf. Score Filter\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n", - "/cmnfs/home/z.xiao/.local/lib/python3.10/site-packages/seaborn/_base.py:948: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", - " data_subset = grouped_data.get_group(pd_key)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "50%: 0.82\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-30 13:52:35,111 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/ref_vs_pred_im/PS_model_test_per_image_weighted_iou_metric_distribution_im_pred.png\n", - "2024-10-30 13:52:35,406 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/ref_vs_pred_im/PS_model_test_per_image_weighted_iou_metric_distribution_im_pred.svg\n" - ] - } - ], - "source": [ - "%autoreload 2\n", - "from peak_detection_2d.utils import plot_per_image_metric_distr\n", - "\n", - "plot_per_image_metric_distr(\n", - " loss_array=test_pred_df_targets,\n", - " metric_name=\"per_image_weighted_iou_metric\",\n", - " save_dir=save_dir,\n", - " hue=\"Pass Intensity Filter\",\n", - " title =\"Test Set Weighted IoU (Pred IM)\",\n", - " xlabel=\"Weighted IoU\",\n", - " show_quantiles=[50],\n", - " palette={False: \"#d8a6a6\", True: \"#a00000\"},\n", - " hue_order=[False, True],\n", - " dataset_name=dataset_name\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-10-30 13:52:42,764 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/ref_vs_pred_im/roc_auc_im_pred.png\n", - "2024-10-30 13:52:42,954 - utils.plot - INFO - Save plot at /cmnfs/proj/ORIGINS/SWAPS_exp/SWAPS_paper_figures/fig3_FDR/ref_vs_pred_im/roc_auc_im_pred.svg\n" - ] - }, - { - "data": { - "text/plain": [ - "0.7199242651558383" - ] - }, - "execution_count": 77, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from peak_detection_2d.utils import plot_roc_auc\n", - "\n", - "plot_roc_auc(\n", - " pred_df=test_pred_df,\n", - " save_dir=save_dir,\n", - " dataset_name=dataset_name,\n", - " title=\"Test Set ROC AUC (Pred IM)\",\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "sbs", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/pyproject.toml b/pyproject.toml index 5ebe8c1..74df33a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -47,6 +47,7 @@ dependencies = [ "tensorboard==2.12.3", "tqdm==4.66.5", "yacs==0.1.8", + "pyteomics==4.6.2" ] [project.scripts] sbs_runner_ims = "sbs_runner_ims:main" diff --git a/swaps/optimization/inference.py b/swaps/optimization/inference.py index 343dbc9..b65df89 100644 --- a/swaps/optimization/inference.py +++ b/swaps/optimization/inference.py @@ -746,6 +746,105 @@ def slice_frame_data_blocks(frame_data, col_cut_indices_start, col_cut_indices_e return frame_data_blocks +def process_one_frame( + ms1scans: pd.DataFrame, + ms1_frame_idx: int, + maxquant_result_ref_with_im_index_sortmz: pd.DataFrame, + return_pept_act: bool = False, + mz_bin_digits: int = 3, + process_in_blocks: bool = True, + debug: bool = False, +): + """Process one frame data without IMS dimension with sparse encoding and peak selection.""" + Logger.debug("Start data preparation.") + # prepare data + frame_data = ms1scans.loc[ms1scans["MS1_frame_idx"] == ms1_frame_idx] + Logger.debug("Frame data shape: %s", frame_data.shape[0]) + peaks_df = pd.DataFrame() + pept_act_coo = { + "coord_frame_indices": [], + "coord_pept_indices": [], + "data": [], + } + if frame_data.shape[0] > 0: + scan_time = np.round(ms1scans.loc[ms1_frame_idx, "Time_minute"], decimals=4) + Logger.info("Scan time: %s", scan_time) + candidate_precursor_by_rt = maxquant_result_ref_with_im_index_sortmz.loc[ + (maxquant_result_ref_with_im_index_sortmz["RT_search_left"] <= scan_time) + & (maxquant_result_ref_with_im_index_sortmz["RT_search_right"] >= scan_time) + ] + Logger.info( + "Number of candidates by RT in frame %s: %s", + ms1_frame_idx, + candidate_precursor_by_rt.shape[0], + ) + if candidate_precursor_by_rt.shape[0] > 0: + candidate_precursor_by_rt.sort_values( + "mz_rank", ascending=True, inplace=True + ) + all_frame_pept_idx = candidate_precursor_by_rt.mz_rank.values + ( + frame_array, + candidate_array, + ) = _prepare_sparse_matrices( + candidate_precursor_by_rt=candidate_precursor_by_rt, + frame_data=frame_data, + all_id=all_frame_pept_idx, + mz_bin_digits=mz_bin_digits, + use_ims=False, + ) + + assert frame_array.shape[1] == candidate_array.shape[1] + Logger.debug("Start optimization with sparse encoding.") + if candidate_precursor_by_rt.shape[0] > 6000 and process_in_blocks: + im_pept_act = sparse_encode_divide_and_conquer( + frame_array, candidate_array + ) + else: + # optimization with sparse encoding + im_pept_act = sparse_encode( + frame_array, + candidate_array, + algorithm="threshold", + alpha=0, + positive=True, + ) + Logger.debug("Start peak selection.") + if return_pept_act: + pept_act_coo = {} + nonzero_indices = np.nonzero(im_pept_act) + pept_act_coo["data"] = im_pept_act[nonzero_indices] + pept_act_coo["coord_frame_indices"] = np.repeat( + ms1_frame_idx, len(pept_act_coo["data"]) + ) + # pept_act_coo["coord_im_indices"] = nonzero_indices[0] + pept_act_coo["coord_pept_indices"] = all_frame_pept_idx[ + nonzero_indices[1] + ] + else: + Logger.info("No candidate precursor by RT from frame %s", ms1_frame_idx) + else: + Logger.info("No data for frame index %s", ms1_frame_idx) + if debug: + return ( + peaks_df, + pept_act_coo, + frame_array, + candidate_array, + im_pept_act, + candidate_precursor_by_rt, + all_frame_pept_idx, + ) + else: + return ( + peaks_df, + pept_act_coo, + # candidate_array, + # frame_array, + # im_pept_act, + ) # TODO: remove candidate array + + def process_one_frame_ims( data: pd.DataFrame, ms1scans: pd.DataFrame, @@ -796,11 +895,12 @@ def process_one_frame_ims( frame_array, candidate_array, ) = _prepare_sparse_matrices( - candidate_precursor_by_rt, - frame_data, - mobility_values, - all_frame_pept_idx, + candidate_precursor_by_rt=candidate_precursor_by_rt, + frame_data=frame_data, + mobility_values=mobility_values, + all_id=all_frame_pept_idx, mz_bin_digits=mz_bin_digits, + use_ims=True, ) assert frame_array.shape[1] == candidate_array.shape[1] @@ -905,7 +1005,52 @@ def make_coo_from_dict(data_dict, shape: tuple, cutoff: List[int]): ) -def process_batch_frame_ims( +def make_coo_from_dict_no_ims(data_dict, shape: tuple, cutoff: List[int]): + Logger.info("Shape of COO matrix: %s", shape) + if len(cutoff) > 1: + coo_list = [] + # n_pept_in_blocks = shape[2] // n_blocks_by_pept + # cutoff = [(n_pept_in_blocks * (i + 1)) for i in range(n_blocks_by_pept - 1)] + # cutoff.append(shape[2] + 1) + Logger.debug("cutoff list %s", cutoff) + prev_cutoff = 0 + for cutoff_i in cutoff: + block_idx = np.where( + (prev_cutoff <= np.array(data_dict["coord_pept_indices"])) + & (np.array(data_dict["coord_pept_indices"]) < cutoff_i) + )[0].astype(int) + Logger.info("block index %s", block_idx) + if len(block_idx) > 0: + coo_list.append( + sparse.COO( + coords=[ + list( + itemgetter(*block_idx)(data_dict["coord_frame_indices"]) + ), + # list(itemgetter(*block_idx)(data_dict["coord_im_indices"])), + list( + itemgetter(*block_idx)(data_dict["coord_pept_indices"]) + ), + ], + data=list(itemgetter(*block_idx)(data_dict["data"])), + shape=shape, + ) + ) + prev_cutoff = cutoff_i + return coo_list + else: + return sparse.COO( + coords=[ + data_dict["coord_frame_indices"], + # data_dict["coord_im_indices"], + data_dict["coord_pept_indices"], + ], + data=data_dict["data"], + shape=shape, + ) + + +def process_batch_frame( data: pd.DataFrame, ms1scans: pd.DataFrame, batch_scan_idx: list, @@ -919,53 +1064,88 @@ def process_batch_frame_ims( save_dir: str = "", return_im_pept_act: bool = False, extract_im_peak: bool = True, + use_ims: bool = True, **kwargs, ): batch_peaks_df = [] - batch_im_rt_pept_act_coo_dict = { - "coord_frame_indices": [], - "coord_im_indices": [], - "coord_pept_indices": [], - "data": [], - } + if use_ims: + batch_im_rt_pept_act_coo_dict = { + "coord_frame_indices": [], + "coord_im_indices": [], + "coord_pept_indices": [], + "data": [], + } + else: + batch_rt_pept_act_coo_dict = { + "coord_frame_indices": [], + "coord_pept_indices": [], + "data": [], + } for scan_idx in batch_scan_idx: Logger.debug("Start processing frame index %s", scan_idx) - peaks_df, frame_im_pept_act_coo = process_one_frame_ims( - data=data, - ms1scans=ms1scans, - ms1_frame_idx=scan_idx, - maxquant_result_ref_with_im_index_sortmz=maxquant_result_ref_with_im_index, - mobility_values=mobility_values, - delta_mobility_thres=delta_mobility_thres, - mz_bin_digits=mz_bin_digits, - process_in_blocks=process_in_blocks, - return_im_pept_act=return_im_pept_act, - extract_im_peak=extract_im_peak, - **kwargs, - ) - if extract_im_peak: - batch_peaks_df.append(peaks_df) - if return_im_pept_act: - for key in batch_im_rt_pept_act_coo_dict.keys(): - batch_im_rt_pept_act_coo_dict[key].extend(frame_im_pept_act_coo[key]) + if use_ims: + peaks_df, frame_im_pept_act_coo = process_one_frame_ims( + data=data, + ms1scans=ms1scans, + ms1_frame_idx=scan_idx, + maxquant_result_ref_with_im_index_sortmz=maxquant_result_ref_with_im_index, + mobility_values=mobility_values, + delta_mobility_thres=delta_mobility_thres, + mz_bin_digits=mz_bin_digits, + process_in_blocks=process_in_blocks, + return_im_pept_act=return_im_pept_act, + extract_im_peak=extract_im_peak, + **kwargs, + ) + if extract_im_peak: + batch_peaks_df.append(peaks_df) + if return_im_pept_act: + for key in batch_im_rt_pept_act_coo_dict.keys(): + batch_im_rt_pept_act_coo_dict[key].extend( + frame_im_pept_act_coo[key] + ) + else: + peaks_df, frame_im_pept_act_coo = process_one_frame( + ms1scans=ms1scans, + ms1_frame_idx=scan_idx, + maxquant_result_ref_with_im_index_sortmz=maxquant_result_ref_with_im_index, + mz_bin_digits=mz_bin_digits, + process_in_blocks=process_in_blocks, + return_pept_act=return_im_pept_act, + ) + if return_im_pept_act: + for key in batch_rt_pept_act_coo_dict.keys(): + batch_rt_pept_act_coo_dict[key].extend(frame_im_pept_act_coo[key]) - if extract_im_peak: + if use_ims and extract_im_peak: batch_peaks_df = pd.concat(batch_peaks_df).reset_index(drop=True) batch_peaks_df.to_csv( os.path.join(save_dir, f"batch_peaks_df_{batch_num}.csv"), index=False ) if return_im_pept_act: - batch_im_rt_pept_act_coo = make_coo_from_dict( - batch_im_rt_pept_act_coo_dict, - shape=( - len(ms1scans.index.values) - + 1, # this index is rank, starting from 1, add 1 for the last frame - len(mobility_values), - len(maxquant_result_ref_with_im_index.mz_rank) - + 1, # this index is rank, starting from 1, add 1 for the last frame - ), - cutoff=cutoff, - ) + if use_ims: + batch_im_rt_pept_act_coo = make_coo_from_dict( + batch_im_rt_pept_act_coo_dict, + shape=( + len(ms1scans.index.values) + + 1, # this index is rank, starting from 1, add 1 for the last frame + len(mobility_values), + len(maxquant_result_ref_with_im_index.mz_rank) + + 1, # this index is rank, starting from 1, add 1 for the last frame + ), + cutoff=cutoff, + ) + else: + batch_im_rt_pept_act_coo = make_coo_from_dict_no_ims( + batch_rt_pept_act_coo_dict, + shape=( + len(ms1scans.index.values) + + 1, # this index is rank, starting from 1, add 1 for the last frame + len(maxquant_result_ref_with_im_index.mz_rank) + + 1, # this index is rank, starting from 1, add 1 for the last frame + ), + cutoff=cutoff, + ) if isinstance(batch_im_rt_pept_act_coo, list): for pept_batch_idx, pept_batch_dict in enumerate(batch_im_rt_pept_act_coo): @@ -999,9 +1179,10 @@ def process_batch_frame_ims( def _prepare_sparse_matrices( candidate_precursor_by_rt, frame_data, - mobility_values, all_id, mz_bin_digits: int = 3, + use_ims: bool = True, + mobility_values: pd.DataFrame = None, ): # prepare arrays from sparse matrices candidate_id = np.repeat( @@ -1016,8 +1197,10 @@ def _prepare_sparse_matrices( ) candidate_id_index = np.searchsorted(all_id, candidate_id) - - frame_mz = np.round(frame_data["mz_values"], decimals=mz_bin_digits) + if use_ims: + frame_mz = np.round(frame_data["mz_values"], decimals=mz_bin_digits) + else: + frame_mz = np.round(frame_data["mzarray"].values[0], decimals=mz_bin_digits) all_mz = np.sort(np.array(list(set(frame_mz).union(set(candidate_mz))))) Logger.debug( "Number of mz values in candidate, frame and joint:%s, %s, %s", @@ -1027,17 +1210,26 @@ def _prepare_sparse_matrices( ) candidate_mz_index = np.searchsorted(all_mz, candidate_mz) frame_mz_index = np.searchsorted(all_mz, frame_mz) - # Logger.info("all_mz shape %s", all_mz.shape) - # Logger.info("frame mz shape %s", frame_mz.shape) - all_im = np.sort(mobility_values["mobility_values"]) - # Logger.info("mobility values columns %s", mobility_values.columns) - # Logger.info("all_im shape %s", all_im.shape) - # Logger.info("frame mobility shape %s", frame_data["mobility_values"].shape) - frame_im_index = np.searchsorted(all_im, frame_data["mobility_values"]) - - frame_coo = coo_matrix( - (frame_data["intensity_values"], (frame_im_index, frame_mz_index)), - ) + if use_ims: + assert mobility_values is not None + all_im = np.sort(mobility_values["mobility_values"]) + frame_im_index = np.searchsorted(all_im, frame_data["mobility_values"]) + + frame_coo = coo_matrix( + (frame_data["intensity_values"], (frame_im_index, frame_mz_index)), + ) + else: + intarray = frame_data["intarray"].values[0] + frame_coo = coo_matrix( + ( + intarray, + ( + np.zeros(len(intarray)).astype(int), + frame_mz_index, + ), + ), + shape=(1, len(all_mz)), + ) candidate_coo = coo_matrix( (candidate_abundance, (candidate_id_index, candidate_mz_index)) ) @@ -1224,7 +1416,7 @@ def generate_id_partitions( return id_partitions -def process_ims_frames_parallel( +def process_frames_parallel( n_jobs: int, batch_scan_indices: list, data, @@ -1239,10 +1431,11 @@ def process_ims_frames_parallel( save_dir: str = "", return_im_pept_act: bool = False, extract_im_peak: bool = True, + use_ims: bool = True, # n_blocks_by_pept: int = 0, ): list_batch_im_pept_act_coo_dict = Parallel(n_jobs=n_jobs)( - delayed(process_batch_frame_ims)( + delayed(process_batch_frame)( data=data, maxquant_result_ref_with_im_index=maxquant_ref, ms1scans=ms1scans, @@ -1257,6 +1450,7 @@ def process_ims_frames_parallel( return_im_pept_act=return_im_pept_act, extract_im_peak=extract_im_peak, cutoff=cutoff, + use_ims=use_ims, ) for batch in batch_scan_indices ) diff --git a/swaps/prepare_dict/prepare_dict.py b/swaps/prepare_dict/prepare_dict.py index ea1ce68..0544fa7 100644 --- a/swaps/prepare_dict/prepare_dict.py +++ b/swaps/prepare_dict/prepare_dict.py @@ -38,6 +38,7 @@ def merge_ref_and_exp( maxquant_exp_df: pd.DataFrame, save_dir: str, ref_type: str = ["MQ", "pred"], + use_ims: bool = True, ): """Merge dictionaries from multiple files using Modified sequence and Charge""" # evaluate the elution counts of the experiment file @@ -123,16 +124,17 @@ def merge_ref_and_exp( "Calibrated retention time start", "Calibrated retention time", "Calibrated retention time finish", - "mobility_values_index_left_ref", - "mobility_values_index_right_ref", - "mobility_values_index_center_ref", - # "mobility_values_left_ref", - # "mobility_values_right_ref", - "mobility_values_center_ref", # "mobility_values_left_ref", # "mobility_values_right_ref", # "mobility_values_center_ref", ] + if use_ims: + ref_spec_columns += [ + "mobility_values_index_left_ref", + "mobility_values_index_right_ref", + "mobility_values_index_center_ref", + "mobility_values_center_ref", + ] Logger.info("ref spec columns: %s", ref_spec_columns) elif ref_type in ["pred"]: ref_spec_columns = [] @@ -1218,6 +1220,7 @@ def construct_dict( random_seed: int = 42, n_blocks_by_pept: int = 1, keep_matched_precursors: bool = False, + use_ims: bool = True, # device: str = "gpu", ): gpu_count = torch.cuda.device_count() @@ -1244,16 +1247,25 @@ def construct_dict( maxquant_exp_df.shape, ) if not keep_matched_precursors: - maxquant_exp_df = maxquant_exp_df.loc[ - maxquant_exp_df["Type"].isin(["TIMS-MULTI-MSMS"]) - ] + if use_ims: + maxquant_exp_df = maxquant_exp_df.loc[ + maxquant_exp_df["Type"].isin(["TIMS-MULTI-MSMS"]) + ] + maxquant_ref_df = maxquant_ref_df.loc[ + maxquant_ref_df["Type"].isin(["TIMS-MULTI-MSMS"]) + ] + else: + maxquant_exp_df = maxquant_exp_df.loc[ + maxquant_exp_df["Type"].isin(["MULTI-MSMS", "MSMS"]) + ] + maxquant_ref_df = maxquant_ref_df.loc[ + maxquant_ref_df["Type"].isin(["MULTI-MSMS", "MSMS"]) + ] Logger.info( "maxquant_exp_df size after removing matched precursors: %s", maxquant_exp_df.shape, ) - maxquant_ref_df = maxquant_ref_df.loc[ - maxquant_ref_df["Type"].isin(["TIMS-MULTI-MSMS"]) - ] + Logger.info( "maxquant_ref_df size after removing matched precursors: %s", maxquant_ref_df.shape, @@ -1263,21 +1275,23 @@ def construct_dict( rt_values_df["Time_minute"].max(), ) Logger.info("RT index range: %s", rt_range) - im_range = ( - mobility_values_df["mobility_values"].min(), - mobility_values_df["mobility_values"].max(), - ) - im_idx_range = ( - mobility_values_df["mobility_values_index"].min(), - mobility_values_df["mobility_values_index"].max(), - ) - Logger.info("IM index range: %s", im_range) construct_dict_dir = os.path.join(result_dir, "construct_dict") rt_transfer_dir = os.path.join(construct_dict_dir, "RT_transfer_learn") - im_transfer_dir = os.path.join(construct_dict_dir, "IM_transfer_learn") os.makedirs(construct_dict_dir, exist_ok=True) os.makedirs(rt_transfer_dir, exist_ok=True) - os.makedirs(im_transfer_dir, exist_ok=True) + if use_ims: + im_range = ( + mobility_values_df["mobility_values"].min(), + mobility_values_df["mobility_values"].max(), + ) + im_idx_range = ( + mobility_values_df["mobility_values_index"].min(), + mobility_values_df["mobility_values_index"].max(), + ) + Logger.info("IM index range: %s", im_range) + + im_transfer_dir = os.path.join(construct_dict_dir, "IM_transfer_learn") + os.makedirs(im_transfer_dir, exist_ok=True) maxquant_exp_filtered_path = os.path.join( construct_dict_dir, "maxquant_exp_filtered.txt" ) @@ -1313,7 +1327,7 @@ def construct_dict( Logger.info("Using existing RT model") delta_rt_95 = cfg_prepare_dict.RT_TOL # IM - if cfg_prepare_dict.IM_REF == "pred": + if use_ims and cfg_prepare_dict.IM_REF == "pred": if cfg_prepare_dict.UPDATED_IM_MODEL_PATH == "": Logger.info("Retraining IM model with AlphaPeptDeep") if not _LOADED_ALPHA_DATASET: @@ -1350,21 +1364,22 @@ def construct_dict( mq_rt_right_col="Calibrated retention time finish", idx_suffix="_exp", ) # exp values are based on the calibration - maxquant_exp_df = dict_add_im_index( - maxquant_df=maxquant_exp_df, - mobility_values_df=mobility_values_df, - mq_im_center_col="1/K0", - idx_suffix="_exp", - ) - if ref_type == "MQ": - # dict_add_rt_index doesn't work for ref values - maxquant_ref_df = dict_add_im_index( - maxquant_df=maxquant_ref_df, + if use_ims: + maxquant_exp_df = dict_add_im_index( + maxquant_df=maxquant_exp_df, mobility_values_df=mobility_values_df, mq_im_center_col="1/K0", - idx_suffix="_ref", - im_idx_length=None, + idx_suffix="_exp", ) + # dict_add_rt_index doesn't work for ref values + if ref_type == "MQ": + maxquant_ref_df = dict_add_im_index( + maxquant_df=maxquant_ref_df, + mobility_values_df=mobility_values_df, + mq_im_center_col="1/K0", + idx_suffix="_ref", + im_idx_length=None, + ) # merge reference and experiment maxquant_dict = merge_ref_and_exp( @@ -1372,6 +1387,7 @@ def construct_dict( maxquant_exp_df=maxquant_exp_df, save_dir=construct_dict_dir, ref_type=ref_type, + use_ims=use_ims, ) # generate decoy first and then predict RT and IM @@ -1426,55 +1442,58 @@ def construct_dict( raise ValueError(f"RT reference {cfg_prepare_dict.RT_REF} not supported") # add im pred - match cfg_prepare_dict.IM_REF: - case "pred": - maxquant_dict = dict_add_alpha_pept_pred( - model_path=cfg_prepare_dict.UPDATED_IM_MODEL_PATH, - pept_property="mobility", - dict_for_pred_path=dict_path, - maxquant_dict=maxquant_dict, - lc_grad=cfg_prepare_dict.RT_MAX, - device=device, - ) - case "align_lr": - maxquant_dict, delta_im_95 = dict_add_im_align_lr( - maxquant_dict, - train_frac=cfg_prepare_dict.TRAIN_FRAC, - random_state=random_seed, + if use_ims: + match cfg_prepare_dict.IM_REF: + case "pred": + maxquant_dict = dict_add_alpha_pept_pred( + model_path=cfg_prepare_dict.UPDATED_IM_MODEL_PATH, + pept_property="mobility", + dict_for_pred_path=dict_path, + maxquant_dict=maxquant_dict, + lc_grad=cfg_prepare_dict.RT_MAX, + device=device, + ) + case "align_lr": + maxquant_dict, delta_im_95 = dict_add_im_align_lr( + maxquant_dict, + train_frac=cfg_prepare_dict.TRAIN_FRAC, + random_state=random_seed, + ) + cfg_prepare_dict.DELTA_IM_95 = delta_im_95.item() + case "ref": + Logger.info("Using ref IM for IM prediction") + pass + case "mix": + Logger.info("Using mix IM for IM reference/prediction") + pass + case "exp": + Logger.info("Using exp IM for IM reference") + pass + case _: + raise ValueError( + f"IM reference {cfg_prepare_dict.IM_REF} not supported" + ) + maxquant_dict = maxquant_dict.rename( + mapper={"mobility_values_index": "mobility_pred_idx"}, axis=1 + ) + # specify im tolerence for search range (expected ion mobility length) + if cfg_prepare_dict.IM_LENGTH < 0: + Logger.info( + "IM tolerance not specified, using 99.9 percentile of experiment IM length" ) - cfg_prepare_dict.DELTA_IM_95 = delta_im_95.item() - case "ref": - Logger.info("Using ref IM for IM prediction") - pass - case "mix": - Logger.info("Using mix IM for IM reference/prediction") - pass - case "exp": - Logger.info("Using exp IM for IM reference") - pass - case _: - raise ValueError(f"IM reference {cfg_prepare_dict.IM_REF} not supported") - maxquant_dict = maxquant_dict.rename( - mapper={"mobility_values_index": "mobility_pred_idx"}, axis=1 - ) - # specify im tolerence for search range (expected ion mobility length) - if cfg_prepare_dict.IM_LENGTH < 0: - Logger.info( - "IM tolerance not specified, using 99.9 percentile of experiment IM length" + im_length = ( + int(maxquant_exp_df["Ion mobility length"].quantile(0.999) + 2) // 2 + ) # TODO: currently using only exp IM length + cfg_prepare_dict.IM_LENGTH = im_length + + maxquant_dict = _define_im_idx_search_range( + maxquant_df=maxquant_dict, + im_length=cfg_prepare_dict.IM_LENGTH, + im_ref=cfg_prepare_dict.IM_REF, + im_idx_range=im_idx_range, + delta_im_95=cfg_prepare_dict.DELTA_IM_95, + mobility_values_df=mobility_values_df, ) - im_length = ( - int(maxquant_exp_df["Ion mobility length"].quantile(0.999) + 2) // 2 - ) # TODO: currently using only exp IM length - cfg_prepare_dict.IM_LENGTH = im_length - - maxquant_dict = _define_im_idx_search_range( - maxquant_df=maxquant_dict, - im_length=cfg_prepare_dict.IM_LENGTH, - im_ref=cfg_prepare_dict.IM_REF, - im_idx_range=im_idx_range, - delta_im_95=cfg_prepare_dict.DELTA_IM_95, - mobility_values_df=mobility_values_df, - ) maxquant_dict = _define_rt_search_range( maxquant_result_dict=maxquant_dict, rt_tol=float(cfg_prepare_dict.RT_TOL), diff --git a/swaps/sbs_runner_ims.py b/swaps/sbs_runner_ims.py index 880c283..73c706d 100644 --- a/swaps/sbs_runner_ims.py +++ b/swaps/sbs_runner_ims.py @@ -14,9 +14,10 @@ export_im_and_ms1scans, combine_3d_act_and_sum_int, ) +from utils.tools import load_mzml from utils.config import get_cfg_defaults from utils.singleton_swaps_optimization import swaps_optimization_cfg -from optimization.inference import process_ims_frames_parallel, generate_id_partitions +from optimization.inference import process_frames_parallel, generate_id_partitions from peak_detection_2d.dataset.prepare_dataset import prepare_training_dataset from peak_detection_2d.infer_on_pept_act import infer_on_pept_act from peak_detection_2d.train import train @@ -60,9 +61,12 @@ def opt_scan_by_scan(config_path: str): if cfg.OPTIMIZATION.N_BATCH < 0: cfg.OPTIMIZATION.N_BATCH = cfg.N_CPU # set batches as the same as N_CPU # Load data - data, hdf_file_name = load_dotd_data( - cfg.DATA_PATH, swaps_result_dir=cfg.EXPORT_DATA_HDF5_DIR - ) + if cfg.USE_IMS: + data, hdf_file_name = load_dotd_data( + cfg.DATA_PATH, swaps_result_dir=cfg.EXPORT_DATA_HDF5_DIR + ) + else: + data = load_mzml(cfg.DATA_PATH, unify_format=True) if cfg.DICT_PICKLE_PATH != "": maxquant_result_ref = pd.read_pickle(filepath_or_buffer=cfg.DICT_PICKLE_PATH) ms1scans = pd.read_csv(os.path.join(cfg.RESULT_PATH, "ms1scans.csv")) @@ -72,26 +76,27 @@ def opt_scan_by_scan(config_path: str): else: # Get the lowest level directory name with .d extension dir_with_extension = os.path.basename(os.path.normpath(cfg.DATA_PATH)) + dir_wo_extension = dir_with_extension.split(".")[0] if ( len(cfg.FILTER_EXP_BY_RAW_FILE) == 0 ): # if not specified, get the lowest level directory name with .d extension, by default None - cfg.FILTER_EXP_BY_RAW_FILE.append(dir_with_extension.rstrip(".d")) - - ms1scans, mobility_values_df = export_im_and_ms1scans( - data=data, swaps_result_dir=cfg.RESULT_PATH - ) + cfg.FILTER_EXP_BY_RAW_FILE.append(dir_wo_extension) + if dir_with_extension.endswith(".d"): + ms1scans, mobility_values_df = export_im_and_ms1scans( + data=data, swaps_result_dir=cfg.RESULT_PATH + ) + elif dir_with_extension.endswith(".mzML"): + ms1scans = data + mobility_values_df = None maxquant_result_ref = pd.read_csv(cfg.MQ_REF_PATH, sep="\t", low_memory=False) - # TODO filter ref df if needed if len(cfg.FILTER_REF_BY_RAW_FILE) > 0: if cfg.FILTER_REF_BY_RAW_FILE[0] == "data": maxquant_result_ref = maxquant_result_ref[ - maxquant_result_ref["Raw file"].isin( - [dir_with_extension.rstrip(".d")] - ) + maxquant_result_ref["Raw file"].isin([dir_wo_extension]) ] logging.info( "Filtered reference maxquant result by raw file: %s, resulting ref rows: %s", - dir_with_extension.rstrip(".d"), + dir_wo_extension, maxquant_result_ref.shape[0], ) else: @@ -108,6 +113,7 @@ def opt_scan_by_scan(config_path: str): filter_exp_by_raw_file=cfg.FILTER_EXP_BY_RAW_FILE, maxquant_exp_path=cfg.MQ_EXP_PATH, # maxquant_exp_df=maxquant_result_exp, + use_ims=cfg.USE_IMS, maxquant_ref_df=maxquant_result_ref, result_dir=os.path.join(cfg.RESULT_PATH), mobility_values_df=mobility_values_df, @@ -120,15 +126,22 @@ def opt_scan_by_scan(config_path: str): logging.info( "Peptide batch index: %s", maxquant_result_ref["pept_batch_idx"].unique() ) - peptact_shape = ( - ( - len(ms1scans.index.values) - + 1, # this index is rank, starting from 1, add 1 for the last frame - len(mobility_values_df), + if cfg.USE_IMS: + peptact_shape = ( + ( + len(ms1scans.index.values) + + 1, # this index is rank, starting from 1, add 1 for the last frame + len(mobility_values_df), + len(maxquant_result_ref.mz_rank) + + 1, # this index is rank, starting from 1, add 1 for the last frame + ), + ) + else: + peptact_shape = ( + len(ms1scans.index.values) + 1, # this index is rank, starting from 1 len(maxquant_result_ref.mz_rank) - + 1, # this index is rank, starting from 1, add 1 for the last frame - ), - ) + + 1, # this index is rank, starting from 1 + ) cfg.PREPARE_DICT = cfg_prepare_dict cfg.DICT_PICKLE_PATH = dict_pickle_path cfg.OPTIMIZATION.PEPTACT_SHAPE = peptact_shape @@ -184,7 +197,7 @@ def opt_scan_by_scan(config_path: str): logging.info("indices in first batch: %s", batch_scan_indices[0]) # process scans cutoff = get_mzrank_batch_cutoff(maxquant_result_ref) - process_ims_frames_parallel( + process_frames_parallel( data=data, n_jobs=cfg.N_CPU, ms1scans=ms1scans, @@ -199,6 +212,7 @@ def opt_scan_by_scan(config_path: str): save_dir=act_dir, return_im_pept_act=True, extract_im_peak=False, + use_ims=cfg.USE_IMS, ) minutes, seconds = divmod(time.time() - start_time, 60) @@ -214,9 +228,10 @@ def opt_scan_by_scan(config_path: str): n_blocks_by_pept=cfg.OPTIMIZATION.N_BLOCKS_BY_PEPT, n_batch=cfg.OPTIMIZATION.N_BATCH, act_dir=act_dir, - remove_batch_file=False, + remove_batch_file=True, calc_pept_act_sum_filter_by_im=cfg.RESULT_ANALYSIS.POST_PROCESSING.FILTER_BY_IM, maxquant_result_ref=maxquant_result_ref, + use_ims=cfg.USE_IMS, im_ref=cfg.PREPARE_DICT.IM_REF, ) diff --git a/swaps/utils/exp_configs/config_ayla_test.yaml b/swaps/utils/exp_configs/config_ayla_test.yaml new file mode 100644 index 0000000..82ac6f8 --- /dev/null +++ b/swaps/utils/exp_configs/config_ayla_test.yaml @@ -0,0 +1,31 @@ +RESULT_PATH: /cmnfs/proj/ORIGINS/SWAPS_exp/test_thermo/test_ayla +ADD_TIMESTAMP_TO_RESULT_PATH: true +DATA_PATH: /cmnfs/data/proteomics/origin/ayla_proteometools_subset/01709a_GB1-TUM_first_pool_100_01_01-DDA-1h-R1.mzML +DEBUG: false +DICT_PICKLE_PATH: '' +EXPORT_DATA_HDF5_DIR: '' +MQ_REF_PATH: /cmnfs/data/proteomics/origin/ayla_proteometools_subset/TUM_first_pool_100_01_01_DDA-1h-R1-tryptic/evidence.txt +FILTER_REF_BY_RAW_FILE: ['01709a_GB1-TUM_first_pool_100_01_01-DDA-1h-R1'] +MQ_EXP_PATH: /cmnfs/data/proteomics/origin/ayla_proteometools_subset/TUM_first_pool_100_01_01_DDA-1h-R1-tryptic/evidence.txt +FILTER_EXP_BY_RAW_FILE: [] +USE_IMS: false +N_CPU: 5 +OPTIMIZATION: + N_BLOCKS_BY_PEPT: 1 + N_BATCH: 5 +PREPARE_DICT: + DICT_PICKLE_PATH: '' + FILTER_PRED_BY_RAW_FILE: '' + FILTER_TRAIN_BY_RAW_FILE: '' + GENERATE_DECOY: false + ISO_MIN_AB_THRES: 0.01 + KEEP_MATCHED_PRECURSORS: false + MZ_BIN_DIGITS: 2 + RT_REF: exp + RT_TOL: 0.01 +RANDOM_SEED: 42 +PEAK_SELECTION: + ENABLE: false +RESULT_ANALYSIS: + ENABLE: true + diff --git a/swaps/utils/ims_utils.py b/swaps/utils/ims_utils.py index 173a556..c134d0c 100644 --- a/swaps/utils/ims_utils.py +++ b/swaps/utils/ims_utils.py @@ -110,6 +110,7 @@ def combine_3d_act_and_sum_int( remove_batch_file: bool = False, calc_pept_act_sum_filter_by_im: bool = False, maxquant_result_ref: pd.DataFrame = None, + use_ims: bool = True, im_ref: str = "exp", ): """ @@ -136,10 +137,21 @@ def combine_3d_act_and_sum_int( act_dir, f"im_rt_pept_act_coo_peptbatch{pept_block_num}.npz" ) ) - if pept_block_num == 0: - pept_act_sum_all = act_3d_all.sum(axis=(0, 1)) + Logger.info( + "Loaded 3D activation intensity data for pept batch %s with shape %s", + pept_block_num, + act_3d_all.shape, + ) + if use_ims: + if pept_block_num == 0: + pept_act_sum_all = act_3d_all.sum(axis=(0, 1)) + else: + pept_act_sum_all += act_3d_all.sum(axis=(0, 1)) else: - pept_act_sum_all += act_3d_all.sum(axis=(0, 1)) + if pept_block_num == 0: + pept_act_sum_all = act_3d_all.sum(axis=0) + else: + pept_act_sum_all += act_3d_all.sum(axis=0) # act_3d_all = None except FileNotFoundError: for batch_num in range(n_batch): @@ -150,7 +162,10 @@ def combine_3d_act_and_sum_int( f"im_rt_pept_act_coo_batch{batch_num}_peptbatch{pept_block_num}.npz", ) ) - pept_act_sum = act_3d.sum(axis=(0, 1)) + if use_ims: + pept_act_sum = act_3d.sum(axis=(0, 1)) + else: + pept_act_sum = act_3d.sum(axis=0) logging.info("NNZ size of batch %s act_3d %s", batch_num, act_3d.nnz) if batch_num == 0: act_3d_all = act_3d @@ -207,32 +222,41 @@ def combine_3d_act_and_sum_int( ) ) pept_act_sum_array = sparse.asnumpy(pept_act_sum_all) - + Logger.info("pept_act_sum_all sum %s", pept_act_sum_array.shape) del pept_act_sum_all - # pept_act_sum_all_array = np.append(pept_act_sum_all_array, pept_act_sum_array) - pept_act_sum_df = pd.DataFrame( - pept_act_sum_array[:], - columns=["pept_act_sum"], - index=np.arange(pept_act_sum_array.shape[0]), - ) - pept_act_sum_df["mz_rank"] = pept_act_sum_df.index - pept_act_sum_df.to_csv(os.path.join(act_dir, "pept_act_sum.csv"), index=False) - if calc_pept_act_sum_filter_by_im: - pept_act_sum_filter_by_im_df = pd.DataFrame( - pept_act_sum_filter_by_im_array[:], - columns=["pept_act_sum_filter_by_im"], - index=np.arange(pept_act_sum_filter_by_im_array.shape[0]), - ) - Logger.debug( - "pept_act_sum_filter_by_im_df sum %s", - pept_act_sum_filter_by_im_df["pept_act_sum_filter_by_im"].sum(), - ) - pept_act_sum_filter_by_im_df["mz_rank"] = pept_act_sum_filter_by_im_df.index - pept_act_sum_filter_by_im_df.to_csv( - os.path.join(act_dir, "pept_act_sum_filter_by_im.csv"), index=False + if use_ims: + # pept_act_sum_all_array = np.append(pept_act_sum_all_array, pept_act_sum_array) + pept_act_sum_df = pd.DataFrame( + pept_act_sum_array[:], + columns=["pept_act_sum"], + index=np.arange(pept_act_sum_array.shape[0]), ) + pept_act_sum_df["mz_rank"] = pept_act_sum_df.index + pept_act_sum_df.to_csv(os.path.join(act_dir, "pept_act_sum.csv"), index=False) + if calc_pept_act_sum_filter_by_im: + pept_act_sum_filter_by_im_df = pd.DataFrame( + pept_act_sum_filter_by_im_array[:], + columns=["pept_act_sum_filter_by_im"], + index=np.arange(pept_act_sum_filter_by_im_array.shape[0]), + ) + Logger.debug( + "pept_act_sum_filter_by_im_df sum %s", + pept_act_sum_filter_by_im_df["pept_act_sum_filter_by_im"].sum(), + ) + pept_act_sum_filter_by_im_df["mz_rank"] = pept_act_sum_filter_by_im_df.index + pept_act_sum_filter_by_im_df.to_csv( + os.path.join(act_dir, "pept_act_sum_filter_by_im.csv"), index=False + ) - return pept_act_sum_filter_by_im_df # TODO: remove later + return pept_act_sum_filter_by_im_df # TODO: remove later + else: + pept_act_sum_df = pd.DataFrame( + pept_act_sum_array, + columns=["pept_act_sum"], + index=np.arange(len(pept_act_sum_array)), + ) + pept_act_sum_df["mz_rank"] = pept_act_sum_df.index + pept_act_sum_df.to_csv(os.path.join(act_dir, "pept_act_sum.csv"), index=False) def sum_3d_act_filter_by_im_fast( diff --git a/swaps/utils/tools.py b/swaps/utils/tools.py index 24b3f91..95dea97 100644 --- a/swaps/utils/tools.py +++ b/swaps/utils/tools.py @@ -222,7 +222,7 @@ def match_time_to_scan( return df -def load_mzml(msconvert_file: str): +def load_mzml(msconvert_file: str, unify_format: bool = False): """ read data from mzml format @@ -260,10 +260,22 @@ def load_mzml(msconvert_file: str): mzarray = [x.tolist() for x in mzarray] intarray = [x.tolist() for x in intarray] col_set = ["ind", "mslev", "bpmz", "bpint", "starttime", "mzarray", "intarray"] + df_ms1 = pd.DataFrame( list(zip(ind, mslev, bpmz, bpint, starttime, mzarray, intarray)), columns=col_set, ) + if unify_format: + df_ms1.rename( + mapper={ + "starttime": "Time_minute", + "ind": "Id", + "bpint": "MaxIntensity", + }, + axis=1, + inplace=True, + ) + df_ms1["MS1_frame_idx"] = df_ms1["Id"] Logger.info("Saving data to pickle file") df_ms1.to_pickle(msconvert_file[:-5] + ".pkl")